From feae98561c9ad8c3e71a05de861c0303eb32debc Mon Sep 17 00:00:00 2001 From: zhuwenxing Date: Thu, 5 Dec 2024 23:49:48 +0800 Subject: [PATCH] refactor Signed-off-by: zhuwenxing --- README.md | 39 ++----- archives/2020/01.md | 2 - archives/2020/02.md | 2 - archives/2020/03.md | 2 - archives/2020/04.md | 2 - archives/2020/05.md | 2 - archives/2020/06.md | 2 - archives/2020/07.md | 2 - archives/2020/08.md | 2 - archives/2020/09.md | 2 - archives/2020/10.md | 2 - archives/2020/11.md | 2 - archives/2020/12.md | 2 - archives/2021/05.md | 59 +++++------ archives/2021/06.md | 218 +++++++++++++++----------------------- archives/2021/07.md | 155 +++++++++++---------------- archives/2021/08.md | 169 ++++++++++++----------------- archives/2021/09.md | 141 +++++++++---------------- archives/2021/10.md | 210 +++++++++++++++--------------------- archives/2021/11.md | 196 +++++++++++++--------------------- archives/2021/12.md | 156 ++++++++++----------------- archives/2022/01.md | 136 +++++++++--------------- archives/2022/02.md | 199 +++++++++++++---------------------- archives/2022/03.md | 216 ++++++++++++++------------------------ archives/2022/04.md | 127 +++++++++------------- archives/2022/05.md | 198 ++++++++++++++-------------------- archives/2022/06.md | 212 ++++++++++++++----------------------- archives/2022/07.md | 178 ++++++++++++------------------- archives/2022/08.md | 194 ++++++++++++++-------------------- archives/2022/09.md | 187 ++++++++++++--------------------- archives/2022/10.md | 235 ++++++++++++++++------------------------- archives/2022/11.md | 251 +++++++++++++++++--------------------------- archives/2022/12.md | 171 ++++++++++++------------------ archives/2023/01.md | 179 ++++++++++++------------------- archives/2023/02.md | 210 ++++++++++++++---------------------- archives/2023/03.md | 226 +++++++++++++++------------------------ archives/2023/04.md | 173 ++++++++++++------------------ archives/2023/05.md | 234 ++++++++++++++++------------------------- archives/2023/06.md | 226 +++++++++++++++------------------------ archives/2023/07.md | 180 ++++++++++++------------------- archives/2023/08.md | 192 +++++++++++++-------------------- archives/2023/09.md | 219 +++++++++++++++----------------------- archives/2023/10.md | 208 ++++++++++++++---------------------- archives/2023/11.md | 177 ++++++++++++------------------- archives/2023/12.md | 225 ++++++++++++++++----------------------- archives/2024/01.md | 241 ++++++++++++++++-------------------------- archives/2024/02.md | 207 ++++++++++++++---------------------- archives/2024/03.md | 211 +++++++++++++------------------------ archives/2024/04.md | 215 +++++++++++++++---------------------- archives/2024/05.md | 213 ++++++++++++++----------------------- archives/2024/06.md | 197 +++++++++++++--------------------- archives/2024/07.md | 207 ++++++++++++++---------------------- archives/2024/08.md | 211 +++++++++++++------------------------ archives/2024/09.md | 172 +++++++++++------------------- archives/2024/10.md | 246 ++++++++++++++----------------------------- archives/2024/11.md | 211 +++++++++++++------------------------ archives/2024/12.md | 34 ++---- daily_arxiv.py | 43 +++++--- 58 files changed, 3204 insertions(+), 5324 deletions(-) delete mode 100644 archives/2020/01.md delete mode 100644 archives/2020/02.md delete mode 100644 archives/2020/03.md delete mode 100644 archives/2020/04.md delete mode 100644 archives/2020/05.md delete mode 100644 archives/2020/06.md delete mode 100644 archives/2020/07.md delete mode 100644 archives/2020/08.md delete mode 100644 archives/2020/09.md delete mode 100644 archives/2020/10.md delete mode 100644 archives/2020/11.md delete mode 100644 archives/2020/12.md diff --git a/README.md b/README.md index accb8635..23c1f675 100644 --- a/README.md +++ b/README.md @@ -8,41 +8,22 @@ This project automatically tracks and analyzes papers from eess.SP (Electrical E The main features include: - Daily updates of papers with open-source implementations - Focus on signal processing and information theory research -- Automatic tracking and organization of papers by date -- Direct links to both papers and their corresponding code repositories +- Automatic tracking and organization -## Latest Updates (Last 7 Days) +## Latest Updates ### 2024-12-04 -|paper|code| -|---|---| -|[pitn: physics-informed temporal networks for cuffless blood pressure estimation](https://arxiv.org/abs/2408.08488)|[acl-pitn](https://github.com/zest86/acl-pitn)| +|date|paper|code| +|---|---|---| ### 2024-12-03 -|paper|code| -|---|---| -|[robust graph filter identification and graph denoising from signal observations](https://arxiv.org/abs/2210.08488)|[graph_denoising](https://github.com/reysam93/graph_denoising)| -|[recurrences reveal shared causal drivers of complex time series](https://arxiv.org/abs/2301.13516)|[shrec](https://github.com/williamgilpin/shrec)| -|[kronecker-structured sparse vector recovery with application to irs-mimo channel estimation](https://arxiv.org/abs/2310.07869)|[dsr](https://github.com/yanbinhe/dsr)| -|[doorinet: door heading prediction through inertial deep learning](https://arxiv.org/abs/2402.09427)|[doorinet](https://github.com/ansfl/doorinet)| -|[sky-gvio: an enhanced gnss/ins/vision navigation with fcn-based sky-segmentation in urban canyon](https://arxiv.org/abs/2404.11070)|[sky-view-images](https://github.com/whuwangjr/sky-view-images)| -|[soundscape captioning using sound affective quality network and large language model](https://arxiv.org/abs/2406.05914)|[soundscaper](https://github.com/yuanbo2020/soundscaper)| -|[understanding generalizability of diffusion models requires rethinking the hidden gaussian structure](https://arxiv.org/abs/2410.24060)|[Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure](https://github.com/Morefre/Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure)| -|[snake-inspired mobile robot positioning with hybrid learning](https://arxiv.org/abs/2411.17430)|[MoRPINet](https://github.com/ansfl/MoRPINet)| -|[automatic differentiation-based full waveform inversion with flexible workflows](https://arxiv.org/abs/2412.00486)|[ADFWI](https://github.com/liufeng2317/ADFWI)| -|[pruned convolutional attention network based wideband spectrum sensing with sub-nyquist sampling](https://arxiv.org/abs/2412.00562)|[PCA-WSSNet](https://github.com/AI4CogComm/PCA-WSSNet)| -|[rotation invariant quantization for model compression](https://arxiv.org/abs/2303.03106)|[riq](https://github.com/ehaleva/riq)| -|[task-aware distributed source coding under dynamic bandwidth](https://arxiv.org/abs/2305.15523)|[task-aware-distributed-source-coding](https://github.com/utaustin-swarmlab/task-aware-distributed-source-coding)| -|[a truly concurrent semantics for reversible ccs](https://arxiv.org/abs/2309.14011)|[reversible-ccs-as-nets](https://github.com/hmelgra/reversible-ccs-as-nets)| +|date|paper|code| +|---|---|---| +|2412.00486|[automatic differentiation-based full waveform inversion with flexible workflows](https://arxiv.org/abs/2412.00486)|[ADFWI](https://github.com/liufeng2317/ADFWI)| +|2412.00562|[pruned convolutional attention network based wideband spectrum sensing with sub-nyquist sampling](https://arxiv.org/abs/2412.00562)|[PCA-WSSNet](https://github.com/AI4CogComm/PCA-WSSNet)| ### 2024-12-02 -|paper|code| -|---|---| -|[a time-causal and time-recursive analogue of the gabor transform](https://arxiv.org/abs/2308.14512)|[pygabor](https://github.com/tonylindeberg/pygabor)| -|[robust stochastically-descending unrolled networks](https://arxiv.org/abs/2312.15788)|[unrolledglow](https://github.com/smrhadou/unrolledglow)| -|[unleashing the power of data tsunami: a comprehensive survey on data assessment and selection for instruction tuning of language models](https://arxiv.org/abs/2408.02085)|[fantastic-data-engineering](https://github.com/yuleiqin/fantastic-data-engineering)| -|[scaling transformers for low-bitrate high-quality speech coding](https://arxiv.org/abs/2411.19842)|[stable-codec](https://github.com/Stability-AI/stable-codec)| -|[scalable exploration via ensemble++](https://arxiv.org/abs/2407.13195)|[ensemble_plus_plus](https://github.com/szrlee/ensemble_plus_plus)| -|[fast mutual information computation for large binary datasets](https://arxiv.org/abs/2411.19702)|[bulk-MI](https://github.com/aofalcao/bulk-MI)| +|date|paper|code| +|---|---|---| ## Archives diff --git a/archives/2020/01.md b/archives/2020/01.md deleted file mode 100644 index af0c90be..00000000 --- a/archives/2020/01.md +++ /dev/null @@ -1,2 +0,0 @@ -# January 2020 Archive - diff --git a/archives/2020/02.md b/archives/2020/02.md deleted file mode 100644 index 61474259..00000000 --- a/archives/2020/02.md +++ /dev/null @@ -1,2 +0,0 @@ -# February 2020 Archive - diff --git a/archives/2020/03.md b/archives/2020/03.md deleted file mode 100644 index 5738141a..00000000 --- a/archives/2020/03.md +++ /dev/null @@ -1,2 +0,0 @@ -# March 2020 Archive - diff --git a/archives/2020/04.md b/archives/2020/04.md deleted file mode 100644 index 03b5a272..00000000 --- a/archives/2020/04.md +++ /dev/null @@ -1,2 +0,0 @@ -# April 2020 Archive - diff --git a/archives/2020/05.md b/archives/2020/05.md deleted file mode 100644 index daca6a9c..00000000 --- a/archives/2020/05.md +++ /dev/null @@ -1,2 +0,0 @@ -# May 2020 Archive - diff --git a/archives/2020/06.md b/archives/2020/06.md deleted file mode 100644 index bd443908..00000000 --- a/archives/2020/06.md +++ /dev/null @@ -1,2 +0,0 @@ -# June 2020 Archive - diff --git a/archives/2020/07.md b/archives/2020/07.md deleted file mode 100644 index 830c1dd8..00000000 --- a/archives/2020/07.md +++ /dev/null @@ -1,2 +0,0 @@ -# July 2020 Archive - diff --git a/archives/2020/08.md b/archives/2020/08.md deleted file mode 100644 index bc2c7767..00000000 --- a/archives/2020/08.md +++ /dev/null @@ -1,2 +0,0 @@ -# August 2020 Archive - diff --git a/archives/2020/09.md b/archives/2020/09.md deleted file mode 100644 index 0b4a45a7..00000000 --- a/archives/2020/09.md +++ /dev/null @@ -1,2 +0,0 @@ -# September 2020 Archive - diff --git a/archives/2020/10.md b/archives/2020/10.md deleted file mode 100644 index f00b2e29..00000000 --- a/archives/2020/10.md +++ /dev/null @@ -1,2 +0,0 @@ -# October 2020 Archive - diff --git a/archives/2020/11.md b/archives/2020/11.md deleted file mode 100644 index 1000144f..00000000 --- a/archives/2020/11.md +++ /dev/null @@ -1,2 +0,0 @@ -# November 2020 Archive - diff --git a/archives/2020/12.md b/archives/2020/12.md deleted file mode 100644 index 016c1953..00000000 --- a/archives/2020/12.md +++ /dev/null @@ -1,2 +0,0 @@ -# December 2020 Archive - diff --git a/archives/2021/05.md b/archives/2021/05.md index debf0cab..903452b6 100644 --- a/archives/2021/05.md +++ b/archives/2021/05.md @@ -1,51 +1,40 @@ # May 2021 Archive ## 2021-05-31 -|paper|code| -|---|---| -|[a simulation-based end-to-end learning framework for evidential occupancy grid mapping](https://arxiv.org/abs/2102.12718)|[EviLOG](https://github.com/ika-rwth-aachen/EviLOG)| -|[salientsleepnet: multimodal salient wave detection network for sleep staging](https://arxiv.org/abs/2105.13864)|[SalientSleepNet](https://github.com/ziyujia/SalientSleepNet)| -|[recovery of future data via convolution nuclear norm minimization](https://arxiv.org/abs/1909.03889)|[CNNM](https://github.com/gcliu1982/CNNM)| +|date|paper|code| +|---|---|---| +|2105.13864|[salientsleepnet: multimodal salient wave detection network for sleep staging](https://arxiv.org/abs/2105.13864)|[SalientSleepNet](https://github.com/ziyujia/SalientSleepNet)| ## 2021-05-28 -|paper|code| -|---|---| -|[multi-resolution csi feedback with deep learning in massive mimo system](https://arxiv.org/abs/1910.14322)|[CRNet](https://github.com/Kylin9511/CRNet)| -|[unsupervised deep learning for massive mimo hybrid beamforming](https://arxiv.org/abs/2007.00038)|[HBF-Net](https://github.com/HamedHojatian/HBF-Net)| -|[robust learning from corrupted eeg with dynamic spatial filtering](https://arxiv.org/abs/2105.12916)|[dynamic-spatial-filtering](https://github.com/hubertjb/dynamic-spatial-filtering)| +|date|paper|code| +|---|---|---| +|2105.12916|[robust learning from corrupted eeg with dynamic spatial filtering](https://arxiv.org/abs/2105.12916)|[dynamic-spatial-filtering](https://github.com/hubertjb/dynamic-spatial-filtering)| ## 2021-05-27 -|paper|code| -|---|---| -|[learning to continuously optimize wireless resource in episodically dynamic environment](https://arxiv.org/abs/2011.07782)|[ICASSP2021](https://github.com/Haoran-S/ICASSP2021)| -|[lenient regret and good-action identification in gaussian process bandits](https://arxiv.org/abs/2102.05793)|[GoodAction](https://github.com/caitree/GoodAction)| +|date|paper|code| +|---|---|---| ## 2021-05-26 -|paper|code| -|---|---| -|[self-supervised transfer learning of physiological representations from free-living wearable data](https://arxiv.org/abs/2011.12121)|[Step2heart](https://github.com/sdimi/Step2heart)| -|[robust adversarial learning via sparsifying front ends](https://arxiv.org/abs/1810.10625)|[sparsity-based-defenses](https://github.com/soorya19/sparsity-based-defenses)| -|[npd entropy: a non-parametric differential entropy rate estimator](https://arxiv.org/abs/2105.11580)|[npd_entropy](https://github.com/afeutrill/npd_entropy)| -|[honest-but-curious nets: sensitive attributes of private inputs can be secretly coded into the entropy of classifiers' outputs](https://arxiv.org/abs/2105.12049)|[honest-but-curious-nets](https://github.com/mmalekzadeh/honest-but-curious-nets)| +|date|paper|code| +|---|---|---| +|2105.11580|[npd entropy: a non-parametric differential entropy rate estimator](https://arxiv.org/abs/2105.11580)|[npd_entropy](https://github.com/afeutrill/npd_entropy)| +|2105.12049|[honest-but-curious nets: sensitive attributes of private inputs can be secretly coded into the entropy of classifiers' outputs](https://arxiv.org/abs/2105.12049)|[honest-but-curious-nets](https://github.com/mmalekzadeh/honest-but-curious-nets)| ## 2021-05-25 -|paper|code| -|---|---| -|[deep joint source channel coding for wirelessimage transmission with ofdm](https://arxiv.org/abs/2101.03909)|[Deep-JSCC-for-images-with-OFDM](https://github.com/mingyuyng/Deep-JSCC-for-images-with-OFDM)| -|[joint learning of multiple granger causal networks via non-convex regularizations: inference of group-level brain connectivity](https://arxiv.org/abs/2105.07196)|[JGranger_ncvx](https://github.com/parinthorn/JGranger_ncvx)| -|[denoising noisy neural networks: a bayesian approach with compensation](https://arxiv.org/abs/2105.10699)|[NoisyNN](https://github.com/lynshao/NoisyNN)| -|[deep active learning approach to adaptive beamforming for mmwave initial alignment](https://arxiv.org/abs/2012.13607)|[DL-ActiveLearning-BeamAlignment](https://github.com/foadsohrabi/DL-ActiveLearning-BeamAlignment)| -|[byzantine-resilient federated machine learning via over-the-air computation](https://arxiv.org/abs/2105.10883)|[Byzantine_AirComp](https://github.com/goldenBill/Byzantine_AirComp)| +|date|paper|code| +|---|---|---| +|2105.07196|[joint learning of multiple granger causal networks via non-convex regularizations: inference of group-level brain connectivity](https://arxiv.org/abs/2105.07196)|[JGranger_ncvx](https://github.com/parinthorn/JGranger_ncvx)| +|2105.10699|[denoising noisy neural networks: a bayesian approach with compensation](https://arxiv.org/abs/2105.10699)|[NoisyNN](https://github.com/lynshao/NoisyNN)| +|2105.10883|[byzantine-resilient federated machine learning via over-the-air computation](https://arxiv.org/abs/2105.10883)|[Byzantine_AirComp](https://github.com/goldenBill/Byzantine_AirComp)| ## 2021-05-24 -|paper|code| -|---|---| -|[semi-supervised learning for identifying the likelihood of agitation in people with dementia](https://arxiv.org/abs/2105.10398)|[Agitation_detection](https://github.com/RoonakR/Agitation_detection)| -|[redunet: a white-box deep network from the principle of maximizing rate reduction](https://arxiv.org/abs/2105.10446)|[MCR2](https://github.com/Ma-Lab-Berkeley/MCR2)| +|date|paper|code| +|---|---|---| +|2105.10398|[semi-supervised learning for identifying the likelihood of agitation in people with dementia](https://arxiv.org/abs/2105.10398)|[Agitation_detection](https://github.com/RoonakR/Agitation_detection)| +|2105.10446|[redunet: a white-box deep network from the principle of maximizing rate reduction](https://arxiv.org/abs/2105.10446)|[MCR2](https://github.com/Ma-Lab-Berkeley/MCR2)| ## 2021-05-21 -|paper|code| -|---|---| -|[min2net: end-to-end multi-task learning for subject-independent motor imagery eeg classification](https://arxiv.org/abs/2102.03814)|[MIN2Net](https://github.com/IoBT-VISTEC/MIN2Net)| -|[point process simulation of generalised inverse gaussian processes and estimation of the jaeger integral](https://arxiv.org/abs/2105.09429)|[GiG](https://github.com/yamankindap/GiG)| +|date|paper|code| +|---|---|---| +|2105.09429|[point process simulation of generalised inverse gaussian processes and estimation of the jaeger integral](https://arxiv.org/abs/2105.09429)|[GiG](https://github.com/yamankindap/GiG)| diff --git a/archives/2021/06.md b/archives/2021/06.md index 15fba5c6..3a8f499c 100644 --- a/archives/2021/06.md +++ b/archives/2021/06.md @@ -1,180 +1,126 @@ # June 2021 Archive ## 2021-06-29 -|paper|code| -|---|---| -|[efficient sparse coding using hierarchical riemannian pursuit](https://arxiv.org/abs/2104.10314)|[HRP](https://github.com/yokoxue/HRP)| -|[accelerated alternating projections for robust principal component analysis](https://arxiv.org/abs/1711.05519)|[AccAltProj_for_RPCA](https://github.com/caesarcai/AccAltProj_for_RPCA)| -|[mode-wise tensor decompositions: multi-dimensional generalizations of cur decompositions](https://arxiv.org/abs/2103.11037)|[Modewise_Tensor_Decomp](https://github.com/caesarcai/Modewise_Tensor_Decomp)| -|[learning from an exploring demonstrator: optimal reward estimation for bandits](https://arxiv.org/abs/2106.14866)|[inverse-bandit-code-release](https://github.com/wenshuoguo/inverse-bandit-code-release)| +|date|paper|code| +|---|---|---| +|2106.14866|[learning from an exploring demonstrator: optimal reward estimation for bandits](https://arxiv.org/abs/2106.14866)|[inverse-bandit-code-release](https://github.com/wenshuoguo/inverse-bandit-code-release)| ## 2021-06-28 -|paper|code| -|---|---| -|[an inertial block majorization minimization framework for nonsmooth nonconvex optimization](https://arxiv.org/abs/2010.12133)|[TITAN](https://github.com/nhatpd/TITAN)| -|[prior image-constrained reconstruction using style-based generative models](https://arxiv.org/abs/2102.12525)|[pic-recon](https://github.com/comp-imaging-sci/pic-recon)| -|[scalable perception-action-communication loops with convolutional and graph neural networks](https://arxiv.org/abs/2106.13358)|[VGAI](https://github.com/VITA-Group/VGAI)| -|[linearly self-equivalent apn permutations in small dimension](https://arxiv.org/abs/2003.12006)|[self_equivalent_apn](https://github.com/cbe90/self_equivalent_apn)| -|[optimal sic ordering and power allocation in downlink multi-cell noma systems](https://arxiv.org/abs/2102.05015)|[Optimal-JSPA-MultiCell-NOMA](https://gitlab.com/sepehrrezvani/Optimal-JSPA-MultiCell-NOMA)| -|[fast quantum state reconstruction via accelerated non-convex programming](https://arxiv.org/abs/2104.07006)|[MiFGD](https://github.com/gidiko/MiFGD)| +|date|paper|code| +|---|---|---| +|2106.13358|[scalable perception-action-communication loops with convolutional and graph neural networks](https://arxiv.org/abs/2106.13358)|[VGAI](https://github.com/VITA-Group/VGAI)| ## 2021-06-25 -|paper|code| -|---|---| -|[universal adversarial perturbations for cnn classifiers in eeg-based bcis](https://arxiv.org/abs/1912.01171)|[UAP_EEG](https://github.com/ZihanLiu95/UAP_EEG)| -|[atlas fusion -- modern framework for autonomous agent sensor data fusion](https://arxiv.org/abs/2010.11991)|[Atlas-Fusion](https://github.com/Robotics-BUT/Atlas-Fusion)| -|[atp-net: an attention-based ternary projection network for compressed sensing](https://arxiv.org/abs/2106.12728)|[ATP-Net](https://github.com/MasonNie/ATP-Net)| -|[a declarative goal-oriented framework for smart environments with lpaas](https://arxiv.org/abs/2106.13083)|[Solomon](https://github.com/di-unipi-socc/Solomon)| -|[capacity-achieving spatially coupled sparse superposition codes with amp decoding](https://arxiv.org/abs/2002.07844)|[sparc_public](https://github.com/kuanhsieh/sparc_public)| +|date|paper|code| +|---|---|---| +|2106.12728|[atp-net: an attention-based ternary projection network for compressed sensing](https://arxiv.org/abs/2106.12728)|[ATP-Net](https://github.com/MasonNie/ATP-Net)| +|2106.13083|[a declarative goal-oriented framework for smart environments with lpaas](https://arxiv.org/abs/2106.13083)|[Solomon](https://github.com/di-unipi-socc/Solomon)| ## 2021-06-24 -|paper|code| -|---|---| -|[real-time outdoor localization using radio maps: a deep learning approach](https://arxiv.org/abs/2106.12556)|[LocUNet](https://github.com/CagkanYapar/LocUNet)| -|[robust compressed sensing using generative models](https://arxiv.org/abs/2006.09461)|[csgm-robust-neurips](https://github.com/ajiljalal/csgm-robust-neurips)| +|date|paper|code| +|---|---|---| +|2106.12556|[real-time outdoor localization using radio maps: a deep learning approach](https://arxiv.org/abs/2106.12556)|[LocUNet](https://github.com/CagkanYapar/LocUNet)| ## 2021-06-23 -|paper|code| -|---|---| -|[interpretable deep learning for the remote characterisation of ambulation in multiple sclerosis using smartphones](https://arxiv.org/abs/2103.09171)|[DBA](https://github.com/fpetitjean/DBA)| -|[extraction of instantaneous frequencies and amplitudes in nonstationary time-series data](https://arxiv.org/abs/2104.01293)|[NFMD-ExtractionInstantaneous](https://github.com/sheadan/NFMD-ExtractionInstantaneous)| -|[adversarially-trained nonnegative matrix factorization](https://arxiv.org/abs/2104.04757)|[AT_NMF](https://github.com/caiting123321/AT_NMF)| -|[transfer bayesian meta-learning via weighted free energy minimization](https://arxiv.org/abs/2106.10711)|[meta_learning_pacoh](https://github.com/jonasrothfuss/meta_learning_pacoh)| -|[transformer-based spatial-temporal feature learning for eeg decoding](https://arxiv.org/abs/2106.11170)|[EEG-Transformer](https://github.com/anranknight/EEG-Transformer)| -|[reinforcement learning for phy layer communications](https://arxiv.org/abs/2106.11595)|[malin-multi-armed-bandit-learning-for-iot-networks-with-grc](https://bitbucket.org/scee_ietr/malin-multi-armed-bandit-learning-for-iot-networks-with-grc)| -|[federated over-air subspace tracking from incomplete and corrupted data](https://arxiv.org/abs/2002.12873)|[distributed-pca](https://github.com/praneethmurthy/distributed-pca)| -|[instance-optimal compressed sensing via posterior sampling](https://arxiv.org/abs/2106.11438)|[code-cs-fairness](https://github.com/ajiljalal/code-cs-fairness)| -|[deep stereo image compression with decoder side information using wyner common information](https://arxiv.org/abs/2106.11723)|[DWSIC](https://github.com/ipc-lab/DWSIC)| +|date|paper|code| +|---|---|---| +|2106.10711|[transfer bayesian meta-learning via weighted free energy minimization](https://arxiv.org/abs/2106.10711)|[meta_learning_pacoh](https://github.com/jonasrothfuss/meta_learning_pacoh)| +|2106.11170|[transformer-based spatial-temporal feature learning for eeg decoding](https://arxiv.org/abs/2106.11170)|[EEG-Transformer](https://github.com/anranknight/EEG-Transformer)| +|2106.11595|[reinforcement learning for phy layer communications](https://arxiv.org/abs/2106.11595)|[malin-multi-armed-bandit-learning-for-iot-networks-with-grc](https://bitbucket.org/scee_ietr/malin-multi-armed-bandit-learning-for-iot-networks-with-grc)| +|2106.11438|[instance-optimal compressed sensing via posterior sampling](https://arxiv.org/abs/2106.11438)|[code-cs-fairness](https://github.com/ajiljalal/code-cs-fairness)| +|2106.11723|[deep stereo image compression with decoder side information using wyner common information](https://arxiv.org/abs/2106.11723)|[DWSIC](https://github.com/ipc-lab/DWSIC)| ## 2021-06-22 -|paper|code| -|---|---| -|[automated pipeline for eeg artifact reduction (appear) recorded during fmri](https://arxiv.org/abs/1912.05507)|[appear](https://github.com/obada-alzoubi/appear)| -|[automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors](https://arxiv.org/abs/2006.10159)|[qkeras](https://github.com/google/qkeras)| -|[real elliptically skewed distributions and their application to robust cluster analysis](https://arxiv.org/abs/2006.16671)|[Real-Elliptically-Skewed-Distributions](https://github.com/schrchr/Real-Elliptically-Skewed-Distributions)| -|[mean subtraction and mode selection in dynamic mode decomposition](https://arxiv.org/abs/2105.03607)|[msub_mdselect_dmd](https://github.com/gowtham-ss-ragavan/msub_mdselect_dmd)| +|date|paper|code| +|---|---|---| ## 2021-06-21 -|paper|code| -|---|---| -|[robustsleepnet: transfer learning for automated sleep staging at scale](https://arxiv.org/abs/2101.02452)|[RobustSleepNet](https://github.com/Dreem-Organization/RobustSleepNet)| -|[under the sand: navigation and localization of a small unmanned aerial vehicle for landmine detection with ground penetrating synthetic aperture radar](https://arxiv.org/abs/2106.10108)|[mav_findmine](https://github.com/ethz-asl/mav_findmine)| -|[vqmivc: vector quantization and mutual information-based unsupervised speech representation disentanglement for one-shot voice conversion](https://arxiv.org/abs/2106.10132)|[VQMIVC](https://github.com/Wendison/VQMIVC)| -|[probabilistic sequential shrinking: a best arm identification algorithm for stochastic bandits with corruptions](https://arxiv.org/abs/2010.07904)|[2021-ICML](https://github.com/zixinzh/2021-ICML)| +|date|paper|code| +|---|---|---| +|2106.10108|[under the sand: navigation and localization of a small unmanned aerial vehicle for landmine detection with ground penetrating synthetic aperture radar](https://arxiv.org/abs/2106.10108)|[mav_findmine](https://github.com/ethz-asl/mav_findmine)| +|2106.10132|[vqmivc: vector quantization and mutual information-based unsupervised speech representation disentanglement for one-shot voice conversion](https://arxiv.org/abs/2106.10132)|[VQMIVC](https://github.com/Wendison/VQMIVC)| ## 2021-06-18 -|paper|code| -|---|---| -|[a simulation-based end-to-end learning framework for evidential occupancy grid mapping](https://arxiv.org/abs/2102.12718)|[EviLOG](https://github.com/ika-rwth-aachen/EviLOG)| -|[a 1d-cnn based deep learning technique for sleep apnea detection in iot sensors](https://arxiv.org/abs/2105.00528)|[CNN_sleep_apnea](https://github.com/arlenejohn/CNN_sleep_apnea)| -|[minimax estimation of partially-observed vector autoregressions](https://arxiv.org/abs/2106.09327)|[PartiallyObservedVectorAutoRegressions](https://github.com/gdalle/PartiallyObservedVectorAutoRegressions)| -|[a factor graph em algorithm for inference of kinetic microstates from patch clamp measurements](https://arxiv.org/abs/2106.09594)|[PatchClampFactorGraphEM](https://github.com/andreweckford/PatchClampFactorGraphEM)| +|date|paper|code| +|---|---|---| +|2106.09327|[minimax estimation of partially-observed vector autoregressions](https://arxiv.org/abs/2106.09327)|[PartiallyObservedVectorAutoRegressions](https://github.com/gdalle/PartiallyObservedVectorAutoRegressions)| +|2106.09594|[a factor graph em algorithm for inference of kinetic microstates from patch clamp measurements](https://arxiv.org/abs/2106.09594)|[PatchClampFactorGraphEM](https://github.com/andreweckford/PatchClampFactorGraphEM)| ## 2021-06-17 -|paper|code| -|---|---| -|[multivariate public key cryptosystem from sidon spaces](https://arxiv.org/abs/2106.07785)|[Sidon-Cryptosystem](https://github.com/b-langton/Sidon-Cryptosystem)| +|date|paper|code| +|---|---|---| +|2106.07785|[multivariate public key cryptosystem from sidon spaces](https://arxiv.org/abs/2106.07785)|[Sidon-Cryptosystem](https://github.com/b-langton/Sidon-Cryptosystem)| ## 2021-06-16 -|paper|code| -|---|---| -|[how to find a unicorn: a novel model-free, unsupervised anomaly detection method for time series](https://arxiv.org/abs/2004.11468)|[uniqed](https://github.com/phrenico/uniqed)| -|[accelerating ill-conditioned low-rank matrix estimation via scaled gradient descent](https://arxiv.org/abs/2005.08898)|[ScaledGD](https://github.com/Titan-Tong/ScaledGD)| -|[speaker diarization using two-pass leave-one-out gaussian plda clustering of dnn embeddings](https://arxiv.org/abs/2104.02469)|[VBx](https://github.com/hltcoe/VBx)| -|[unique sparse decomposition of low rank matrices](https://arxiv.org/abs/2106.07736)|[Unique_Fac_of_Low_Rank](https://github.com/Jindiande/Unique_Fac_of_Low_Rank)| -|[attention-based distributed speech enhancement for unconstrained microphone arrays with varying number of nodes](https://arxiv.org/abs/2106.07939)|[disco](https://github.com/nfurnon/disco)| -|[improving lossless compression rates via monte carlo bits-back coding](https://arxiv.org/abs/2102.11086)|[mcbits](https://github.com/ryoungj/mcbits)| -|[computing accurate probabilistic estimates of one-d entropy from equiprobable random samples](https://arxiv.org/abs/2102.12675)|[Entropy](https://github.com/rehsani/Entropy)| -|[improving the list decoding version of the cyclically equivariant neural decoder](https://arxiv.org/abs/2106.07964)|[code](https://github.com/improvedlistdecoder/code)| +|date|paper|code| +|---|---|---| +|2106.07736|[unique sparse decomposition of low rank matrices](https://arxiv.org/abs/2106.07736)|[Unique_Fac_of_Low_Rank](https://github.com/Jindiande/Unique_Fac_of_Low_Rank)| +|2106.07939|[attention-based distributed speech enhancement for unconstrained microphone arrays with varying number of nodes](https://arxiv.org/abs/2106.07939)|[disco](https://github.com/nfurnon/disco)| +|2106.07964|[improving the list decoding version of the cyclically equivariant neural decoder](https://arxiv.org/abs/2106.07964)|[code](https://github.com/improvedlistdecoder/code)| ## 2021-06-15 -|paper|code| -|---|---| -|[towards fast region adaptive ultrasound beamformer for plane wave imaging using convolutional neural networks](https://arxiv.org/abs/2106.07006)|[cnnusbf](https://github.com/rpm1412/cnnusbf)| -|[wase: learning when to attend for speaker extraction in cocktail party environments](https://arxiv.org/abs/2106.07016)|[wase](https://github.com/aispeech-lab/wase)| -|[enhanced hyperspectral image super-resolution via rgb fusion and tv-tv minimization](https://arxiv.org/abs/2106.07066)|[hs-sr-tvtv](https://github.com/marijavella/hs-sr-tvtv)| -|[on continuous local bdd-based search for hybrid sat solving](https://arxiv.org/abs/2012.07983)|[GradSAT](https://github.com/vardigroup/GradSAT)| -|[decoding supercodes of gabidulin codes and applications to cryptanalysis](https://arxiv.org/abs/2103.02700)|[Attack_on_LIGA](https://github.com/mbombar/Attack_on_LIGA)| -|[on perceptual lossy compression: the cost of perceptual reconstruction and an optimal training framework](https://arxiv.org/abs/2106.02782)|[Perceptual-Lossy-Compression](https://github.com/ZeyuYan/Perceptual-Lossy-Compression)| +|date|paper|code| +|---|---|---| +|2106.07006|[towards fast region adaptive ultrasound beamformer for plane wave imaging using convolutional neural networks](https://arxiv.org/abs/2106.07006)|[cnnusbf](https://github.com/rpm1412/cnnusbf)| +|2106.07016|[wase: learning when to attend for speaker extraction in cocktail party environments](https://arxiv.org/abs/2106.07016)|[wase](https://github.com/aispeech-lab/wase)| +|2106.07066|[enhanced hyperspectral image super-resolution via rgb fusion and tv-tv minimization](https://arxiv.org/abs/2106.07066)|[hs-sr-tvtv](https://github.com/marijavella/hs-sr-tvtv)| +|2106.02782|[on perceptual lossy compression: the cost of perceptual reconstruction and an optimal training framework](https://arxiv.org/abs/2106.02782)|[Perceptual-Lossy-Compression](https://github.com/ZeyuYan/Perceptual-Lossy-Compression)| ## 2021-06-14 -|paper|code| -|---|---| -|[moreau-yosida $f$-divergences](https://arxiv.org/abs/2102.13416)|[moreau-yosida-f-divergences](https://github.com/renyi-ai/moreau-yosida-f-divergences)| -|[redunet: a white-box deep network from the principle of maximizing rate reduction](https://arxiv.org/abs/2105.10446)|[MCR2](https://github.com/Ma-Lab-Berkeley/MCR2)| +|date|paper|code| +|---|---|---| ## 2021-06-11 -|paper|code| -|---|---| -|[generating mimo channels for 6g virtual worlds using ray-tracing simulations](https://arxiv.org/abs/2106.05377)|[SSP-Raymobtime](https://github.com/lasseufpa/SSP-Raymobtime)| -|[aerial reconfigurable intelligent surface-aided wireless communication systems](https://arxiv.org/abs/2106.05380)|[Aerial-RIS](https://github.com/trinhudo/Aerial-RIS)| +|date|paper|code| +|---|---|---| +|2106.05377|[generating mimo channels for 6g virtual worlds using ray-tracing simulations](https://arxiv.org/abs/2106.05377)|[SSP-Raymobtime](https://github.com/lasseufpa/SSP-Raymobtime)| +|2106.05380|[aerial reconfigurable intelligent surface-aided wireless communication systems](https://arxiv.org/abs/2106.05380)|[Aerial-RIS](https://github.com/trinhudo/Aerial-RIS)| ## 2021-06-10 -|paper|code| -|---|---| -|[an iterative jacobi-like algorithm to compute a few sparse eigenvalue-eigenvector pairs](https://arxiv.org/abs/2105.14642)|[JACOBI-PCA](https://github.com/cristian-rusu-research/JACOBI-PCA)| -|[optimizing a binary intelligent reflecting surface for ofdm communications under mutual coupling](https://arxiv.org/abs/2106.04280)|[SP_Cup_2021](https://github.com/emilbjornson/SP_Cup_2021)| -|[time-frequency phase retrieval for audio -- the effect of transform parameters](https://arxiv.org/abs/2106.05148)|[phaseRetrievalEvaluation](https://github.com/andimarafioti/phaseRetrievalEvaluation)| -|[unsupervised discovery of temporal structure in noisy data with dynamical components analysis](https://arxiv.org/abs/1905.09944)|[DynamicalComponentsAnalysis](https://github.com/BouchardLab/DynamicalComponentsAnalysis)| +|date|paper|code| +|---|---|---| +|2106.04280|[optimizing a binary intelligent reflecting surface for ofdm communications under mutual coupling](https://arxiv.org/abs/2106.04280)|[SP_Cup_2021](https://github.com/emilbjornson/SP_Cup_2021)| +|2106.05148|[time-frequency phase retrieval for audio -- the effect of transform parameters](https://arxiv.org/abs/2106.05148)|[phaseRetrievalEvaluation](https://github.com/andimarafioti/phaseRetrievalEvaluation)| ## 2021-06-09 -|paper|code| -|---|---| -|[proactive and aoi-aware failure recovery for stateful nfv-enabled zero-touch 6g networks: model-free drl approach](https://arxiv.org/abs/2103.03817)|[ZT-PFR](https://github.com/wildsky95/ZT-PFR)| -|[dilated convolution based csi feedback compression for massive mimo systems](https://arxiv.org/abs/2106.04043)|[DCRNet](https://github.com/recusant7/DCRNet)| -|[deepbeam: deep waveform learning for coordination-free beam management in mmwave networks](https://arxiv.org/abs/2012.14350)|[deepbeam](https://github.com/wineslab/deepbeam)| -|[principal bit analysis: autoencoding with schur-concave loss](https://arxiv.org/abs/2106.02796)|[PBA](https://github.com/SourbhBh/PBA)| -|[robust generalization despite distribution shift via minimum discriminating information](https://arxiv.org/abs/2106.04443)|[PMDI_DRO](https://github.com/pmdidro/PMDI_DRO)| +|date|paper|code| +|---|---|---| +|2106.04043|[dilated convolution based csi feedback compression for massive mimo systems](https://arxiv.org/abs/2106.04043)|[DCRNet](https://github.com/recusant7/DCRNet)| +|2106.02796|[principal bit analysis: autoencoding with schur-concave loss](https://arxiv.org/abs/2106.02796)|[PBA](https://github.com/SourbhBh/PBA)| +|2106.04443|[robust generalization despite distribution shift via minimum discriminating information](https://arxiv.org/abs/2106.04443)|[PMDI_DRO](https://github.com/pmdidro/PMDI_DRO)| ## 2021-06-08 -|paper|code| -|---|---| -|[optimal network slicing for service-oriented networks with flexible routing and guaranteed e2e latency](https://arxiv.org/abs/2006.13019)|[networkslicing](https://github.com/chenweikun/networkslicing)| -|[multi-modal point-of-care diagnostics for covid-19 based on acoustics and symptoms](https://arxiv.org/abs/2106.00639)|[MuDiCov](https://github.com/iiscleap/MuDiCov)| -|[configuring an intelligent reflecting surface for wireless communications](https://arxiv.org/abs/2106.03497)|[SP_Cup_2021](https://github.com/emilbjornson/SP_Cup_2021)| -|[energy and age pareto optimal trajectories in uav-assisted wireless data collection](https://arxiv.org/abs/2106.03822)|[BDforUavPath](https://github.com/Yuanliaoo/BDforUavPath)| -|[on perceptual lossy compression: the cost of perceptual reconstruction and an optimal training framework](https://arxiv.org/abs/2106.02782)|[Perceptual-Lossy-Compression](https://github.com/ZeyuYan/Perceptual-Lossy-Compression)| +|date|paper|code| +|---|---|---| +|2106.00639|[multi-modal point-of-care diagnostics for covid-19 based on acoustics and symptoms](https://arxiv.org/abs/2106.00639)|[MuDiCov](https://github.com/iiscleap/MuDiCov)| +|2106.03497|[configuring an intelligent reflecting surface for wireless communications](https://arxiv.org/abs/2106.03497)|[SP_Cup_2021](https://github.com/emilbjornson/SP_Cup_2021)| +|2106.03822|[energy and age pareto optimal trajectories in uav-assisted wireless data collection](https://arxiv.org/abs/2106.03822)|[BDforUavPath](https://github.com/Yuanliaoo/BDforUavPath)| +|2106.02782|[on perceptual lossy compression: the cost of perceptual reconstruction and an optimal training framework](https://arxiv.org/abs/2106.02782)|[Perceptual-Lossy-Compression](https://github.com/ZeyuYan/Perceptual-Lossy-Compression)| ## 2021-06-07 -|paper|code| -|---|---| -|[cold: concurrent loads disaggregator for non-intrusive load monitoring](https://arxiv.org/abs/2106.02352)|[cold-nilm](https://github.com/arx7ti/cold-nilm)| -|[homological time series analysis of sensor signals from power plants](https://arxiv.org/abs/2106.02493)|[TwirlFlake](https://github.com/karhunenloeve/TwirlFlake)| -|[the signed cumulative distribution transform for 1-d signal analysis and classification](https://arxiv.org/abs/2106.02146)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| +|date|paper|code| +|---|---|---| +|2106.02352|[cold: concurrent loads disaggregator for non-intrusive load monitoring](https://arxiv.org/abs/2106.02352)|[cold-nilm](https://github.com/arx7ti/cold-nilm)| +|2106.02493|[homological time series analysis of sensor signals from power plants](https://arxiv.org/abs/2106.02493)|[TwirlFlake](https://github.com/karhunenloeve/TwirlFlake)| +|2106.02146|[the signed cumulative distribution transform for 1-d signal analysis and classification](https://arxiv.org/abs/2106.02146)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| ## 2021-06-04 -|paper|code| -|---|---| -|[channel estimation for one-bit multiuser massive mimo using conditional gan](https://arxiv.org/abs/2006.11435)|[Channel_Estimation_cGAN](https://github.com/YudiDong/Channel_Estimation_cGAN)| -|[gender bias in depression detection using audio features](https://arxiv.org/abs/2010.15120)|[DepAudioNet_reproduction](https://github.com/adbailey1/DepAudioNet_reproduction)| -|[heppcat: probabilistic pca for data with heteroscedastic noise](https://arxiv.org/abs/2101.03468)|[heteroscedastic-probabilistic-pca](https://gitlab.com/dahong/heteroscedastic-probabilistic-pca)| -|[sparse kronecker-product coding for unsourced multiple access](https://arxiv.org/abs/2103.04722)|[SKPC-UMA](https://github.com/Zeyu-Han01/SKPC-UMA)| -|[multi-uav path planning for wireless data harvesting with deep reinforcement learning](https://arxiv.org/abs/2010.12461)|[uav_data_harvesting](https://github.com/hbayerlein/uav_data_harvesting)| +|date|paper|code| +|---|---|---| ## 2021-06-03 -|paper|code| -|---|---| -|[adaptive self-interference cancellation for full-duplex wireless communication systems](https://arxiv.org/abs/2104.01504)|[Full-Duplex-Steepest-Descent](https://github.com/ebalti/Full-Duplex-Steepest-Descent)| -|[self-training sampling with monolingual data uncertainty for neural machine translation](https://arxiv.org/abs/2106.00941)|[UncSamp](https://github.com/wxjiao/UncSamp)| +|date|paper|code| +|---|---|---| +|2106.00941|[self-training sampling with monolingual data uncertainty for neural machine translation](https://arxiv.org/abs/2106.00941)|[UncSamp](https://github.com/wxjiao/UncSamp)| ## 2021-06-02 -|paper|code| -|---|---| -|[reconfigurable intelligent surface enabled federated learning: a unified communication-learning design approach](https://arxiv.org/abs/2011.10282)|[RIS-FL](https://github.com/liuhang1994/RIS-FL)| -|[a mixed integer least-squares formulation of the gnss snapshot positioning problem](https://arxiv.org/abs/2101.00895)|[snapshot-positioning](https://github.com/eyalw711/snapshot-positioning)| -|[dynamic-deep: ecg task-aware compression](https://arxiv.org/abs/2106.00606)|[Dynamic-Deep](https://github.com/eladwass/Dynamic-Deep)| -|[a compact and interpretable convolutional neural network for cross-subject driver drowsiness detection from single-channel eeg](https://arxiv.org/abs/2106.00613)|[A-Compact-and-Interpretable-Convolutional-Neural-Network-for-Single-Channel-EEG](https://github.com/cuijiancorbin/A-Compact-and-Interpretable-Convolutional-Neural-Network-for-Single-Channel-EEG)| -|[meta-har: federated representation learning for human activity recognition](https://arxiv.org/abs/2106.00615)|[Meta-HAR](https://github.com/Chain123/Meta-HAR)| +|date|paper|code| +|---|---|---| +|2106.00606|[dynamic-deep: ecg task-aware compression](https://arxiv.org/abs/2106.00606)|[Dynamic-Deep](https://github.com/eladwass/Dynamic-Deep)| +|2106.00613|[a compact and interpretable convolutional neural network for cross-subject driver drowsiness detection from single-channel eeg](https://arxiv.org/abs/2106.00613)|[A-Compact-and-Interpretable-Convolutional-Neural-Network-for-Single-Channel-EEG](https://github.com/cuijiancorbin/A-Compact-and-Interpretable-Convolutional-Neural-Network-for-Single-Channel-EEG)| +|2106.00615|[meta-har: federated representation learning for human activity recognition](https://arxiv.org/abs/2106.00615)|[Meta-HAR](https://github.com/Chain123/Meta-HAR)| ## 2021-06-01 -|paper|code| -|---|---| -|[an efficient and effective second-order training algorithm for lstm-based adaptive learning](https://arxiv.org/abs/1910.09857)|[EfficientEffectiveLSTM](https://github.com/nurimertvural/EfficientEffectiveLSTM)| -|[block deep neural network-based signal detector for generalized spatial modulation](https://arxiv.org/abs/2008.03612)|[B_DNN](https://github.com/hasanabs/B_DNN)| -|[support recovery for sparse multidimensional phase retrieval](https://arxiv.org/abs/2011.00619)|[Sparse-Multidimensional-PR](https://github.com/sew347/Sparse-Multidimensional-PR)| -|[overcoming measurement inconsistency in deep learning for linear inverse problems: applications in medical imaging](https://arxiv.org/abs/2011.14387)|[mri-tvtv](https://github.com/marijavella/mri-tvtv)| -|[interval propagation through the discrete fourier transform](https://arxiv.org/abs/2012.09778)|[Fourier-transform](https://github.com/marcodeangelis/Fourier-transform)| -|[clnet: complex input lightweight neural network designed for massive mimo csi feedback](https://arxiv.org/abs/2102.07507)|[CLNet](https://github.com/SIJIEJI/CLNet)| -|[an iterative jacobi-like algorithm to compute a few sparse eigenvalue-eigenvector pairs](https://arxiv.org/abs/2105.14642)|[JACOBI-PCA](https://github.com/cristian-rusu-research/JACOBI-PCA)| -|[an automated theorem proving framework for information-theoretic results](https://arxiv.org/abs/2101.12370)|[psitip](https://github.com/cheuktingli/psitip)| +|date|paper|code| +|---|---|---| diff --git a/archives/2021/07.md b/archives/2021/07.md index 3ad0e120..31170c76 100644 --- a/archives/2021/07.md +++ b/archives/2021/07.md @@ -1,134 +1,97 @@ # July 2021 Archive ## 2021-07-29 -|paper|code| -|---|---| -|[eegdenoisenet: a benchmark dataset for end-to-end deep learning solutions of eeg denoising](https://arxiv.org/abs/2009.11662)|[Single-Channel-EEG-Denoise](https://github.com/ncclabsustech/Single-Channel-EEG-Denoise)| -|[on optimal quantization in sequential detection](https://arxiv.org/abs/2107.13412)|[QSPRT](https://github.com/mifauss/QSPRT)| +|date|paper|code| +|---|---|---| +|2107.13412|[on optimal quantization in sequential detection](https://arxiv.org/abs/2107.13412)|[QSPRT](https://github.com/mifauss/QSPRT)| ## 2021-07-28 -|paper|code| -|---|---| -|[edgenets:edge varying graph neural networks](https://arxiv.org/abs/2001.07620)|[graph-neural-networks](https://github.com/alelab-upenn/graph-neural-networks)| -|[neural waveshaping synthesis](https://arxiv.org/abs/2107.05050)|[neural-waveshaping-synthesis](https://github.com/ben-hayes/neural-waveshaping-synthesis)| -|[information flows of diverse autoencoders](https://arxiv.org/abs/2102.07402)|[IPRL](https://github.com/Sungyeop/IPRL)| -|[straggler mitigation through unequal error protection for distributed approximate matrix multiplication](https://arxiv.org/abs/2103.02928)|[UEP-Straggler-Mitigation](https://github.com/HernandezEduin/UEP-Straggler-Mitigation)| +|date|paper|code| +|---|---|---| +|2107.05050|[neural waveshaping synthesis](https://arxiv.org/abs/2107.05050)|[neural-waveshaping-synthesis](https://github.com/ben-hayes/neural-waveshaping-synthesis)| ## 2021-07-27 -|paper|code| -|---|---| -|[adaptive social learning](https://arxiv.org/abs/2004.02494)|[asl-it-2021](https://github.com/asl-epfl/asl-it-2021)| -|[a mixed integer least-squares formulation of the gnss snapshot positioning problem](https://arxiv.org/abs/2101.00895)|[snapshot-positioning](https://github.com/eyalw711/snapshot-positioning)| -|[federated mmwave beam selection utilizing lidar data](https://arxiv.org/abs/2102.02802)|[ITU_Beam_Selection_TF](https://github.com/galidor/ITU_Beam_Selection_TF)| -|[reconfigurable intelligent surface phase hopping for ultra-reliable communications](https://arxiv.org/abs/2107.11852)|[ris-phase-hopping](https://gitlab.com/klb2/ris-phase-hopping)| -|[fermi: fair empirical risk minimization via exponential r\'enyi mutual information](https://arxiv.org/abs/2102.12586)|[FERMI](https://github.com/optimization-for-data-driven-science/FERMI)| +|date|paper|code| +|---|---|---| +|2107.11852|[reconfigurable intelligent surface phase hopping for ultra-reliable communications](https://arxiv.org/abs/2107.11852)|[ris-phase-hopping](https://gitlab.com/klb2/ris-phase-hopping)| ## 2021-07-23 -|paper|code| -|---|---| -|[high-dimensional fast convolutional framework (hicu) for calibrationless mri](https://arxiv.org/abs/2004.08962)|[HICU](https://github.com/OSU-CMR/HICU)| -|[a multispeaker dataset of raw and reconstructed speech production real-time mri video and 3d volumetric images](https://arxiv.org/abs/2102.07896)|[usc_speech_mri](https://github.com/usc-mrel/usc_speech_mri)| -|[interpretable sincnet-based deep learning for emotion recognition from eeg brain activity](https://arxiv.org/abs/2107.10790)|[SincNet-for-Autism-EEG-based-Emotion-Recognition](https://github.com/meiyor/SincNet-for-Autism-EEG-based-Emotion-Recognition)| +|date|paper|code| +|---|---|---| +|2107.10790|[interpretable sincnet-based deep learning for emotion recognition from eeg brain activity](https://arxiv.org/abs/2107.10790)|[SincNet-for-Autism-EEG-based-Emotion-Recognition](https://github.com/meiyor/SincNet-for-Autism-EEG-based-Emotion-Recognition)| ## 2021-07-22 -|paper|code| -|---|---| -|[vqmivc: vector quantization and mutual information-based unsupervised speech representation disentanglement for one-shot voice conversion](https://arxiv.org/abs/2106.10132)|[VQMIVC](https://github.com/Wendison/VQMIVC)| -|[regularized classification-aware quantization](https://arxiv.org/abs/2107.09716)|[rcaq](https://github.com/dsevero/rcaq)| -|[ecg heartbeat classification using multimodal fusion](https://arxiv.org/abs/2107.09869)|[ECG-Heartbeat-Classification-Using-Multimodal-Fusion](https://github.com/zaamad/ECG-Heartbeat-Classification-Using-Multimodal-Fusion)| +|date|paper|code| +|---|---|---| +|2107.09716|[regularized classification-aware quantization](https://arxiv.org/abs/2107.09716)|[rcaq](https://github.com/dsevero/rcaq)| +|2107.09869|[ecg heartbeat classification using multimodal fusion](https://arxiv.org/abs/2107.09869)|[ECG-Heartbeat-Classification-Using-Multimodal-Fusion](https://github.com/zaamad/ECG-Heartbeat-Classification-Using-Multimodal-Fusion)| ## 2021-07-21 -|paper|code| -|---|---| -|[change point detection in time series data using autoencoders with a time-invariant representation](https://arxiv.org/abs/2008.09524)|[TIRE](https://github.com/deryckt/TIRE)| -|[deep low-rank plus sparse network for dynamic mr imaging](https://arxiv.org/abs/2010.13677)|[LS-Net-Dynamic-MRI](https://github.com/wenqihuang/LS-Net-Dynamic-MRI)| -|[deep learning assisted calibrated beam training for millimeter-wave communication systems](https://arxiv.org/abs/2101.05206)|[DL-assisted-calibrated-beam-training](https://github.com/KeMa1998/DL-assisted-calibrated-beam-training)| -|[directional sparse filtering using weighted lehmer mean for blind separation of unbalanced speech mixtures](https://arxiv.org/abs/2102.00196)|[directional-sparse-filtering-tf](https://github.com/karnwatcharasupat/directional-sparse-filtering-tf)| -|[energy disaggregation using variational autoencoders](https://arxiv.org/abs/2103.12177)|[VAE-NILM](https://github.com/ETSSmartRes/VAE-NILM)| -|[efficient sparse coding using hierarchical riemannian pursuit](https://arxiv.org/abs/2104.10314)|[HRP](https://github.com/yokoxue/HRP)| -|[one billion audio sounds from gpu-enabled modular synthesis](https://arxiv.org/abs/2104.12922)|[torchsynth](https://github.com/torchsynth/torchsynth)| -|[compressing multisets with large alphabets](https://arxiv.org/abs/2107.09202)|[multiset-compression](https://github.com/facebookresearch/multiset-compression)| +|date|paper|code| +|---|---|---| +|2107.09202|[compressing multisets with large alphabets](https://arxiv.org/abs/2107.09202)|[multiset-compression](https://github.com/facebookresearch/multiset-compression)| ## 2021-07-19 -|paper|code| -|---|---| -|[kernel learning for high-resolution time-frequency distribution](https://arxiv.org/abs/2007.00322)|[KL-TFD](https://github.com/teki97/KL-TFD)| -|[depth estimation from monocular images and sparse radar using deep ordinal regression network](https://arxiv.org/abs/2107.07596)|[DORN_radar](https://github.com/lochenchou/DORN_radar)| -|[learning optimal representations with the decodable information bottleneck](https://arxiv.org/abs/2009.12789)|[Mini_Decodable_Information_Bottleneck](https://github.com/YannDubs/Mini_Decodable_Information_Bottleneck)| -|[information flows of diverse autoencoders](https://arxiv.org/abs/2102.07402)|[IPRL](https://github.com/Sungyeop/IPRL)| +|date|paper|code| +|---|---|---| +|2107.07596|[depth estimation from monocular images and sparse radar using deep ordinal regression network](https://arxiv.org/abs/2107.07596)|[DORN_radar](https://github.com/lochenchou/DORN_radar)| ## 2021-07-16 -|paper|code| -|---|---| -|[visualization of linear operations in the spherical harmonics domain](https://arxiv.org/abs/2104.13069)|[visualization-of-sh-domain-operations](https://github.com/kentgens/visualization-of-sh-domain-operations)| -|[a low-complexity radar detector outperforming os-cfar for indoor drone obstacle avoidance](https://arxiv.org/abs/2107.07250)|[RadarDetector](https://github.com/ali20480/RadarDetector)| +|date|paper|code| +|---|---|---| +|2107.07250|[a low-complexity radar detector outperforming os-cfar for indoor drone obstacle avoidance](https://arxiv.org/abs/2107.07250)|[RadarDetector](https://github.com/ali20480/RadarDetector)| ## 2021-07-15 -|paper|code| -|---|---| -|[optimal power allocation in downlink noma](https://arxiv.org/abs/2107.06678)|[optimal-power-allocation-in-downlink-noma.-sum-rate-and-energy-efficiency-maximization](https://gitlab.com/sepehrrezvani/optimal-power-allocation-in-downlink-noma.-sum-rate-and-energy-efficiency-maximization)| -|[trellis bma: coded trace reconstruction on ids channels for dna storage](https://arxiv.org/abs/2107.06440)|[clustered-nanopore-reads-dataset](https://github.com/microsoft/clustered-nanopore-reads-dataset)| +|date|paper|code| +|---|---|---| +|2107.06678|[optimal power allocation in downlink noma](https://arxiv.org/abs/2107.06678)|[optimal-power-allocation-in-downlink-noma.-sum-rate-and-energy-efficiency-maximization](https://gitlab.com/sepehrrezvani/optimal-power-allocation-in-downlink-noma.-sum-rate-and-energy-efficiency-maximization)| +|2107.06440|[trellis bma: coded trace reconstruction on ids channels for dna storage](https://arxiv.org/abs/2107.06440)|[clustered-nanopore-reads-dataset](https://github.com/microsoft/clustered-nanopore-reads-dataset)| ## 2021-07-14 -|paper|code| -|---|---| -|[low rate protograph-based ldpc codes for continuous variable quantum key distribution](https://arxiv.org/abs/2107.06242)|[Protograph_Optimization](https://github.com/kadirgumus/Protograph_Optimization)| +|date|paper|code| +|---|---|---| +|2107.06242|[low rate protograph-based ldpc codes for continuous variable quantum key distribution](https://arxiv.org/abs/2107.06242)|[Protograph_Optimization](https://github.com/kadirgumus/Protograph_Optimization)| ## 2021-07-13 -|paper|code| -|---|---| -|[a deep-bayesian framework for adaptive speech duration modification](https://arxiv.org/abs/2107.04973)|[pytorch-speech-transformer](https://github.com/ravi-0841/pytorch-speech-transformer)| -|[neural waveshaping synthesis](https://arxiv.org/abs/2107.05050)|[neural-waveshaping-synthesis](https://github.com/ben-hayes/neural-waveshaping-synthesis)| -|[dihedral multi-reference alignment](https://arxiv.org/abs/2107.05262)|[DihedralMRA](https://github.com/nirsharon/DihedralMRA)| -|[on fading channel dependency structures with a positive zero-outage capacity](https://arxiv.org/abs/2102.02541)|[zero-outage-joint-distributions](https://gitlab.com/klb2/zero-outage-joint-distributions)| +|date|paper|code| +|---|---|---| +|2107.04973|[a deep-bayesian framework for adaptive speech duration modification](https://arxiv.org/abs/2107.04973)|[pytorch-speech-transformer](https://github.com/ravi-0841/pytorch-speech-transformer)| +|2107.05050|[neural waveshaping synthesis](https://arxiv.org/abs/2107.05050)|[neural-waveshaping-synthesis](https://github.com/ben-hayes/neural-waveshaping-synthesis)| +|2107.05262|[dihedral multi-reference alignment](https://arxiv.org/abs/2107.05262)|[DihedralMRA](https://github.com/nirsharon/DihedralMRA)| ## 2021-07-12 -|paper|code| -|---|---| -|[interpretable classification of bacterial raman spectra with knockoff wavelets](https://arxiv.org/abs/2006.04937)|[raman-knockoffs](https://github.com/chicanagram/raman-knockoffs)| -|[easycom: an augmented reality dataset to support algorithms for easy communication in noisy environments](https://arxiv.org/abs/2107.04174)|[EasyComDataset](https://github.com/facebookresearch/EasyComDataset)| -|[block alternating bregman majorization minimization with extrapolation](https://arxiv.org/abs/2107.04395)|[BMME](https://github.com/LeThiKhanhHien/BMME)| -|[multiple testing and variable selection along least angle regression's path](https://arxiv.org/abs/1906.12072)|[lar_testing](https://github.com/ydecastro/lar_testing)| +|date|paper|code| +|---|---|---| +|2107.04174|[easycom: an augmented reality dataset to support algorithms for easy communication in noisy environments](https://arxiv.org/abs/2107.04174)|[EasyComDataset](https://github.com/facebookresearch/EasyComDataset)| +|2107.04395|[block alternating bregman majorization minimization with extrapolation](https://arxiv.org/abs/2107.04395)|[BMME](https://github.com/LeThiKhanhHien/BMME)| ## 2021-07-09 -|paper|code| -|---|---| -|[diagnosis of intelligent reflecting surface in millimeter-wave communication systems](https://arxiv.org/abs/2101.03792)|[IRSdiagnosis](https://github.com/DestinationSR/IRSdiagnosis)| -|[iowarain: a statewide rain event dataset based on weather radars and quantitative precipitation estimation](https://arxiv.org/abs/2107.03432)|[IowaRain](https://github.com/uihilab/IowaRain)| +|date|paper|code| +|---|---|---| +|2107.03432|[iowarain: a statewide rain event dataset based on weather radars and quantitative precipitation estimation](https://arxiv.org/abs/2107.03432)|[IowaRain](https://github.com/uihilab/IowaRain)| ## 2021-07-08 -|paper|code| -|---|---| -|[lossy compression for lossless prediction](https://arxiv.org/abs/2106.10800)|[lossyless](https://github.com/YannDubs/lossyless)| +|date|paper|code| +|---|---|---| ## 2021-07-07 -|paper|code| -|---|---| -|[discrete signal processing on meet/join lattices](https://arxiv.org/abs/2012.04358)|[lattice-signal-processing](https://github.com/bseifert-HSA/lattice-signal-processing)| -|[rodnet: a real-time radar object detection network cross-supervised by camera-radar fused object 3d localization](https://arxiv.org/abs/2102.05150)|[RODNet](https://github.com/yizhou-wang/RODNet)| -|[learning semantic segmentation of large-scale point clouds with random sampling](https://arxiv.org/abs/2107.02389)|[RandLA-Net](https://github.com/QingyongHu/RandLA-Net)| -|[bayesian algorithm execution: estimating computable properties of black-box functions using mutual information](https://arxiv.org/abs/2104.09460)|[bayesian-algorithm-execution](https://github.com/willieneis/bayesian-algorithm-execution)| +|date|paper|code| +|---|---|---| +|2107.02389|[learning semantic segmentation of large-scale point clouds with random sampling](https://arxiv.org/abs/2107.02389)|[RandLA-Net](https://github.com/QingyongHu/RandLA-Net)| ## 2021-07-06 -|paper|code| -|---|---| -|[efficient sparse coding using hierarchical riemannian pursuit](https://arxiv.org/abs/2104.10314)|[HRP](https://github.com/yokoxue/HRP)| -|[packing: towards 2x nlp bert acceleration](https://arxiv.org/abs/2107.02027)|[packedBERT](https://github.com/graphcore/tutorials/tree/sdk-release-2.1/blogs_code/packedBERT)| +|date|paper|code| +|---|---|---| +|2107.02027|[packing: towards 2x nlp bert acceleration](https://arxiv.org/abs/2107.02027)|[packedBERT](https://github.com/graphcore/tutorials/tree/sdk-release-2.1/blogs_code/packedBERT)| ## 2021-07-05 -|paper|code| -|---|---| -|[real elliptically skewed distributions and their application to robust cluster analysis](https://arxiv.org/abs/2006.16671)|[Real-Elliptically-Skewed-Distributions](https://github.com/schrchr/Real-Elliptically-Skewed-Distributions)| -|[joint analog beam selection and digital beamforming in millimeter wave cell-free massive mimo systems](https://arxiv.org/abs/2103.11199)|[JointDesigninmmWaveCellFreeNetworks](https://github.com/DrCMY/JointDesigninmmWaveCellFreeNetworks)| -|[inter-beat interval estimation with tiramisu model: a novel approach with reduced error](https://arxiv.org/abs/2107.00693)|[IBI_Tiramisu](https://github.com/Arefeen06088/IBI_Tiramisu)| -|[tight mutual information estimation with contrastive fenchel-legendre optimization](https://arxiv.org/abs/2107.01131)|[FLO](https://github.com/qingguo666/FLO)| -|[simpler, faster, stronger: breaking the log-k curse on contrastive learners with flatnce](https://arxiv.org/abs/2107.01152)|[FlatCLR](https://github.com/Junya-Chen/FlatCLR)| +|date|paper|code| +|---|---|---| +|2107.00693|[inter-beat interval estimation with tiramisu model: a novel approach with reduced error](https://arxiv.org/abs/2107.00693)|[IBI_Tiramisu](https://github.com/Arefeen06088/IBI_Tiramisu)| +|2107.01131|[tight mutual information estimation with contrastive fenchel-legendre optimization](https://arxiv.org/abs/2107.01131)|[FLO](https://github.com/qingguo666/FLO)| +|2107.01152|[simpler, faster, stronger: breaking the log-k curse on contrastive learners with flatnce](https://arxiv.org/abs/2107.01152)|[FlatCLR](https://github.com/Junya-Chen/FlatCLR)| ## 2021-07-02 -|paper|code| -|---|---| -|[automated pipeline for eeg artifact reduction (appear) recorded during fmri](https://arxiv.org/abs/1912.05507)|[appear](https://github.com/obada-alzoubi/appear)| -|[a sketching framework for reduced data transfer in photon counting lidar](https://arxiv.org/abs/2102.08732)|[sketched_lidar](https://gitlab.com/Tachella/sketched_lidar)| -|[conditional independence for pretext task selection in self-supervised speech representation learning](https://arxiv.org/abs/2104.07388)|[Pseudo-Label-Selection](https://github.com/salah-zaiem/Pseudo-Label-Selection)| -|[reinforcement learning for physical layer communications](https://arxiv.org/abs/2106.11595)|[malin-multi-armed-bandit-learning-for-iot-networks-with-grc](https://bitbucket.org/scee_ietr/malin-multi-armed-bandit-learning-for-iot-networks-with-grc)| +|date|paper|code| +|---|---|---| diff --git a/archives/2021/08.md b/archives/2021/08.md index 087d0650..b971ecd9 100644 --- a/archives/2021/08.md +++ b/archives/2021/08.md @@ -1,145 +1,112 @@ # August 2021 Archive ## 2021-08-31 -|paper|code| -|---|---| -|[signal2image modules in deep neural networks for eeg classification](https://arxiv.org/abs/1904.13216)|[signal2image-modules-in-deep-neural-networks-for-eeg-classification](https://github.com/pbizopoulos/signal2image-modules-in-deep-neural-networks-for-eeg-classification)| -|[high fidelity deep learning-based mri reconstruction with instance-wise discriminative feature matching loss](https://arxiv.org/abs/2108.12460)|[ufloss](https://github.com/mikgroup/ufloss)| -|[iterative error decimation for syndrome-based neural network decoders](https://arxiv.org/abs/2012.00089)|[ied](https://github.com/kamassury/ied)| -|[towards optimally efficient search with deep learning for large-scale mimo systems](https://arxiv.org/abs/2101.02420)|[hats](https://github.com/skypitcher/hats)| -|[arbitrary-length analogs to de bruijn sequences](https://arxiv.org/abs/2108.07759)|[pkl](https://github.com/nelloreward/pkl)| -|[ko codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning](https://arxiv.org/abs/2108.12920)|[kocodes](https://github.com/deepcomm/kocodes)| +|date|paper|code| +|---|---|---| +|2108.12460|[high fidelity deep learning-based mri reconstruction with instance-wise discriminative feature matching loss](https://arxiv.org/abs/2108.12460)|[ufloss](https://github.com/mikgroup/ufloss)| +|2108.07759|[arbitrary-length analogs to de bruijn sequences](https://arxiv.org/abs/2108.07759)|[pkl](https://github.com/nelloreward/pkl)| +|2108.12920|[ko codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning](https://arxiv.org/abs/2108.12920)|[kocodes](https://github.com/deepcomm/kocodes)| ## 2021-08-30 -|paper|code| -|---|---| -|[multiple hypothesis testing framework for spatial signals](https://arxiv.org/abs/2108.12314)|[lfdr-smom](https://github.com/mgoelz95/lfdr-smom)| +|date|paper|code| +|---|---|---| +|2108.12314|[multiple hypothesis testing framework for spatial signals](https://arxiv.org/abs/2108.12314)|[lfdr-smom](https://github.com/mgoelz95/lfdr-smom)| ## 2021-08-26 -|paper|code| -|---|---| -|[bayesian context trees: modelling and exact inference for discrete time series](https://arxiv.org/abs/2007.14900)|[Bayesian-Suffix-Trees](https://github.com/IoannisPapageorgiou/Bayesian-Suffix-Trees)| +|date|paper|code| +|---|---|---| ## 2021-08-25 -|paper|code| -|---|---| -|[equivariant imaging: learning beyond the range space](https://arxiv.org/abs/2103.14756)|[EI](https://github.com/edongdongchen/EI)| -|[learning sparse analytic filters for piano transcription](https://arxiv.org/abs/2108.10382)|[sparse-analytic-filters](https://github.com/cwitkowitz/sparse-analytic-filters)| +|date|paper|code| +|---|---|---| +|2108.10382|[learning sparse analytic filters for piano transcription](https://arxiv.org/abs/2108.10382)|[sparse-analytic-filters](https://github.com/cwitkowitz/sparse-analytic-filters)| ## 2021-08-24 -|paper|code| -|---|---| -|[a spiking neural network (snn) for detecting high frequency oscillations (hfos) in the intraoperative ecog](https://arxiv.org/abs/2011.08783)|[SNN_HFO_ECoG](https://github.com/kburel/SNN_HFO_ECoG)| -|[salience: an unsupervised user adaptation model for multiple wearable sensors based human activity recognition](https://arxiv.org/abs/2108.10213)|[SALIENCE](https://github.com/wdkhuans/SALIENCE)| -|[exclusive group lasso for structured variable selection](https://arxiv.org/abs/2108.10284)|[exclusive-lasso](https://github.com/gregdvd/exclusive-lasso)| -|[iterative error decimation for syndrome-based neural network decoders](https://arxiv.org/abs/2012.00089)|[ied](https://github.com/kamassury/ied)| -|[honest-but-curious nets: sensitive attributes of private inputs can be secretly coded into the classifiers' outputs](https://arxiv.org/abs/2105.12049)|[honest-but-curious-nets](https://github.com/mmalekzadeh/honest-but-curious-nets)| +|date|paper|code| +|---|---|---| +|2108.10213|[salience: an unsupervised user adaptation model for multiple wearable sensors based human activity recognition](https://arxiv.org/abs/2108.10213)|[SALIENCE](https://github.com/wdkhuans/SALIENCE)| +|2108.10284|[exclusive group lasso for structured variable selection](https://arxiv.org/abs/2108.10284)|[exclusive-lasso](https://github.com/gregdvd/exclusive-lasso)| ## 2021-08-21 -|paper|code| -|---|---| -|[statistical inference in the differential privacy model](https://arxiv.org/abs/2108.05000)|[INSPECTRE](https://github.com/HuanyuZhang/INSPECTRE)| +|date|paper|code| +|---|---|---| +|2108.05000|[statistical inference in the differential privacy model](https://arxiv.org/abs/2108.05000)|[INSPECTRE](https://github.com/HuanyuZhang/INSPECTRE)| ## 2021-08-20 -|paper|code| -|---|---| -|[chmusic: a traditional chinese music dataset for evaluation of instrument recognition](https://arxiv.org/abs/2108.08470)|[chmusic](https://github.com/haoranweiutd/chmusic)| -|[synthesis of logical clifford operators via symplectic geometry](https://arxiv.org/abs/1803.06987)|[symplectic-arxiv18a](https://github.com/nrenga/symplectic-arxiv18a)| -|[kerdock codes determine unitary 2-designs](https://arxiv.org/abs/1904.07842)|[symplectic-arxiv18a](https://github.com/nrenga/symplectic-arxiv18a)| -|[logical clifford synthesis for stabilizer codes](https://arxiv.org/abs/1907.00310)|[symplectic-arxiv18a](https://github.com/nrenga/symplectic-arxiv18a)| -|[belief propagation with quantum messages for quantum-enhanced classical communications](https://arxiv.org/abs/2003.04356)|[bpqm](https://github.com/nrenga/bpqm)| +|date|paper|code| +|---|---|---| +|2108.08470|[chmusic: a traditional chinese music dataset for evaluation of instrument recognition](https://arxiv.org/abs/2108.08470)|[chmusic](https://github.com/haoranweiutd/chmusic)| ## 2021-08-19 -|paper|code| -|---|---| -|[signal2image modules in deep neural networks for eeg classification](https://arxiv.org/abs/1904.13216)|[signal2image-modules-in-deep-neural-networks-for-eeg-classification](https://github.com/pbizopoulos/signal2image-modules-in-deep-neural-networks-for-eeg-classification)| -|[gender bias in depression detection using audio features](https://arxiv.org/abs/2010.15120)|[DepAudioNet_reproduction](https://github.com/adbailey1/DepAudioNet_reproduction)| -|[m-ar-k-fast independent component analysis](https://arxiv.org/abs/2108.07908)|[_fastica.py](https://github.com/luca-parisi/m-arcsinh_scikit-learn_TensorFlow_Keras/blob/master/_fastica.py)| +|date|paper|code| +|---|---|---| +|2108.07908|[m-ar-k-fast independent component analysis](https://arxiv.org/abs/2108.07908)|[_fastica.py](https://github.com/luca-parisi/m-arcsinh_scikit-learn_TensorFlow_Keras/blob/master/_fastica.py)| ## 2021-08-18 -|paper|code| -|---|---| -|[deep completion autoencoders for radio map estimation](https://arxiv.org/abs/2005.05964)|[deep-autoencoders-cartography](https://github.com/yvestegnya2/deep-autoencoders-cartography)| -|[a sketching framework for reduced data transfer in photon counting lidar](https://arxiv.org/abs/2102.08732)|[sketched_lidar](https://gitlab.com/Tachella/sketched_lidar)| -|[towards fast region adaptive ultrasound beamformer for plane wave imaging using convolutional neural networks](https://arxiv.org/abs/2106.07006)|[cnnusbf](https://github.com/rpm1412/cnnusbf)| -|[progressive transmission using recurrent neural networks](https://arxiv.org/abs/2108.01643)|[Progressive_transmission](https://github.com/safarisadegh/Progressive_transmission)| -|[language-independent approach for automatic computation of vowel articulation features in dysarthric speech assessment](https://arxiv.org/abs/2108.06943)|[autovai](https://github.com/speechcog/autovai)| -|[precision and accuracy of acoustic gunshot location in an urban environment](https://arxiv.org/abs/2108.07377)|[research.accuracy-of-gunshot-location](https://github.com/shotspotter/research.accuracy-of-gunshot-location)| -|[how powerful is graph convolution for recommendation?](https://arxiv.org/abs/2108.07567)|[GF_CF](https://github.com/yshenaw/GF_CF)| -|[lossy compression for lossless prediction](https://arxiv.org/abs/2106.10800)|[lossyless](https://github.com/YannDubs/lossyless)| -|[arbitrary-length analogs to de bruijn sequences](https://arxiv.org/abs/2108.07759)|[pkl](https://github.com/nelloreward/pkl)| +|date|paper|code| +|---|---|---| +|2108.01643|[progressive transmission using recurrent neural networks](https://arxiv.org/abs/2108.01643)|[Progressive_transmission](https://github.com/safarisadegh/Progressive_transmission)| +|2108.06943|[language-independent approach for automatic computation of vowel articulation features in dysarthric speech assessment](https://arxiv.org/abs/2108.06943)|[autovai](https://github.com/speechcog/autovai)| +|2108.07377|[precision and accuracy of acoustic gunshot location in an urban environment](https://arxiv.org/abs/2108.07377)|[research.accuracy-of-gunshot-location](https://github.com/shotspotter/research.accuracy-of-gunshot-location)| +|2108.07567|[how powerful is graph convolution for recommendation?](https://arxiv.org/abs/2108.07567)|[GF_CF](https://github.com/yshenaw/GF_CF)| +|2108.07759|[arbitrary-length analogs to de bruijn sequences](https://arxiv.org/abs/2108.07759)|[pkl](https://github.com/nelloreward/pkl)| ## 2021-08-17 -|paper|code| -|---|---| -|[homological time series analysis of sensor signals from power plants](https://arxiv.org/abs/2106.02493)|[TwirlFlake](https://github.com/karhunenloeve/TwirlFlake)| -|[unique sparse decomposition of low rank matrices](https://arxiv.org/abs/2106.07736)|[Unique_Fac_of_Low_Rank](https://github.com/Jindiande/Unique_Fac_of_Low_Rank)| -|[a greedy algorithm for quantizing neural networks](https://arxiv.org/abs/2010.15979)|[quantized_neural_networks](https://github.com/elybrand/quantized_neural_networks)| -|[mode-wise tensor decompositions: multi-dimensional generalizations of cur decompositions](https://arxiv.org/abs/2103.11037)|[Modewise_Tensor_Decomp](https://github.com/caesarcai/Modewise_Tensor_Decomp)| +|date|paper|code| +|---|---|---| ## 2021-08-16 -|paper|code| -|---|---| -|[irs-aided swipt: joint waveform, active and passive beamforming design under nonlinear harvester model](https://arxiv.org/abs/2012.05646)|[irs-aided-swipt-joint-waveform-active-and-passive-beamforming-design-under-nonlinear-harvester-model](https://github.com/snowztail/irs-aided-swipt-joint-waveform-active-and-passive-beamforming-design-under-nonlinear-harvester-model)| +|date|paper|code| +|---|---|---| ## 2021-08-13 -|paper|code| -|---|---| -|[is the brain macroscopically linear? a system identification of resting state dynamics](https://arxiv.org/abs/2012.12351)|[rest-system-id](https://github.com/enozari/rest-system-id)| +|date|paper|code| +|---|---|---| ## 2021-08-12 -|paper|code| -|---|---| -|[statistical inference in the differential privacy model](https://arxiv.org/abs/2108.05000)|[INSPECTRE](https://github.com/HuanyuZhang/INSPECTRE)| +|date|paper|code| +|---|---|---| +|2108.05000|[statistical inference in the differential privacy model](https://arxiv.org/abs/2108.05000)|[INSPECTRE](https://github.com/HuanyuZhang/INSPECTRE)| ## 2021-08-11 -|paper|code| -|---|---| -|[adversarially-trained nonnegative matrix factorization](https://arxiv.org/abs/2104.04757)|[AT_NMF](https://github.com/caiting123321/AT_NMF)| -|[an open framework for analyzing and modeling xr network traffic](https://arxiv.org/abs/2108.04577)|[ns-3-vr-app](https://github.com/signetlabdei/ns-3-vr-app)| -|[a generalizable model-and-data driven approach for open-set rff authentication](https://arxiv.org/abs/2108.04436)|[ns-rff](https://github.com/xrj-com/ns-rff)| +|date|paper|code| +|---|---|---| +|2108.04577|[an open framework for analyzing and modeling xr network traffic](https://arxiv.org/abs/2108.04577)|[ns-3-vr-app](https://github.com/signetlabdei/ns-3-vr-app)| +|2108.04436|[a generalizable model-and-data driven approach for open-set rff authentication](https://arxiv.org/abs/2108.04436)|[ns-rff](https://github.com/xrj-com/ns-rff)| ## 2021-08-10 -|paper|code| -|---|---| -|[detecting false data injection attacks in smart grids with modeling errors: a deep transfer learning based approach](https://arxiv.org/abs/2104.06307)|[DTL-FDIA-TSG](https://github.com/599143868/DTL-FDIA-TSG)| -|[deep single shot musical instrument identification using scalograms](https://arxiv.org/abs/2108.03569)|[deep-single-shot-musical-instrument-identificationusing-time-frequency-localized-features](https://github.com/dibakar1/deep-single-shot-musical-instrument-identificationusing-time-frequency-localized-features)| -|[beatnet: crnn and particle filtering for online joint beat downbeat and meter tracking](https://arxiv.org/abs/2108.03576)|[beatnet](https://github.com/mjhydri/beatnet)| +|date|paper|code| +|---|---|---| +|2108.03569|[deep single shot musical instrument identification using scalograms](https://arxiv.org/abs/2108.03569)|[deep-single-shot-musical-instrument-identificationusing-time-frequency-localized-features](https://github.com/dibakar1/deep-single-shot-musical-instrument-identificationusing-time-frequency-localized-features)| +|2108.03576|[beatnet: crnn and particle filtering for online joint beat downbeat and meter tracking](https://arxiv.org/abs/2108.03576)|[beatnet](https://github.com/mjhydri/beatnet)| ## 2021-08-09 -|paper|code| -|---|---| -|[searching for waveforms on spatially-filtered epileptic ecog](https://arxiv.org/abs/2103.13853)|[cspwave](https://github.com/chmendoza/cspwave)| +|date|paper|code| +|---|---|---| ## 2021-08-06 -|paper|code| -|---|---| -|[clnet: complex input lightweight neural network designed for massive mimo csi feedback](https://arxiv.org/abs/2102.07507)|[CLNet](https://github.com/SIJIEJI/CLNet)| -|[foundations of user-centric cell-free massive mimo](https://arxiv.org/abs/2108.02541)|[cell-free-book](https://github.com/emilbjornson/cell-free-book)| +|date|paper|code| +|---|---|---| +|2108.02541|[foundations of user-centric cell-free massive mimo](https://arxiv.org/abs/2108.02541)|[cell-free-book](https://github.com/emilbjornson/cell-free-book)| ## 2021-08-05 -|paper|code| -|---|---| -|[random convolution kernels with multi-scale decomposition for preterm eeg inter-burst detection](https://arxiv.org/abs/2108.02039)|[ms_rocket](https://github.com/otoolej/ms_rocket)| +|date|paper|code| +|---|---|---| +|2108.02039|[random convolution kernels with multi-scale decomposition for preterm eeg inter-burst detection](https://arxiv.org/abs/2108.02039)|[ms_rocket](https://github.com/otoolej/ms_rocket)| ## 2021-08-04 -|paper|code| -|---|---| -|[sequential weakly labeled multi-activity localization and recognition on wearable sensors using recurrent attention networks](https://arxiv.org/abs/2004.05768)|[RAN](https://github.com/KennCoder7/RAN)| -|[progressive transmission using recurrent neural networks](https://arxiv.org/abs/2108.01643)|[Progressive_transmission](https://github.com/safarisadegh/Progressive_transmission)| -|[robust compressed sensing mri with deep generative priors](https://arxiv.org/abs/2108.01368)|[csgm-mri-langevin](https://github.com/utcsilab/csgm-mri-langevin)| +|date|paper|code| +|---|---|---| +|2108.01643|[progressive transmission using recurrent neural networks](https://arxiv.org/abs/2108.01643)|[Progressive_transmission](https://github.com/safarisadegh/Progressive_transmission)| +|2108.01368|[robust compressed sensing mri with deep generative priors](https://arxiv.org/abs/2108.01368)|[csgm-mri-langevin](https://github.com/utcsilab/csgm-mri-langevin)| ## 2021-08-03 -|paper|code| -|---|---| -|[deep residual learning for channel estimation in intelligent reflecting surface-assisted multi-user communications](https://arxiv.org/abs/2009.01423)|[CDRN-channel-estimation-IRS](https://github.com/XML124/CDRN-channel-estimation-IRS)| -|[robust enf estimation based on harmonic enhancement and maximum weight clique](https://arxiv.org/abs/2011.03414)|[ENF-WHU-Dataset](https://github.com/ghuawhu/ENF-WHU-Dataset)| -|[opencsi: an open-source dataset for indoor localization using csi-based fingerprinting](https://arxiv.org/abs/2104.07963)|[thymio-radio-map](https://github.com/arthurgassner/thymio-radio-map)| -|[a scalable federated multi-agent architecture for networked connected communication network](https://arxiv.org/abs/2108.00506)|[Fed-MF-MAL](https://github.com/paperflight/Fed-MF-MAL)| -|[few-shot calibration of low-cost air pollution (pm2.5) sensors using meta-learning](https://arxiv.org/abs/2108.00640)|[2021KalpitBTMT](https://github.com/madhavlab/2021KalpitBTMT)| +|date|paper|code| +|---|---|---| +|2108.00506|[a scalable federated multi-agent architecture for networked connected communication network](https://arxiv.org/abs/2108.00506)|[Fed-MF-MAL](https://github.com/paperflight/Fed-MF-MAL)| +|2108.00640|[few-shot calibration of low-cost air pollution (pm2.5) sensors using meta-learning](https://arxiv.org/abs/2108.00640)|[2021KalpitBTMT](https://github.com/madhavlab/2021KalpitBTMT)| ## 2021-08-02 -|paper|code| -|---|---| -|[on the interpretation of linear riemannian tangent space model parameters in m/eeg](https://arxiv.org/abs/2107.14398)|[interpret_lin_rts_mdls](https://github.com/rkobler/interpret_lin_rts_mdls)| +|date|paper|code| +|---|---|---| diff --git a/archives/2021/09.md b/archives/2021/09.md index 71fb52c5..81330c63 100644 --- a/archives/2021/09.md +++ b/archives/2021/09.md @@ -1,129 +1,92 @@ # September 2021 Archive ## 2021-09-30 -|paper|code| -|---|---| -|[deep augmented music algorithm for data-driven doa estimation](https://arxiv.org/abs/2109.10581)|[icassp22](https://github.com/da-music/icassp22)| -|[optimal sic ordering and power allocation in downlink multi-cell noma systems](https://arxiv.org/abs/2102.05015)|[Optimal-JSPA-MultiCell-NOMA](https://gitlab.com/sepehrrezvani/Optimal-JSPA-MultiCell-NOMA)| +|date|paper|code| +|---|---|---| +|2109.10581|[deep augmented music algorithm for data-driven doa estimation](https://arxiv.org/abs/2109.10581)|[icassp22](https://github.com/da-music/icassp22)| ## 2021-09-29 -|paper|code| -|---|---| -|[robust localization in wireless networks from corrupted signals](https://arxiv.org/abs/2010.16297)|[RobustLocalization](https://github.com/Muhammad-Osama/RobustLocalization)| -|[cobiveco: consistent biventricular coordinates for precise and intuitive description of position in the heart -- with matlab implementation](https://arxiv.org/abs/2102.02898)|[Cobiveco](https://github.com/KIT-IBT/Cobiveco)| +|date|paper|code| +|---|---|---| ## 2021-09-28 -|paper|code| -|---|---| -|[the generalized method of moments for multi-reference alignment](https://arxiv.org/abs/2103.02215)|[gmm-cryo](https://github.com/abasasa/gmm-cryo)| -|[error thresholds for arbitrary pauli noise](https://arxiv.org/abs/1910.00471)|[graph-states-coherent-info](https://github.com/felixled/graph-states-coherent-info)| -|[revisiting minimum description length complexity in overparameterized models](https://arxiv.org/abs/2006.10189)|[mdl-complexity](https://github.com/csinva/mdl-complexity)| +|date|paper|code| +|---|---|---| ## 2021-09-27 -|paper|code| -|---|---| -|[afp-src: identification of antifreeze proteins using sparse representation classifier](https://arxiv.org/abs/2009.05277)|[AFP-SRC](https://github.com/Shujaat123/AFP-SRC)| -|[sparse multi-reference alignment: sample complexity and computational hardness](https://arxiv.org/abs/2109.11656)|[sparsemra](https://github.com/tamirbendory/sparsemra)| -|[generalized autocorrelation analysis for multi-target detection](https://arxiv.org/abs/2109.11813)|[mtd-gmm](https://github.com/krshay/mtd-gmm)| -|[coded sparse matrix computation schemes that leverage partial stragglers](https://arxiv.org/abs/2012.06065)|[LeveragePartialStragglers](https://github.com/anindyabijoydas/LeveragePartialStragglers)| -|[the value of information and efficient switching in channel selection](https://arxiv.org/abs/2101.03888)|[valueofinformationandefficientswitching](https://github.com/yoninazarathy/valueofinformationandefficientswitching)| -|[estimating r\'enyi's $\alpha$-cross-entropies in a matrix-based way](https://arxiv.org/abs/2109.11737)|[mbrce](https://github.com/isledge/mbrce)| +|date|paper|code| +|---|---|---| +|2109.11656|[sparse multi-reference alignment: sample complexity and computational hardness](https://arxiv.org/abs/2109.11656)|[sparsemra](https://github.com/tamirbendory/sparsemra)| +|2109.11813|[generalized autocorrelation analysis for multi-target detection](https://arxiv.org/abs/2109.11813)|[mtd-gmm](https://github.com/krshay/mtd-gmm)| +|2109.11737|[estimating r\'enyi's $\alpha$-cross-entropies in a matrix-based way](https://arxiv.org/abs/2109.11737)|[mbrce](https://github.com/isledge/mbrce)| ## 2021-09-24 -|paper|code| -|---|---| -|[quantization and deployment of deep neural networks on microcontrollers](https://arxiv.org/abs/2105.13331)|[microai_public](https://bitbucket.org/edge-team-leat/microai_public)| -|[unified signal compression using a gan with iterative latent representation optimization](https://arxiv.org/abs/2109.11168)|[bpgan-signal-compression](https://github.com/bowenl0218/bpgan-signal-compression)| +|date|paper|code| +|---|---|---| +|2109.11168|[unified signal compression using a gan with iterative latent representation optimization](https://arxiv.org/abs/2109.11168)|[bpgan-signal-compression](https://github.com/bowenl0218/bpgan-signal-compression)| ## 2021-09-23 -|paper|code| -|---|---| -|[deep augmented music algorithm for data-driven doa estimation](https://arxiv.org/abs/2109.10581)|[icassp22](https://github.com/da-music/icassp22)| -|[practical distributed quantum information processing with loccnet](https://arxiv.org/abs/2101.12190)|[Quantum](https://github.com/PaddlePaddle/Quantum)| +|date|paper|code| +|---|---|---| +|2109.10581|[deep augmented music algorithm for data-driven doa estimation](https://arxiv.org/abs/2109.10581)|[icassp22](https://github.com/da-music/icassp22)| ## 2021-09-21 -|paper|code| -|---|---| -|[multi-reference alignment in high dimensions: sample complexity and phase transition](https://arxiv.org/abs/2007.11482)|[high-dimensional-mra-bounds](https://github.com/TamirBendory/high-dimensional-mra-bounds)| -|[removing noise from extracellular neural recordings using fully convolutional denoising autoencoders](https://arxiv.org/abs/2109.08945)|[fcdae-neural-signal-denoising](https://github.com/alexdelitzas/fcdae-neural-signal-denoising)| -|[measuring the volatility of the political agenda in public opinion and news media](https://arxiv.org/abs/1808.09037)|[polvol](https://github.com/euagendas/polvol)| -|[on the curvatures of gaussian random field manifolds](https://arxiv.org/abs/2109.09204)|[curvature_gmrf](https://github.com/alexandrelevada/curvature_gmrf)| +|date|paper|code| +|---|---|---| +|2109.08945|[removing noise from extracellular neural recordings using fully convolutional denoising autoencoders](https://arxiv.org/abs/2109.08945)|[fcdae-neural-signal-denoising](https://github.com/alexdelitzas/fcdae-neural-signal-denoising)| +|2109.09204|[on the curvatures of gaussian random field manifolds](https://arxiv.org/abs/2109.09204)|[curvature_gmrf](https://github.com/alexandrelevada/curvature_gmrf)| ## 2021-09-20 -|paper|code| -|---|---| -|[irs-aided swipt: joint waveform, active and passive beamforming design under nonlinear harvester model](https://arxiv.org/abs/2012.05646)|[irs-aided-swipt-joint-waveform-active-and-passive-beamforming-design-under-nonlinear-harvester-model](https://github.com/snowztail/irs-aided-swipt-joint-waveform-active-and-passive-beamforming-design-under-nonlinear-harvester-model)| +|date|paper|code| +|---|---|---| ## 2021-09-17 -|paper|code| -|---|---| -|[cross-domain activity recognition via substructural optimal transport](https://arxiv.org/abs/2102.03353)|[transferlearning](https://github.com/jindongwang/transferlearning)| -|[a scalable federated multi-agent architecture for networked connected communication network](https://arxiv.org/abs/2108.00506)|[Fed-MF-MAL](https://github.com/paperflight/Fed-MF-MAL)| +|date|paper|code| +|---|---|---| ## 2021-09-16 -|paper|code| -|---|---| -|[optimizing a binary intelligent reflecting surface for ofdm communications under mutual coupling](https://arxiv.org/abs/2106.04280)|[SP_Cup_2021](https://github.com/emilbjornson/SP_Cup_2021)| -|[the emergence of the shape bias results from communicative efficiency](https://arxiv.org/abs/2109.06232)|[emergent-shape-bias](https://github.com/evaportelance/emergent-shape-bias)| +|date|paper|code| +|---|---|---| +|2109.06232|[the emergence of the shape bias results from communicative efficiency](https://arxiv.org/abs/2109.06232)|[emergent-shape-bias](https://github.com/evaportelance/emergent-shape-bias)| ## 2021-09-15 -|paper|code| -|---|---| -|[honest-but-curious nets: sensitive attributes of private inputs can be secretly coded into the classifiers' outputs](https://arxiv.org/abs/2105.12049)|[honest-but-curious-nets](https://github.com/mmalekzadeh/honest-but-curious-nets)| -|[distilling ghz states using stabilizer codes](https://arxiv.org/abs/2109.06248)|[ghz_distillation_qec](https://github.com/nrenga/ghz_distillation_qec)| +|date|paper|code| +|---|---|---| +|2109.06248|[distilling ghz states using stabilizer codes](https://arxiv.org/abs/2109.06248)|[ghz_distillation_qec](https://github.com/nrenga/ghz_distillation_qec)| ## 2021-09-14 -|paper|code| -|---|---| -|[proactive and aoi-aware failure recovery for stateful nfv-enabled zero-touch 6g networks: model-free drl approach](https://arxiv.org/abs/2103.03817)|[ZT-PFR](https://github.com/wildsky95/ZT-PFR)| -|[on the feasibility of modeling ofdm communication signals with unsupervised generative adversarial networks](https://arxiv.org/abs/2109.05107)|[ofdm-gan](https://github.com/usnistgov/ofdm-gan)| -|[modelling the utility of group testing for public health surveillance](https://arxiv.org/abs/2109.05378)|[group-testing](https://github.com/g-pichler/group-testing)| -|[rwp+: a new random waypoint model for high-speed mobility](https://arxiv.org/abs/2109.05978)|[rwp](https://github.com/ammarhuss/rwp)| +|date|paper|code| +|---|---|---| +|2109.05107|[on the feasibility of modeling ofdm communication signals with unsupervised generative adversarial networks](https://arxiv.org/abs/2109.05107)|[ofdm-gan](https://github.com/usnistgov/ofdm-gan)| +|2109.05378|[modelling the utility of group testing for public health surveillance](https://arxiv.org/abs/2109.05378)|[group-testing](https://github.com/g-pichler/group-testing)| +|2109.05978|[rwp+: a new random waypoint model for high-speed mobility](https://arxiv.org/abs/2109.05978)|[rwp](https://github.com/ammarhuss/rwp)| ## 2021-09-13 -|paper|code| -|---|---| -|[two-dimensional multi-target detection: an autocorrelation analysis approach](https://arxiv.org/abs/2105.06765)|[MTD-2D](https://github.com/krshay/MTD-2D)| +|date|paper|code| +|---|---|---| ## 2021-09-10 -|paper|code| -|---|---| -|[deep completion autoencoders for radio map estimation](https://arxiv.org/abs/2005.05964)|[deep-autoencoders-cartography](https://github.com/yvestegnya2/deep-autoencoders-cartography)| -|[total least squares phase retrieval](https://arxiv.org/abs/2102.00927)|[tls_phase](https://github.com/swing-research/tls_phase)| -|[a bayesian framework for information-theoretic probing](https://arxiv.org/abs/2109.03853)|[bayesian-mi](https://github.com/rycolab/bayesian-mi)| +|date|paper|code| +|---|---|---| +|2109.03853|[a bayesian framework for information-theoretic probing](https://arxiv.org/abs/2109.03853)|[bayesian-mi](https://github.com/rycolab/bayesian-mi)| ## 2021-09-09 -|paper|code| -|---|---| -|[mgait: model-based gait analysis using wearable bend and inertial sensors](https://arxiv.org/abs/2102.11895)|[mgait](https://github.com/sizhean/mgait)| -|[federated edge learning with misaligned over-the-air computation](https://arxiv.org/abs/2102.13604)|[MisAlignedOAC](https://github.com/lynshao/MisAlignedOAC)| +|date|paper|code| +|---|---|---| ## 2021-09-08 -|paper|code| -|---|---| -|[homological time series analysis of sensor signals from power plants](https://arxiv.org/abs/2106.02493)|[TwirlFlake](https://github.com/karhunenloeve/TwirlFlake)| -|[multi-layer bilinear generalized approximate message passing](https://arxiv.org/abs/2007.00436)|[ML-BiGAMP](https://github.com/QiuyunZou/ML-BiGAMP)| -|[fusion of dual spatial information for hyperspectral image classification](https://arxiv.org/abs/2010.12337)|[Fusion-of-Dual-Spatial-Information-for-Hyperspectral-Image-Classification](https://github.com/PuhongDuan/Fusion-of-Dual-Spatial-Information-for-Hyperspectral-Image-Classification)| +|date|paper|code| +|---|---|---| ## 2021-09-07 -|paper|code| -|---|---| -|[quasi monte carlo time-frequency analysis](https://arxiv.org/abs/2011.02025)|[LTFT-Phase-Vocoder](https://github.com/RonLevie/LTFT-Phase-Vocoder)| -|[a tutorial on generalized eigendecomposition for source separation in multichannel electrophysiology](https://arxiv.org/abs/2104.12356)|[GED_tutorial](https://github.com/mikexcohen/GED_tutorial)| -|[a variational approach to privacy and fairness](https://arxiv.org/abs/2006.06332)|[VariationalPrivacyFairness](https://github.com/burklight/VariationalPrivacyFairness)| -|[variational quantum algorithms for trace distance and fidelity estimation](https://arxiv.org/abs/2012.05768)|[Quantum](https://github.com/PaddlePaddle/Quantum)| +|date|paper|code| +|---|---|---| ## 2021-09-06 -|paper|code| -|---|---| -|[time encoding of finite-rate-of-innovation signals](https://arxiv.org/abs/2107.03344)|[genfri-tem](https://github.com/kamath-abhijith/genfri-tem)| -|[achievable rate optimization for mimo systems with reconfigurable intelligent surfaces](https://arxiv.org/abs/2008.09563)|[pgm_code_achievable_rate_optimization](https://gitlab.com/n.s.perovic/pgm_code_achievable_rate_optimization)| +|date|paper|code| +|---|---|---| ## 2021-09-01 -|paper|code| -|---|---| -|[support recovery for sparse multidimensional phase retrieval](https://arxiv.org/abs/2011.00619)|[multi-dimensional-turnpike](https://github.com/sew347/multi-dimensional-turnpike)| -|[signal recovery from a few linear measurements of its high-order spectra](https://arxiv.org/abs/2103.01551)|[recovery-high-order-spectra](https://github.com/krshay/recovery-high-order-spectra)| -|[efficient sparse coding using hierarchical riemannian pursuit](https://arxiv.org/abs/2104.10314)|[HRP](https://github.com/yokoxue/HRP)| -|[oversampling highly imbalanced indoor positioning data using deep generative models](https://arxiv.org/abs/2108.13503)|[oversampling_ble_fingerprints](https://github.com/alhomayani/oversampling_ble_fingerprints)| +|date|paper|code| +|---|---|---| diff --git a/archives/2021/10.md b/archives/2021/10.md index 8ceb5f9d..b60c6580 100644 --- a/archives/2021/10.md +++ b/archives/2021/10.md @@ -1,167 +1,123 @@ # October 2021 Archive ## 2021-10-29 -|paper|code| -|---|---| -|[nch sleep databank: a large collection of real-world pediatric sleep studies](https://arxiv.org/abs/2102.13284)|[sleep_study](https://github.com/liboyue/sleep_study)| -|[self-supervised eeg representation learning for automatic sleep staging](https://arxiv.org/abs/2110.15278)|[contrawr](https://github.com/ycq091044/contrawr)| -|[error thresholds for arbitrary pauli noise](https://arxiv.org/abs/1910.00471)|[graph-states-coherent-info](https://github.com/felixled/graph-states-coherent-info)| -|[modelling the utility of group testing for public health surveillance](https://arxiv.org/abs/2109.05378)|[group-testing](https://github.com/g-pichler/group-testing)| +|date|paper|code| +|---|---|---| +|2110.15278|[self-supervised eeg representation learning for automatic sleep staging](https://arxiv.org/abs/2110.15278)|[contrawr](https://github.com/ycq091044/contrawr)| ## 2021-10-28 -|paper|code| -|---|---| -|[robust generalization despite distribution shift via minimum discriminating information](https://arxiv.org/abs/2106.04443)|[pmdi_dro](https://github.com/tobsutter/pmdi_dro)| -|[(almost) free incentivized exploration from decentralized learning agents](https://arxiv.org/abs/2110.14628)|[observe_then_incentivize](https://github.com/shengroup/observe_then_incentivize)| +|date|paper|code| +|---|---|---| +|2110.14628|[(almost) free incentivized exploration from decentralized learning agents](https://arxiv.org/abs/2110.14628)|[observe_then_incentivize](https://github.com/shengroup/observe_then_incentivize)| ## 2021-10-27 -|paper|code| -|---|---| -|[recovery analysis for plug-and-play priors using the restricted eigenvalue condition](https://arxiv.org/abs/2106.03668)|[pnp-recovery](https://github.com/wustl-cig/pnp-recovery)| -|[resilient uav swarm communications with graph convolutional neural network](https://arxiv.org/abs/2106.16048)|[resilient-swarm-communications-with-meta-graph-convolutional-networks](https://github.com/nobodymx/resilient-swarm-communications-with-meta-graph-convolutional-networks)| -|[neural estimators for conditional mutual information using nearest neighbors sampling](https://arxiv.org/abs/2006.07225)|[CMI_Neural_Estimator](https://github.com/smolavipour/CMI_Neural_Estimator)| -|[leadcache: regret-optimal caching in networks](https://arxiv.org/abs/2009.08228)|[leadcache-neurips21](https://github.com/abhishekmitiitm/leadcache-neurips21)| +|date|paper|code| +|---|---|---| ## 2021-10-26 -|paper|code| -|---|---| -|[signal processing based deep learning for blind symbol decoding and modulation classification](https://arxiv.org/abs/2106.10543)|[dual_path_network](https://github.com/uclacores/dual_path_network)| -|[task-based graph signal compression](https://arxiv.org/abs/2110.12387)|[graph_signal_compression](https://github.com/pei65536/graph_signal_compression)| -|[optimal sic ordering and power allocation in downlink multi-cell noma systems](https://arxiv.org/abs/2102.05015)|[Optimal-JSPA-MultiCell-NOMA](https://gitlab.com/sepehrrezvani/Optimal-JSPA-MultiCell-NOMA)| -|[teramimo: a channel simulator for wideband ultra-massive mimo terahertz communications](https://arxiv.org/abs/2104.11054)|[TeraMIMO](https://github.com/hasarieddeen/TeraMIMO)| +|date|paper|code| +|---|---|---| +|2110.12387|[task-based graph signal compression](https://arxiv.org/abs/2110.12387)|[graph_signal_compression](https://github.com/pei65536/graph_signal_compression)| ## 2021-10-22 -|paper|code| -|---|---| -|[learning to demodulate from few pilots via offline and online meta-learning](https://arxiv.org/abs/1908.09049)|[meta-demodulator](https://github.com/kclip/meta-demodulator)| -|[meta-learning to communicate: fast end-to-end training for fading channels](https://arxiv.org/abs/1910.09945)|[meta-autoencoder](https://github.com/kclip/meta-autoencoder)| -|[end-to-end fast training of communication links without a channel model via online meta-learning](https://arxiv.org/abs/2003.01479)|[meta-autoencoder-without-channel-model](https://github.com/kclip/meta-autoencoder-without-channel-model)| -|[truly shift-equivariant convolutional neural networks with adaptive polyphase upsampling](https://arxiv.org/abs/2105.04040)|[truly_shift_invariant_cnns](https://github.com/achaman2/truly_shift_invariant_cnns)| -|[real-m: towards speech separation on real mixtures](https://arxiv.org/abs/2110.10812)|[sisnr-estimation](https://github.com/speechbrain/speechbrain/tree/develop/recipes/REAL-M/sisnr-estimation)| -|[from learning to meta-learning: reduced training overhead and complexity for communication systems](https://arxiv.org/abs/2001.01227)|[meta-autoencoder](https://github.com/kclip/meta-autoencoder)| -|[on fading channel dependency structures with a positive zero-outage capacity](https://arxiv.org/abs/2102.02541)|[zero-outage-joint-distributions](https://gitlab.com/klb2/zero-outage-joint-distributions)| +|date|paper|code| +|---|---|---| +|2110.10812|[real-m: towards speech separation on real mixtures](https://arxiv.org/abs/2110.10812)|[sisnr-estimation](https://github.com/speechbrain/speechbrain/tree/develop/recipes/REAL-M/sisnr-estimation)| ## 2021-10-20 -|paper|code| -|---|---| -|[learning task-oriented communication for edge inference: an information bottleneck approach](https://arxiv.org/abs/2102.04170)|[VL-VFE](https://github.com/shaojiawei07/VL-VFE)| -|[easycom: an augmented reality dataset to support algorithms for easy communication in noisy environments](https://arxiv.org/abs/2107.04174)|[EasyComDataset](https://github.com/facebookresearch/EasyComDataset)| -|[wideband and entropy-aware deep soft bit quantization](https://arxiv.org/abs/2110.09541)|[wideband-llr-deep](https://github.com/utcsilab/wideband-llr-deep)| -|[learning to learn graph topologies](https://arxiv.org/abs/2110.09807)|[l2g-neurips2021](https://github.com/xpuoxford/l2g-neurips2021)| -|[a cautionary tale on fitting decision trees to data from additive models: generalization lower bounds](https://arxiv.org/abs/2110.09626)|[additive_trees](https://github.com/aagarwal1996/additive_trees)| +|date|paper|code| +|---|---|---| +|2110.09541|[wideband and entropy-aware deep soft bit quantization](https://arxiv.org/abs/2110.09541)|[wideband-llr-deep](https://github.com/utcsilab/wideband-llr-deep)| +|2110.09807|[learning to learn graph topologies](https://arxiv.org/abs/2110.09807)|[l2g-neurips2021](https://github.com/xpuoxford/l2g-neurips2021)| +|2110.09626|[a cautionary tale on fitting decision trees to data from additive models: generalization lower bounds](https://arxiv.org/abs/2110.09626)|[additive_trees](https://github.com/aagarwal1996/additive_trees)| ## 2021-10-19 -|paper|code| -|---|---| -|[learning how to demodulate from few pilots via meta-learning](https://arxiv.org/abs/1903.02184)|[meta-demodulator](https://github.com/kclip/meta-demodulator)| -|[localized fourier analysis for graph signal processing](https://arxiv.org/abs/1906.04529)|[loclets](https://bitbucket.org/batistbucket/loclets)| -|[unsupervised learned kalman filtering](https://arxiv.org/abs/2110.09005)|[Unsupervised_ICASSP22](https://github.com/KalmanNet/Unsupervised_ICASSP22)| -|[perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising](https://arxiv.org/abs/2110.08775)|[perturbative_mean_field_matrix_factorization](https://github.com/sphinxteam/perturbative_mean_field_matrix_factorization)| +|date|paper|code| +|---|---|---| +|2110.09005|[unsupervised learned kalman filtering](https://arxiv.org/abs/2110.09005)|[Unsupervised_ICASSP22](https://github.com/KalmanNet/Unsupervised_ICASSP22)| +|2110.08775|[perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising](https://arxiv.org/abs/2110.08775)|[perturbative_mean_field_matrix_factorization](https://github.com/sphinxteam/perturbative_mean_field_matrix_factorization)| ## 2021-10-18 -|paper|code| -|---|---| -|[edge-sr: super-resolution for the masses](https://arxiv.org/abs/2108.10335)|[esr](https://github.com/pnavarre/esr)| +|date|paper|code| +|---|---|---| ## 2021-10-15 -|paper|code| -|---|---| -|[grouped variable selection for generalized eigenvalue problems](https://arxiv.org/abs/2105.13667)|[benchmarkStudySensorSelection](https://github.com/AlexanderBertrandLab/benchmarkStudySensorSelection)| -|[node-screening tests for l0-penalized least-squares problem with supplementary material](https://arxiv.org/abs/2110.07308)|[bnb-screening](https://gitlab.insa-rennes.fr/Theo.Guyard/bnb-screening)| -|[stability analysis of unfolded wmmse for power allocation](https://arxiv.org/abs/2110.07471)|[stability-uwmmse](https://github.com/archo48/stability-uwmmse)| -|[smgc: a complex-valued graph convolutional network via magnetic laplacian for directed graphs](https://arxiv.org/abs/2110.07570)|[MGCs](https://github.com/hazdzz/MGCs)| -|[new instances of quadratic apn functions](https://arxiv.org/abs/2009.07204)|[quadratic_apn](https://github.com/cbe90/quadratic_apn)| -|[construction of optimal spectral methods in phase retrieval](https://arxiv.org/abs/2012.04524)|[Optimal_Spectral_Methods_PR](https://github.com/AnMaillard/Optimal_Spectral_Methods_PR)| -|[mode-wise tensor decompositions: multi-dimensional generalizations of cur decompositions](https://arxiv.org/abs/2103.11037)|[Modewise_Tensor_Decomp](https://github.com/caesarcai/Modewise_Tensor_Decomp)| -|[admm-dad net: a deep unfolding network for analysis compressed sensing](https://arxiv.org/abs/2110.06986)|[ADMM-DAD](https://github.com/vicky-k-19/ADMM-DAD)| +|date|paper|code| +|---|---|---| +|2110.07308|[node-screening tests for l0-penalized least-squares problem with supplementary material](https://arxiv.org/abs/2110.07308)|[bnb-screening](https://gitlab.insa-rennes.fr/Theo.Guyard/bnb-screening)| +|2110.07471|[stability analysis of unfolded wmmse for power allocation](https://arxiv.org/abs/2110.07471)|[stability-uwmmse](https://github.com/archo48/stability-uwmmse)| +|2110.07570|[smgc: a complex-valued graph convolutional network via magnetic laplacian for directed graphs](https://arxiv.org/abs/2110.07570)|[MGCs](https://github.com/hazdzz/MGCs)| +|2110.06986|[admm-dad net: a deep unfolding network for analysis compressed sensing](https://arxiv.org/abs/2110.06986)|[ADMM-DAD](https://github.com/vicky-k-19/ADMM-DAD)| ## 2021-10-14 -|paper|code| -|---|---| -|[conditional independence for pretext task selection in self-supervised speech representation learning](https://arxiv.org/abs/2104.07388)|[Pseudo-Label-Selection](https://github.com/salah-zaiem/Pseudo-Label-Selection)| -|[sdr -- medium rare with fast computations](https://arxiv.org/abs/2110.06440)|[fast_bss_eval](https://github.com/fakufaku/fast_bss_eval)| -|[a primer on near-field beamforming for arrays and reconfigurable intelligent surfaces](https://arxiv.org/abs/2110.06661)|[nearfield-primer](https://github.com/emilbjornson/nearfield-primer)| -|[full-stack comparison of channel models for networks above 100 ghz in an indoor scenario](https://arxiv.org/abs/2110.06838)|[thz-mmnets-2021](https://github.com/signetlabdei/thz-mmnets-2021)| +|date|paper|code| +|---|---|---| +|2110.06440|[sdr -- medium rare with fast computations](https://arxiv.org/abs/2110.06440)|[fast_bss_eval](https://github.com/fakufaku/fast_bss_eval)| +|2110.06661|[a primer on near-field beamforming for arrays and reconfigurable intelligent surfaces](https://arxiv.org/abs/2110.06661)|[nearfield-primer](https://github.com/emilbjornson/nearfield-primer)| +|2110.06838|[full-stack comparison of channel models for networks above 100 ghz in an indoor scenario](https://arxiv.org/abs/2110.06838)|[thz-mmnets-2021](https://github.com/signetlabdei/thz-mmnets-2021)| ## 2021-10-13 -|paper|code| -|---|---| -|[benchmarking deep inverse models over time, and the neural-adjoint method](https://arxiv.org/abs/2009.12919)|[BDIMNNA](https://github.com/BensonRen/BDIMNNA)| -|[on entropy and bit patterns of ring oscillator jitter](https://arxiv.org/abs/2102.02196)|[bitpat](https://github.com/mjosaarinen/bitpat)| -|[smoothed separable nonnegative matrix factorization](https://arxiv.org/abs/2110.05528)|[smoothed-separable-nmf](https://gitlab.com/nnadisic/smoothed-separable-nmf)| -|[deepfilternet: a low complexity speech enhancement framework for full-band audio based on deep filtering](https://arxiv.org/abs/2110.05588)|[deepfilternet](https://github.com/rikorose/deepfilternet)| -|[nearest subspace search in the signed cumulative distribution transform space for 1d signal classification](https://arxiv.org/abs/2110.05606)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| -|[label-aware ranked loss for robust people counting using automotive in-cabin radar](https://arxiv.org/abs/2110.05876)|[labelawareranked-loss](https://github.com/2geeks2/labelawareranked-loss)| -|[classification of anomalous gait using machine learning techniques and embedded sensors](https://arxiv.org/abs/2110.06139)|[HumanGait](https://github.com/rTiagoS/HumanGait)| -|[evaluation of latent space disentanglement in the presence of interdependent attributes](https://arxiv.org/abs/2110.05587)|[dependency-aware-mi-metrics](https://github.com/karnwatcharasupat/dependency-aware-mi-metrics)| -|[learned robust pca: a scalable deep unfolding approach for high-dimensional outlier detection](https://arxiv.org/abs/2110.05649)|[lrpca](https://github.com/caesarcai/lrpca)| -|[information theoretic structured generative modeling](https://arxiv.org/abs/2110.05794)|[structured-generative-modeling](https://github.com/bohu615/structured-generative-modeling)| +|date|paper|code| +|---|---|---| +|2110.05528|[smoothed separable nonnegative matrix factorization](https://arxiv.org/abs/2110.05528)|[smoothed-separable-nmf](https://gitlab.com/nnadisic/smoothed-separable-nmf)| +|2110.05588|[deepfilternet: a low complexity speech enhancement framework for full-band audio based on deep filtering](https://arxiv.org/abs/2110.05588)|[deepfilternet](https://github.com/rikorose/deepfilternet)| +|2110.05606|[nearest subspace search in the signed cumulative distribution transform space for 1d signal classification](https://arxiv.org/abs/2110.05606)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| +|2110.05876|[label-aware ranked loss for robust people counting using automotive in-cabin radar](https://arxiv.org/abs/2110.05876)|[labelawareranked-loss](https://github.com/2geeks2/labelawareranked-loss)| +|2110.06139|[classification of anomalous gait using machine learning techniques and embedded sensors](https://arxiv.org/abs/2110.06139)|[HumanGait](https://github.com/rTiagoS/HumanGait)| +|2110.05587|[evaluation of latent space disentanglement in the presence of interdependent attributes](https://arxiv.org/abs/2110.05587)|[dependency-aware-mi-metrics](https://github.com/karnwatcharasupat/dependency-aware-mi-metrics)| +|2110.05649|[learned robust pca: a scalable deep unfolding approach for high-dimensional outlier detection](https://arxiv.org/abs/2110.05649)|[lrpca](https://github.com/caesarcai/lrpca)| +|2110.05794|[information theoretic structured generative modeling](https://arxiv.org/abs/2110.05794)|[structured-generative-modeling](https://github.com/bohu615/structured-generative-modeling)| ## 2021-10-12 -|paper|code| -|---|---| -|[pm2.5-gnn: a domain knowledge enhanced graph neural network for pm2.5 forecasting](https://arxiv.org/abs/2002.12898)|[PM2.5-GNN](https://github.com/shawnwang-tech/PM2.5-GNN)| -|[privacy for free: wireless federated learning via uncoded transmission with adaptive power control](https://arxiv.org/abs/2006.05459)|[Privacy4Free_DPWFL](https://github.com/kclip/Privacy4Free_DPWFL)| -|[deep joint source-channel coding for wireless image transmission with adaptive rate control](https://arxiv.org/abs/2110.04456)|[dynamic_jscc](https://github.com/mingyuyng/dynamic_jscc)| -|[topological data analysis (tda) techniques enhance hand pose classification from ecog neural recordings](https://arxiv.org/abs/2110.04653)|[ecog_vbh_2021](https://github.com/machinelearningjournalclub/ecog_vbh_2021)| -|[rtsnet: deep learning aided kalman smoothing](https://arxiv.org/abs/2110.04717)|[rtsnet_icassp22](https://github.com/kalmannet/rtsnet_icassp22)| -|[uncertainty in data-driven kalman filtering for partially known state-space models](https://arxiv.org/abs/2110.04738)|[errcov_icassp22](https://github.com/kalmannet/errcov_icassp22)| -|[application of graph convolutions in a lightweight model for skeletal human motion forecasting](https://arxiv.org/abs/2110.04810)|[lightweight-motion-forecasting](https://github.com/LucaHermes/lightweight-motion-forecasting)| -|[chaos as an interpretable benchmark for forecasting and data-driven modelling](https://arxiv.org/abs/2110.05266)|[dysts](https://github.com/williamgilpin/dysts)| -|[wavefuse: a unified deep framework for image fusion with discrete wavelet transform](https://arxiv.org/abs/2007.14110)|[WaveFuse_code](https://github.com/slliuEric/WaveFuse_code)| -|[transfer learning based multi-objective genetic algorithm for dynamic community detection](https://arxiv.org/abs/2109.15136)|[TMOGA](https://github.com/zjg540066169/TMOGA)| +|date|paper|code| +|---|---|---| +|2110.04456|[deep joint source-channel coding for wireless image transmission with adaptive rate control](https://arxiv.org/abs/2110.04456)|[dynamic_jscc](https://github.com/mingyuyng/dynamic_jscc)| +|2110.04653|[topological data analysis (tda) techniques enhance hand pose classification from ecog neural recordings](https://arxiv.org/abs/2110.04653)|[ecog_vbh_2021](https://github.com/machinelearningjournalclub/ecog_vbh_2021)| +|2110.04717|[rtsnet: deep learning aided kalman smoothing](https://arxiv.org/abs/2110.04717)|[rtsnet_icassp22](https://github.com/kalmannet/rtsnet_icassp22)| +|2110.04738|[uncertainty in data-driven kalman filtering for partially known state-space models](https://arxiv.org/abs/2110.04738)|[errcov_icassp22](https://github.com/kalmannet/errcov_icassp22)| +|2110.04810|[application of graph convolutions in a lightweight model for skeletal human motion forecasting](https://arxiv.org/abs/2110.04810)|[lightweight-motion-forecasting](https://github.com/LucaHermes/lightweight-motion-forecasting)| +|2110.05266|[chaos as an interpretable benchmark for forecasting and data-driven modelling](https://arxiv.org/abs/2110.05266)|[dysts](https://github.com/williamgilpin/dysts)| ## 2021-10-11 -|paper|code| -|---|---| -|[direct design of biquad filter cascades with deep learning by sampling random polynomials](https://arxiv.org/abs/2110.03691)|[iirnet](https://github.com/csteinmetz1/iirnet)| -|[ensemble neural representation networks](https://arxiv.org/abs/2110.04124)|[enrp](https://github.com/alirezamorsali/enrp)| -|[operanet: a multimodal activity recognition dataset acquired from radio frequency and vision-based sensors](https://arxiv.org/abs/2110.04239)|[oddet](https://github.com/rogetk/oddet)| -|[randomized continuous frames in time-frequency analysis](https://arxiv.org/abs/2009.10525)|[LTFT-Phase-Vocoder](https://github.com/RonLevie/LTFT-Phase-Vocoder)| +|date|paper|code| +|---|---|---| +|2110.03691|[direct design of biquad filter cascades with deep learning by sampling random polynomials](https://arxiv.org/abs/2110.03691)|[iirnet](https://github.com/csteinmetz1/iirnet)| +|2110.04124|[ensemble neural representation networks](https://arxiv.org/abs/2110.04124)|[enrp](https://github.com/alirezamorsali/enrp)| +|2110.04239|[operanet: a multimodal activity recognition dataset acquired from radio frequency and vision-based sensors](https://arxiv.org/abs/2110.04239)|[oddet](https://github.com/rogetk/oddet)| ## 2021-10-08 -|paper|code| -|---|---| -|[light-sernet: a lightweight fully convolutional neural network for speech emotion recognition](https://arxiv.org/abs/2110.03435)|[light-sernet](https://github.com/aryaaftab/light-sernet)| -|[multi-head relu implicit neural representation networks](https://arxiv.org/abs/2110.03448)|[mh-relu-inr](https://github.com/alirezamorsali/mh-relu-inr)| -|[joint inference of multiple graphs with hidden variables from stationary graph signals](https://arxiv.org/abs/2110.03666)|[hidden_joint_inference](https://github.com/reysam93/hidden_joint_inference)| +|date|paper|code| +|---|---|---| +|2110.03435|[light-sernet: a lightweight fully convolutional neural network for speech emotion recognition](https://arxiv.org/abs/2110.03435)|[light-sernet](https://github.com/aryaaftab/light-sernet)| +|2110.03448|[multi-head relu implicit neural representation networks](https://arxiv.org/abs/2110.03448)|[mh-relu-inr](https://github.com/alirezamorsali/mh-relu-inr)| +|2110.03666|[joint inference of multiple graphs with hidden variables from stationary graph signals](https://arxiv.org/abs/2110.03666)|[hidden_joint_inference](https://github.com/reysam93/hidden_joint_inference)| ## 2021-10-07 -|paper|code| -|---|---| -|[point process simulation of generalised inverse gaussian processes and estimation of the jaeger integral](https://arxiv.org/abs/2105.09429)|[GiG](https://github.com/yamankindap/GiG)| -|[an approximate expectation-maximization for two-dimensional multi-target detection](https://arxiv.org/abs/2110.02289)|[mtd-2d-em](https://github.com/krshay/mtd-2d-em)| -|[a local updating algorithm for personalized pagerank via chebyshev polynomials](https://arxiv.org/abs/2110.02538)|[pagerank_updating_chebyshev_paper](https://github.com/estbautista/pagerank_updating_chebyshev_paper)| -|[unrolling particles: unsupervised learning of sampling distributions](https://arxiv.org/abs/2110.02915)|[unrolling-particles](https://github.com/fgfgama/unrolling-particles)| -|[phase retrieval using expectation consistent signal recovery algorithm based on hypernetwork](https://arxiv.org/abs/2101.04348)|[gec-sr-pr-hypernets](https://github.com/wangchangjen/gec-sr-pr-hypernets)| -|[lossy compression for lossless prediction](https://arxiv.org/abs/2106.10800)|[lossyless](https://github.com/YannDubs/lossyless)| +|date|paper|code| +|---|---|---| +|2110.02289|[an approximate expectation-maximization for two-dimensional multi-target detection](https://arxiv.org/abs/2110.02289)|[mtd-2d-em](https://github.com/krshay/mtd-2d-em)| +|2110.02538|[a local updating algorithm for personalized pagerank via chebyshev polynomials](https://arxiv.org/abs/2110.02538)|[pagerank_updating_chebyshev_paper](https://github.com/estbautista/pagerank_updating_chebyshev_paper)| +|2110.02915|[unrolling particles: unsupervised learning of sampling distributions](https://arxiv.org/abs/2110.02915)|[unrolling-particles](https://github.com/fgfgama/unrolling-particles)| ## 2021-10-06 -|paper|code| -|---|---| -|[vtamiq: transformers for attention modulated image quality assessment](https://arxiv.org/abs/2110.01655)|[vtamiq](https://github.com/ch-andrei/vtamiq)| -|[wireless link scheduling via graph representation learning: a comparative study of different supervision levels](https://arxiv.org/abs/2110.01722)|[LinkSchedulingGNNs_SupervisionStudy](https://github.com/navid-naderi/LinkSchedulingGNNs_SupervisionStudy)| +|date|paper|code| +|---|---|---| +|2110.01655|[vtamiq: transformers for attention modulated image quality assessment](https://arxiv.org/abs/2110.01655)|[vtamiq](https://github.com/ch-andrei/vtamiq)| +|2110.01722|[wireless link scheduling via graph representation learning: a comparative study of different supervision levels](https://arxiv.org/abs/2110.01722)|[LinkSchedulingGNNs_SupervisionStudy](https://github.com/navid-naderi/LinkSchedulingGNNs_SupervisionStudy)| ## 2021-10-05 -|paper|code| -|---|---| -|[power scaling laws and near-field behaviors of massive mimo and intelligent reflecting surfaces](https://arxiv.org/abs/2002.04960)|[near-field-behavior](https://github.com/emilbjornson/near-field-behavior)| -|[map-csi: single-site map-assisted localization using massive mimo csi](https://arxiv.org/abs/2110.00654)|[mapcsi](https://github.com/katarinavuckovic/mapcsi)| -|[a robust alternative for graph convolutional neural networks via graph neighborhood filters](https://arxiv.org/abs/2110.00844)|[neighborhoodgf](https://github.com/vmtenorio/neighborhoodgf)| -|[on the curvatures of gaussian random field manifolds](https://arxiv.org/abs/2109.09204)|[curvature_gmrf](https://github.com/alexandrelevada/curvature_gmrf)| +|date|paper|code| +|---|---|---| +|2110.00654|[map-csi: single-site map-assisted localization using massive mimo csi](https://arxiv.org/abs/2110.00654)|[mapcsi](https://github.com/katarinavuckovic/mapcsi)| +|2110.00844|[a robust alternative for graph convolutional neural networks via graph neighborhood filters](https://arxiv.org/abs/2110.00844)|[neighborhoodgf](https://github.com/vmtenorio/neighborhoodgf)| ## 2021-10-04 -|paper|code| -|---|---| -|[deep learning for classifying and characterizing atmospheric ducting within the maritime setting](https://arxiv.org/abs/2005.06524)|[deep-learning-em-ducting](https://github.com/nonlinearfun/deep-learning-em-ducting)| -|[decomposing non-stationary signals with time-varying wave-shape functions](https://arxiv.org/abs/2010.07394)|[SAMD](https://github.com/macolominas/SAMD)| -|[pyffs: a python library for fast fourier series computation](https://arxiv.org/abs/2110.00262)|[pyFFS](https://github.com/imagingofthings/pyFFS)| -|[leveraging power grid topology in machine learning assisted optimal power flow](https://arxiv.org/abs/2110.00306)|[ml-opf](https://github.com/tdfalc/ml-opf)| +|date|paper|code| +|---|---|---| +|2110.00262|[pyffs: a python library for fast fourier series computation](https://arxiv.org/abs/2110.00262)|[pyFFS](https://github.com/imagingofthings/pyFFS)| +|2110.00306|[leveraging power grid topology in machine learning assisted optimal power flow](https://arxiv.org/abs/2110.00306)|[ml-opf](https://github.com/tdfalc/ml-opf)| ## 2021-10-01 -|paper|code| -|---|---| -|[multi-reference alignment in high dimensions: sample complexity and phase transition](https://arxiv.org/abs/2007.11482)|[high-dimensional-mra-bounds](https://github.com/TamirBendory/high-dimensional-mra-bounds)| -|[multi-ris-aided wireless systems: statistical characterization and performance analysis](https://arxiv.org/abs/2104.01912)|[Multi-RIS](https://github.com/trinhudo/Multi-RIS)| -|[transfer learning based multi-objective evolutionary algorithm for community detection of dynamic complex networks](https://arxiv.org/abs/2109.15136)|[TMOGA](https://github.com/zjg540066169/TMOGA)| +|date|paper|code| +|---|---|---| diff --git a/archives/2021/11.md b/archives/2021/11.md index 1f72eeac..045bacc8 100644 --- a/archives/2021/11.md +++ b/archives/2021/11.md @@ -1,167 +1,117 @@ # November 2021 Archive ## 2021-11-30 -|paper|code| -|---|---| -|[iclabel: an automated electroencephalographic independent component classifier, dataset, and website](https://arxiv.org/abs/1901.07915)|[ICLabel-Train](https://github.com/lucapton/ICLabel-Train)| -|[visualization of linear operations in the spherical harmonics domain](https://arxiv.org/abs/2104.13069)|[visualization-of-sh-domain-operations](https://github.com/iksrwth/visualization-of-sh-domain-operations)| -|[opensync: an opensource platform for synchronizing multiple measures in neuroscience experiments](https://arxiv.org/abs/2107.14367)|[OpenSync_Unity](https://github.com/moeinrazavi/OpenSync_Unity)| -|[ncvx: a user-friendly and scalable package for nonconvex optimization in machine learning](https://arxiv.org/abs/2111.13984)|[ncvx](https://github.com/sun-umn/ncvx)| -|[neural computation of capacity region of memoryless multiple access channels](https://arxiv.org/abs/2105.04453)|[Neural-Capacity-Computation](https://github.com/Farhad-Mrkm/Neural-Capacity-Computation)| -|[redunet: a white-box deep network from the principle of maximizing rate reduction](https://arxiv.org/abs/2105.10446)|[ReduNet](https://github.com/Ma-Lab-Berkeley/ReduNet)| +|date|paper|code| +|---|---|---| +|2111.13984|[ncvx: a user-friendly and scalable package for nonconvex optimization in machine learning](https://arxiv.org/abs/2111.13984)|[ncvx](https://github.com/sun-umn/ncvx)| ## 2021-11-29 -|paper|code| -|---|---| -|[automatic crack classification by exploiting statistical event descriptors for deep learning](https://arxiv.org/abs/1907.10709)|[deeplearning_crack_classification](https://github.com/giuliosiracusano/deeplearning_crack_classification)| -|[contourletnet: a generalized rain removal architecture using multi-direction hierarchical representation](https://arxiv.org/abs/2111.12925)|[contourletnet-bmvc2021](https://github.com/cctakaet/contourletnet-bmvc2021)| -|[evaluation of interpretability for deep learning algorithms in eeg emotion recognition: a case study in autism](https://arxiv.org/abs/2111.13208)|[deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals](https://github.com/meiyor/deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals)| +|date|paper|code| +|---|---|---| +|2111.12925|[contourletnet: a generalized rain removal architecture using multi-direction hierarchical representation](https://arxiv.org/abs/2111.12925)|[contourletnet-bmvc2021](https://github.com/cctakaet/contourletnet-bmvc2021)| +|2111.13208|[evaluation of interpretability for deep learning algorithms in eeg emotion recognition: a case study in autism](https://arxiv.org/abs/2111.13208)|[deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals](https://github.com/meiyor/deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals)| ## 2021-11-25 -|paper|code| -|---|---| -|[point process simulation of generalised inverse gaussian processes and estimation of the jaeger integral](https://arxiv.org/abs/2105.09429)|[GiG](https://github.com/yamankindap/GiG)| -|[machine learning based forward solver: an automatic framework in gprmax](https://arxiv.org/abs/2111.12148)|[gprMax](https://github.com/utsav-akhaury/gprMax)| -|[tsflex: flexible time series processing & feature extraction](https://arxiv.org/abs/2111.12429)|[tsflex](https://github.com/predict-idlab/tsflex)| -|[state-space deep gaussian processes with applications](https://arxiv.org/abs/2111.12604)|[dissertation](https://github.com/zgbkdlm/dissertation)| -|[robust and differentially private mean estimation](https://arxiv.org/abs/2102.09159)|[robust_dp](https://github.com/xiyangl3/robust_dp)| +|date|paper|code| +|---|---|---| +|2111.12148|[machine learning based forward solver: an automatic framework in gprmax](https://arxiv.org/abs/2111.12148)|[gprMax](https://github.com/utsav-akhaury/gprMax)| +|2111.12429|[tsflex: flexible time series processing & feature extraction](https://arxiv.org/abs/2111.12429)|[tsflex](https://github.com/predict-idlab/tsflex)| +|2111.12604|[state-space deep gaussian processes with applications](https://arxiv.org/abs/2111.12604)|[dissertation](https://github.com/zgbkdlm/dissertation)| ## 2021-11-24 -|paper|code| -|---|---| -|[scaling and scalability: provable nonconvex low-rank tensor estimation from incomplete measurements](https://arxiv.org/abs/2104.14526)|[ScaledGD](https://github.com/Titan-Tong/ScaledGD)| -|[efficient hierarchical bayesian inference for spatio-temporal regression models in neuroimaging](https://arxiv.org/abs/2111.01692)|[dugh-neurips-2021](https://github.com/alihashemi-ai/dugh-neurips-2021)| -|[graph neural networks with parallel neighborhood aggregations for graph classification](https://arxiv.org/abs/2111.11482)|[spin](https://github.com/siddhant-doshi/spin)| +|date|paper|code| +|---|---|---| +|2111.01692|[efficient hierarchical bayesian inference for spatio-temporal regression models in neuroimaging](https://arxiv.org/abs/2111.01692)|[dugh-neurips-2021](https://github.com/alihashemi-ai/dugh-neurips-2021)| +|2111.11482|[graph neural networks with parallel neighborhood aggregations for graph classification](https://arxiv.org/abs/2111.11482)|[spin](https://github.com/siddhant-doshi/spin)| ## 2021-11-23 -|paper|code| -|---|---| -|[applications of unsupervised deep transfer learning to intelligent fault diagnosis: a survey and comparative study](https://arxiv.org/abs/1912.12528)|[UDTL](https://github.com/ZhaoZhibin/UDTL)| -|[neural capacity estimators: how reliable are they?](https://arxiv.org/abs/2111.07401)|[nce_icc-2022](https://github.com/farhad-mrkm/nce_icc-2022)| -|[semi-supervised impedance inversion by bayesian neural network based on 2-d cnn pre-training](https://arxiv.org/abs/2111.10596)|[bayesian-semi-supervised-impedance-inversion](https://github.com/tom-900/bayesian-semi-supervised-impedance-inversion)| -|[variational quantum gibbs state preparation with a truncated taylor series](https://arxiv.org/abs/2005.08797)|[Quantum](https://github.com/PaddlePaddle/Quantum)| +|date|paper|code| +|---|---|---| +|2111.07401|[neural capacity estimators: how reliable are they?](https://arxiv.org/abs/2111.07401)|[nce_icc-2022](https://github.com/farhad-mrkm/nce_icc-2022)| +|2111.10596|[semi-supervised impedance inversion by bayesian neural network based on 2-d cnn pre-training](https://arxiv.org/abs/2111.10596)|[bayesian-semi-supervised-impedance-inversion](https://github.com/tom-900/bayesian-semi-supervised-impedance-inversion)| ## 2021-11-22 -|paper|code| -|---|---| -|[a simulation-based end-to-end learning framework for evidential occupancy grid mapping](https://arxiv.org/abs/2102.12718)|[EviLOG](https://github.com/ika-rwth-aachen/EviLOG)| -|[beamforming using digital piezoelectric mems microphone array](https://arxiv.org/abs/2111.10087)|[vm3000-microphones](https://github.com/uwasystemhealth/vm3000-microphones)| -|[decoding supercodes of gabidulin codes and applications to cryptanalysis](https://arxiv.org/abs/2103.02700)|[Attack_on_LIGA](https://github.com/mbombar/Attack_on_LIGA)| -|[error coefficient-reduced polar/pac codes](https://arxiv.org/abs/2111.08843)|[Error-Coefficient-reduced-Polar-PAC-Codes](https://github.com/mohammad-rowshan/Error-Coefficient-reduced-Polar-PAC-Codes)| +|date|paper|code| +|---|---|---| +|2111.10087|[beamforming using digital piezoelectric mems microphone array](https://arxiv.org/abs/2111.10087)|[vm3000-microphones](https://github.com/uwasystemhealth/vm3000-microphones)| +|2111.08843|[error coefficient-reduced polar/pac codes](https://arxiv.org/abs/2111.08843)|[Error-Coefficient-reduced-Polar-PAC-Codes](https://github.com/mohammad-rowshan/Error-Coefficient-reduced-Polar-PAC-Codes)| ## 2021-11-19 -|paper|code| -|---|---| -|[deep reinforcement learning-designed radiofrequency waveform in mri](https://arxiv.org/abs/2105.03061)|[deeprf](https://github.com/snu-list/deeprf)| -|[integrating expert knowledge with domain adaptation for unsupervised fault diagnosis](https://arxiv.org/abs/2107.01849)|[syn2real](https://github.com/qinenergy/syn2real)| +|date|paper|code| +|---|---|---| ## 2021-11-18 -|paper|code| -|---|---| -|[lidar and position-aided mmwave beam selection with non-local cnns and curriculum training](https://arxiv.org/abs/2104.14579)|[LIDAR-mmWave-Beam-Selection](https://github.com/MatteoEURECOM/LIDAR-mmWave-Beam-Selection)| -|[deep learning based mac via joint channel access and rate adaptation](https://arxiv.org/abs/2106.10307)|[Wireless-Signal-Strength-on-2.4GHz-WSS24-dataset](https://github.com/postman511/Wireless-Signal-Strength-on-2.4GHz-WSS24-dataset)| +|date|paper|code| +|---|---|---| ## 2021-11-17 -|paper|code| -|---|---| -|[channel estimation and data detection analysis of massive mimo with 1-bit adcs](https://arxiv.org/abs/2102.10172)|[ch_est_data_det_1-bit](https://github.com/italo-atzeni/ch_est_data_det_1-bit)| -|[towards off-the-grid algorithms for total variation regularized inverse problems](https://arxiv.org/abs/2104.06706)|[tvsfw](https://github.com/rpetit/tvsfw)| -|[joint inference of multiple graphs with hidden variables from stationary graph signals](https://arxiv.org/abs/2110.03666)|[hidden_joint_inference](https://github.com/reysam93/hidden_joint_inference)| -|[r-local sensing: improved algorithm and applications](https://arxiv.org/abs/2110.14034)|[r-local-unlabeled-sensing](https://github.com/aabbas02/r-local-unlabeled-sensing)| -|[deep diffusion models for robust channel estimation](https://arxiv.org/abs/2111.08177)|[diffusion-channels](https://github.com/utcsilab/diffusion-channels)| +|date|paper|code| +|---|---|---| +|2111.08177|[deep diffusion models for robust channel estimation](https://arxiv.org/abs/2111.08177)|[diffusion-channels](https://github.com/utcsilab/diffusion-channels)| ## 2021-11-16 -|paper|code| -|---|---| -|[grassmannian optimization for online tensor completion and tracking with the t-svd](https://arxiv.org/abs/2001.11419)|[TOUCAN](https://github.com/kgilman/TOUCAN)| -|[electromagnetic model of reflective intelligent surfaces](https://arxiv.org/abs/2102.10666)|[Intelligent-Surfaces](https://github.com/MicheleBorgese/Intelligent-Surfaces)| -|[optimal power allocation in downlink multicarrier noma systems: theory and fast algorithms](https://arxiv.org/abs/2107.06678)|[optimal-power-allocation-in-downlink-noma.-sum-rate-and-energy-efficiency-maximization](https://gitlab.com/sepehrrezvani/optimal-power-allocation-in-downlink-noma.-sum-rate-and-energy-efficiency-maximization)| -|[delay-oriented distributed scheduling using graph neural networks](https://arxiv.org/abs/2111.07017)|[gcn-dql](https://github.com/zhongyuanzhao/gcn-dql)| -|[neural capacity estimators: how reliable are they?](https://arxiv.org/abs/2111.07401)|[nce_icc-2022](https://github.com/farhad-mrkm/nce_icc-2022)| -|[power allocation for wireless federated learning using graph neural networks](https://arxiv.org/abs/2111.07480)|[wirelessfl-pdgnet](https://github.com/bl166/wirelessfl-pdgnet)| -|[benefit of joint doa and delay estimation with application to indoor localization in wifi and 5g](https://arxiv.org/abs/1804.00486)|[jade](https://github.com/fwen/jade)| -|[categorical perception: a groundwork for deep learning](https://arxiv.org/abs/2012.05549)|[categorical_perception_ann_neco](https://github.com/l-bg/categorical_perception_ann_neco)| -|[quasifibrations of graphs to find symmetries in biological networks](https://arxiv.org/abs/2111.06999)|[qf](https://github.com/boldip/qf)| +|date|paper|code| +|---|---|---| +|2111.07017|[delay-oriented distributed scheduling using graph neural networks](https://arxiv.org/abs/2111.07017)|[gcn-dql](https://github.com/zhongyuanzhao/gcn-dql)| +|2111.07401|[neural capacity estimators: how reliable are they?](https://arxiv.org/abs/2111.07401)|[nce_icc-2022](https://github.com/farhad-mrkm/nce_icc-2022)| +|2111.07480|[power allocation for wireless federated learning using graph neural networks](https://arxiv.org/abs/2111.07480)|[wirelessfl-pdgnet](https://github.com/bl166/wirelessfl-pdgnet)| +|2111.06999|[quasifibrations of graphs to find symmetries in biological networks](https://arxiv.org/abs/2111.06999)|[qf](https://github.com/boldip/qf)| ## 2021-11-15 -|paper|code| -|---|---| -|[hlt-nus submission for 2020 nist conversational telephone speech sre](https://arxiv.org/abs/2111.06671)|[ecapatdnn](https://github.com/taoruijie/ecapatdnn)| +|date|paper|code| +|---|---|---| +|2111.06671|[hlt-nus submission for 2020 nist conversational telephone speech sre](https://arxiv.org/abs/2111.06671)|[ecapatdnn](https://github.com/taoruijie/ecapatdnn)| ## 2021-11-12 -|paper|code| -|---|---| -|[variational quantum algorithms for trace distance and fidelity estimation](https://arxiv.org/abs/2012.05768)|[Quantum](https://github.com/PaddlePaddle/Quantum)| +|date|paper|code| +|---|---|---| ## 2021-11-11 -|paper|code| -|---|---| -|[eegeyenet: a simultaneous electroencephalography and eye-tracking dataset and benchmark for eye movement prediction](https://arxiv.org/abs/2111.05100)|[eegeyenet](https://github.com/ardkastrati/eegeyenet)| -|[resnests and densenests: block-based dnn models with improved representation guarantees](https://arxiv.org/abs/2111.05496)|[resnest](https://github.com/kjason/resnest)| -|[neural distributed image compression using common information](https://arxiv.org/abs/2106.11723)|[NDIC](https://github.com/ipc-lab/NDIC)| +|date|paper|code| +|---|---|---| +|2111.05100|[eegeyenet: a simultaneous electroencephalography and eye-tracking dataset and benchmark for eye movement prediction](https://arxiv.org/abs/2111.05100)|[eegeyenet](https://github.com/ardkastrati/eegeyenet)| +|2111.05496|[resnests and densenests: block-based dnn models with improved representation guarantees](https://arxiv.org/abs/2111.05496)|[resnest](https://github.com/kjason/resnest)| ## 2021-11-10 -|paper|code| -|---|---| -|[lord-net: unfolded deep detection network with low-resolution receivers](https://arxiv.org/abs/2102.02993)|[LoRD-Net](https://github.com/skhobahi/LoRD-Net)| -|[proactive and aoi-aware failure recovery for stateful nfv-enabled zero-touch 6g networks: model-free drl approach](https://arxiv.org/abs/2103.03817)|[ZT-PFR](https://github.com/wildsky95/ZT-PFR)| -|[transfer bayesian meta-learning via weighted free energy minimization](https://arxiv.org/abs/2106.10711)|[meta_learning_pacoh](https://github.com/jonasrothfuss/meta_learning_pacoh)| -|[compressing sensor data for remote assistance of autonomous vehicles using deep generative models](https://arxiv.org/abs/2111.03201)|[deep_generative_models](https://github.com/daniel-bogdoll/deep_generative_models)| -|[phase retrieval using expectation consistent signal recovery algorithm based on hypernetwork](https://arxiv.org/abs/2101.04348)|[gec-sr-pr-hypernets](https://github.com/wangchangjen/gec-sr-pr-hypernets)| -|[can information flows suggest targets for interventions in neural circuits?](https://arxiv.org/abs/2111.05299)|[ann-info-flow](https://github.com/praveenv253/ann-info-flow)| +|date|paper|code| +|---|---|---| +|2111.03201|[compressing sensor data for remote assistance of autonomous vehicles using deep generative models](https://arxiv.org/abs/2111.03201)|[deep_generative_models](https://github.com/daniel-bogdoll/deep_generative_models)| +|2111.05299|[can information flows suggest targets for interventions in neural circuits?](https://arxiv.org/abs/2111.05299)|[ann-info-flow](https://github.com/praveenv253/ann-info-flow)| ## 2021-11-09 -|paper|code| -|---|---| -|[estimating the magnitude and phase of automotive radar signals under multiple interference sources with fully convolutional networks](https://arxiv.org/abs/2008.05948)|[arim-v2](https://github.com/ristea/arim-v2)| -|[homological time series analysis of sensor signals from power plants](https://arxiv.org/abs/2106.02493)|[TwirlFlake](https://github.com/karhunenloeve/TwirlFlake)| -|[learning sparse analytic filters for piano transcription](https://arxiv.org/abs/2108.10382)|[sparse-analytic-filters](https://github.com/cwitkowitz/sparse-analytic-filters)| -|[rf-net: a unified meta-learning framework for rf-enabled one-shot human activity recognition](https://arxiv.org/abs/2111.04566)|[rfnet](https://github.com/di0002ya/rfnet)| -|[frequency-dependent $f$-number increases the contrast and the spatial resolution in fast pulse-echo ultrasound imaging](https://arxiv.org/abs/2111.04593)|[f_number](https://github.com/mschiffn/f_number)| -|[linguistic dependencies and statistical dependence](https://arxiv.org/abs/2104.08685)|[cpmi-dependencies](https://github.com/mcqll/cpmi-dependencies)| -|[a space of goals: the cognitive geometry of informationally bounded agents](https://arxiv.org/abs/2111.03699)|[cognitive-geometry](https://gitlab.com/uh-adapsys/cognitive-geometry)| -|[geodesic curves in gaussian random field manifolds](https://arxiv.org/abs/2111.03905)|[rk4_geodesic_gmrf](https://github.com/alexandrelevada/rk4_geodesic_gmrf)| +|date|paper|code| +|---|---|---| +|2111.04566|[rf-net: a unified meta-learning framework for rf-enabled one-shot human activity recognition](https://arxiv.org/abs/2111.04566)|[rfnet](https://github.com/di0002ya/rfnet)| +|2111.04593|[frequency-dependent $f$-number increases the contrast and the spatial resolution in fast pulse-echo ultrasound imaging](https://arxiv.org/abs/2111.04593)|[f_number](https://github.com/mschiffn/f_number)| +|2111.03699|[a space of goals: the cognitive geometry of informationally bounded agents](https://arxiv.org/abs/2111.03699)|[cognitive-geometry](https://gitlab.com/uh-adapsys/cognitive-geometry)| +|2111.03905|[geodesic curves in gaussian random field manifolds](https://arxiv.org/abs/2111.03905)|[rk4_geodesic_gmrf](https://github.com/alexandrelevada/rk4_geodesic_gmrf)| ## 2021-11-08 -|paper|code| -|---|---| -|[correlation-aware cooperative multigroup broadcast 360{\deg} video delivery network: a hierarchical deep reinforcement learning approach](https://arxiv.org/abs/2010.11347)|[Hierarchical-Multi-agent-DRL-with-Federated-Learning](https://github.com/paperflight/Hierarchical-Multi-agent-DRL-with-Federated-Learning)| -|[scalable perception-action-communication loops with convolutional and graph neural networks](https://arxiv.org/abs/2106.13358)|[VGAI](https://github.com/VITA-Group/VGAI)| -|[scalable multi-agent reinforcement learning algorithm for wireless networks](https://arxiv.org/abs/2108.00506)|[Fed-MF-MAL](https://github.com/paperflight/Fed-MF-MAL)| -|[millimeter wave wireless assisted robot navigation with link state classification](https://arxiv.org/abs/2110.14789)|[mmwRobotNav](https://github.com/nyu-wireless/mmwRobotNav)| -|[deep-learning based linear precoding for mimo channels with finite-alphabet signaling](https://arxiv.org/abs/2111.03504)|[optimalprecodingmimo](https://github.com/girnyk/optimalprecodingmimo)| +|date|paper|code| +|---|---|---| +|2111.03504|[deep-learning based linear precoding for mimo channels with finite-alphabet signaling](https://arxiv.org/abs/2111.03504)|[optimalprecodingmimo](https://github.com/girnyk/optimalprecodingmimo)| ## 2021-11-05 -|paper|code| -|---|---| -|[maus: a dataset for mental workload assessmenton n-back task using wearable sensor](https://arxiv.org/abs/2111.02561)|[MAUS_dataset_baseline_system](https://github.com/rickwu11/MAUS_dataset_baseline_system)| -|[on the distribution of the information density of gaussian random vectors: explicit formulas and tight approximations](https://arxiv.org/abs/2105.03925)|[information-density](https://gitlab.com/infth/information-density)| -|[partition and code: learning how to compress graphs](https://arxiv.org/abs/2107.01952)|[PnC](https://github.com/gbouritsas/PnC)| +|date|paper|code| +|---|---|---| +|2111.02561|[maus: a dataset for mental workload assessmenton n-back task using wearable sensor](https://arxiv.org/abs/2111.02561)|[MAUS_dataset_baseline_system](https://github.com/rickwu11/MAUS_dataset_baseline_system)| ## 2021-11-04 -|paper|code| -|---|---| -|[diagnosis of intelligent reflecting surface in millimeter-wave communication systems](https://arxiv.org/abs/2101.03792)|[IRSdiagnosis](https://github.com/DestinationSR/IRSdiagnosis)| +|date|paper|code| +|---|---|---| ## 2021-11-03 -|paper|code| -|---|---| -|[a machine-learning-based direction-of-origin filter for the identification of radio frequency interference in the search for technosignatures](https://arxiv.org/abs/2108.00559)|[doom](https://github.com/UCLA-SETI-Group/doom)| -|[efficient hierarchical bayesian inference for spatio-temporal regression models in neuroimaging](https://arxiv.org/abs/2111.01692)|[dugh-neurips-2021](https://github.com/alihashemi-ai/dugh-neurips-2021)| +|date|paper|code| +|---|---|---| +|2111.01692|[efficient hierarchical bayesian inference for spatio-temporal regression models in neuroimaging](https://arxiv.org/abs/2111.01692)|[dugh-neurips-2021](https://github.com/alihashemi-ai/dugh-neurips-2021)| ## 2021-11-02 -|paper|code| -|---|---| -|[complex convolutional neural networks for ultrafast ultrasound image reconstruction from in-phase/quadrature signal](https://arxiv.org/abs/2009.11536)|[cid-net](https://github.com/jingfeng-lu/cid-net)| -|[unique sparse decomposition of low rank matrices](https://arxiv.org/abs/2106.07736)|[Unique_Fac_of_Low_Rank](https://github.com/Jindiande/Unique_Fac_of_Low_Rank)| -|[a novel 1d state space for efficient music rhythmic analysis](https://arxiv.org/abs/2111.00704)|[1d-statespace](https://github.com/mjhydri/1d-statespace)| -|[an information-theoretic approach to distribution shifts](https://arxiv.org/abs/2106.03783)|[dsit](https://github.com/mfederici/dsit)| -|[heterogeneous multi-player multi-armed bandits: closing the gap and generalization](https://arxiv.org/abs/2110.14622)|[mpmab_beacon](https://github.com/shengroup/mpmab_beacon)| -|[generalized data weighting via class-level gradient manipulation](https://arxiv.org/abs/2111.00056)|[gdw-nips2021](https://github.com/ggchen1997/gdw-nips2021)| +|date|paper|code| +|---|---|---| +|2111.00704|[a novel 1d state space for efficient music rhythmic analysis](https://arxiv.org/abs/2111.00704)|[1d-statespace](https://github.com/mjhydri/1d-statespace)| +|2111.00056|[generalized data weighting via class-level gradient manipulation](https://arxiv.org/abs/2111.00056)|[gdw-nips2021](https://github.com/ggchen1997/gdw-nips2021)| ## 2021-11-01 -|paper|code| -|---|---| -|[channel estimation and data detection analysis of massive mimo with 1-bit adcs](https://arxiv.org/abs/2102.10172)|[ch_est_data_det_1-bit](https://github.com/italo-atzeni/ch_est_data_det_1-bit)| -|[ecg-based heart arrhythmia diagnosis through attentional convolutional neural networks](https://arxiv.org/abs/2108.10226)|[heart-arrhythmia-diagnosis-with-deep-learning](https://github.com/ziyuliu-lion/heart-arrhythmia-diagnosis-with-deep-learning)| +|date|paper|code| +|---|---|---| diff --git a/archives/2021/12.md b/archives/2021/12.md index dfadcfb6..7afc6adf 100644 --- a/archives/2021/12.md +++ b/archives/2021/12.md @@ -1,140 +1,100 @@ # December 2021 Archive ## 2021-12-30 -|paper|code| -|---|---| -|[towards real-world bci: ccspnet, a compact subject-independent motor imagery framework](https://arxiv.org/abs/2012.13567)|[CCSPNet](https://github.com/Singular-Brain/CCSPNet)| -|[decentralized power allocation for mimo-noma vehicular edge computing based on deep reinforcement learning](https://arxiv.org/abs/2107.14772)|[VEC_DRL_Doppler](https://github.com/qiongwu86/VEC_DRL_Doppler)| -|[regularity normalization: neuroscience-inspired unsupervised attention across neural network layers](https://arxiv.org/abs/1902.10658)|[UnsupervisedAttentionMechanism](https://github.com/doerlbh/UnsupervisedAttentionMechanism)| +|date|paper|code| +|---|---|---| ## 2021-12-28 -|paper|code| -|---|---| -|[hardware distortion correlation has negligible impact on ul massive mimo spectral efficiency](https://arxiv.org/abs/1811.02007)|[distortion-correlation](https://github.com/emilbjornson/distortion-correlation)| -|[variational quantum algorithms for trace distance and fidelity estimation](https://arxiv.org/abs/2012.05768)|[Quantum](https://github.com/PaddlePaddle/Quantum)| -|[practical distributed quantum information processing with loccnet](https://arxiv.org/abs/2101.12190)|[Quantum](https://github.com/PaddlePaddle/Quantum)| +|date|paper|code| +|---|---|---| ## 2021-12-24 -|paper|code| -|---|---| -|[a machine-learning-based direction-of-origin filter for the identification of radio frequency interference in the search for technosignatures](https://arxiv.org/abs/2108.00559)|[doom](https://github.com/UCLA-SETI-Group/doom)| -|[new instances of quadratic apn functions](https://arxiv.org/abs/2009.07204)|[quadratic_apn](https://github.com/cbe90/quadratic_apn)| +|date|paper|code| +|---|---|---| ## 2021-12-23 -|paper|code| -|---|---| -|[tsflex: flexible time series processing & feature extraction](https://arxiv.org/abs/2111.12429)|[tsflex](https://github.com/predict-idlab/tsflex)| +|date|paper|code| +|---|---|---| ## 2021-12-22 -|paper|code| -|---|---| -|[unique sparse decomposition of low rank matrices](https://arxiv.org/abs/2106.07736)|[Unique_Fac_of_Low_Rank](https://github.com/Jindiande/Unique_Fac_of_Low_Rank)| -|[subject-independent drowsiness recognition from single-channel eeg with an interpretable cnn-lstm model](https://arxiv.org/abs/2112.10894)|[Subject-Independent-Drowsiness-Recognition-from-Single-Channel-EEG-with-an-Interpretable-CNN-LSTM](https://github.com/cuijiancorbin/Subject-Independent-Drowsiness-Recognition-from-Single-Channel-EEG-with-an-Interpretable-CNN-LSTM)| -|[multiple time series fusion based on lstm an application to cap a phase classification using eeg](https://arxiv.org/abs/2112.11218)|[GA_PSO_DEEP_LEARNING](https://github.com/Dntfreitas/GA_PSO_DEEP_LEARNING)| +|date|paper|code| +|---|---|---| +|2112.10894|[subject-independent drowsiness recognition from single-channel eeg with an interpretable cnn-lstm model](https://arxiv.org/abs/2112.10894)|[Subject-Independent-Drowsiness-Recognition-from-Single-Channel-EEG-with-an-Interpretable-CNN-LSTM](https://github.com/cuijiancorbin/Subject-Independent-Drowsiness-Recognition-from-Single-Channel-EEG-with-an-Interpretable-CNN-LSTM)| +|2112.11218|[multiple time series fusion based on lstm an application to cap a phase classification using eeg](https://arxiv.org/abs/2112.11218)|[GA_PSO_DEEP_LEARNING](https://github.com/Dntfreitas/GA_PSO_DEEP_LEARNING)| ## 2021-12-21 -|paper|code| -|---|---| -|[expression is enough: improving traffic signal control with advanced traffic state representation](https://arxiv.org/abs/2112.10107)|[Advanced_XLight](https://github.com/LiangZhang1996/Advanced_XLight)| +|date|paper|code| +|---|---|---| +|2112.10107|[expression is enough: improving traffic signal control with advanced traffic state representation](https://arxiv.org/abs/2112.10107)|[Advanced_XLight](https://github.com/LiangZhang1996/Advanced_XLight)| ## 2021-12-20 -|paper|code| -|---|---| -|[detection of maternal and fetal stress from the electrocardiogram with self-supervised representation learning](https://arxiv.org/abs/2011.02000)|[ssl-ecg-v2](https://github.com/pritamqu/ssl-ecg-v2)| -|[systematic assessment of hyperdimensional computing for epileptic seizure detection](https://arxiv.org/abs/2105.00934)|[HDforEpilepsyPublic](https://c4science.ch/source/HDforEpilepsyPublic)| +|date|paper|code| +|---|---|---| ## 2021-12-17 -|paper|code| -|---|---| -|[search for temporal cell segmentation robustness in phase-contrast microscopy videos](https://arxiv.org/abs/2112.08817)|[microscopy-dl-suite-tf](https://github.com/esgomezm/microscopy-dl-suite-tf)| -|[a deep learning based multitask network for respiration rate estimation -- a practical perspective](https://arxiv.org/abs/2112.09071)|[multirespdl](https://github.com/acrophase/multirespdl)| +|date|paper|code| +|---|---|---| +|2112.08817|[search for temporal cell segmentation robustness in phase-contrast microscopy videos](https://arxiv.org/abs/2112.08817)|[microscopy-dl-suite-tf](https://github.com/esgomezm/microscopy-dl-suite-tf)| +|2112.09071|[a deep learning based multitask network for respiration rate estimation -- a practical perspective](https://arxiv.org/abs/2112.09071)|[multirespdl](https://github.com/acrophase/multirespdl)| ## 2021-12-16 -|paper|code| -|---|---| -|[denoising noisy neural networks: a bayesian approach with compensation](https://arxiv.org/abs/2105.10699)|[NoisyNN](https://github.com/lynshao/NoisyNN)| +|date|paper|code| +|---|---|---| ## 2021-12-15 -|paper|code| -|---|---| -|[early stopping for deep image prior](https://arxiv.org/abs/2112.06074)|[early_stopping_for_dip](https://github.com/sun-umn/early_stopping_for_dip)| -|[a deep knowledge distillation framework for eeg assisted enhancement of single-lead ecg based sleep staging](https://arxiv.org/abs/2112.07252)|[sleep_staging_kd](https://github.com/acrophase/sleep_staging_kd)| +|date|paper|code| +|---|---|---| +|2112.06074|[early stopping for deep image prior](https://arxiv.org/abs/2112.06074)|[early_stopping_for_dip](https://github.com/sun-umn/early_stopping_for_dip)| +|2112.07252|[a deep knowledge distillation framework for eeg assisted enhancement of single-lead ecg based sleep staging](https://arxiv.org/abs/2112.07252)|[sleep_staging_kd](https://github.com/acrophase/sleep_staging_kd)| ## 2021-12-14 -|paper|code| -|---|---| -|[tree-amp: compositional inference with tree approximate message passing](https://arxiv.org/abs/2004.01571)|[tramp](https://github.com/sphinxteam/tramp)| -|[chmusic: a traditional chinese music dataset for evaluation of instrument recognition](https://arxiv.org/abs/2108.08470)|[chmusic](https://github.com/haoranweiutd/chmusic)| -|[multi-static uwb radar-based passive human tracking using cots devices](https://arxiv.org/abs/2109.12856)|[uwb-radar-pedestrian-tracking](https://github.com/clongli/uwb-radar-pedestrian-tracking)| -|[recovery of future data via convolution nuclear norm minimization](https://arxiv.org/abs/1909.03889)|[CNNM](https://github.com/gcliu1982/CNNM)| +|date|paper|code| +|---|---|---| ## 2021-12-13 -|paper|code| -|---|---| -|[removing noise from extracellular neural recordings using fully convolutional denoising autoencoders](https://arxiv.org/abs/2109.08945)|[fcdae-neural-signal-denoising](https://github.com/alexdelitzas/fcdae-neural-signal-denoising)| -|[deepaoanet: learning angle of arrival from software defined radios with deep neural networks](https://arxiv.org/abs/2112.00695)|[deepaoanet](https://github.com/zdai257/deepaoanet)| -|[surrogate-based cross-correlation for particle image velocimetry](https://arxiv.org/abs/2112.05303)|[sbcc](https://github.com/yongleex/sbcc)| +|date|paper|code| +|---|---|---| +|2112.00695|[deepaoanet: learning angle of arrival from software defined radios with deep neural networks](https://arxiv.org/abs/2112.00695)|[deepaoanet](https://github.com/zdai257/deepaoanet)| +|2112.05303|[surrogate-based cross-correlation for particle image velocimetry](https://arxiv.org/abs/2112.05303)|[sbcc](https://github.com/yongleex/sbcc)| ## 2021-12-10 -|paper|code| -|---|---| -|[open community platform for hearing aid algorithm research: open master hearing aid (openmha)](https://arxiv.org/abs/2103.02313)|[openMHA](https://github.com/HoerTech-gGmbH/openMHA)| -|[scalable power control/beamforming in heterogeneous wireless networks with graph neural networks](https://arxiv.org/abs/2104.05463)|[hignn](https://github.com/zhangxiaochen95/hignn)| -|[a unifying theory of thompson sampling for continuous risk-averse bandits](https://arxiv.org/abs/2108.11345)|[continuous-rho-ts](https://github.com/joel-ql-chang/continuous-rho-ts)| +|date|paper|code| +|---|---|---| ## 2021-12-09 -|paper|code| -|---|---| -|[a primer on near-field beamforming for arrays and reconfigurable intelligent surfaces](https://arxiv.org/abs/2110.06661)|[nearfield-primer](https://github.com/emilbjornson/nearfield-primer)| -|[mobile bci dataset of scalp- and ear-eegs with erp and ssvep paradigms while standing, walking, and running](https://arxiv.org/abs/2112.04176)|[mobilebci_data](https://github.com/youngeun1209/mobilebci_data)| -|[adaptive r-peak detection on wearable ecg sensors for high-intensity exercise](https://arxiv.org/abs/2112.04369)|[adaptive_rpeak_det_public](https://c4science.ch/source/adaptive_rpeak_det_public)| -|[adaboost and robust one-bit compressed sensing](https://arxiv.org/abs/2105.02083)|[adaboost-and-robust-one-bit-compressed-sensing](https://github.com/felix-127/adaboost-and-robust-one-bit-compressed-sensing)| +|date|paper|code| +|---|---|---| +|2112.04176|[mobile bci dataset of scalp- and ear-eegs with erp and ssvep paradigms while standing, walking, and running](https://arxiv.org/abs/2112.04176)|[mobilebci_data](https://github.com/youngeun1209/mobilebci_data)| +|2112.04369|[adaptive r-peak detection on wearable ecg sensors for high-intensity exercise](https://arxiv.org/abs/2112.04369)|[adaptive_rpeak_det_public](https://c4science.ch/source/adaptive_rpeak_det_public)| ## 2021-12-08 -|paper|code| -|---|---| -|[the elliptical ornstein-uhlenbeck process](https://arxiv.org/abs/2001.05965)|[ellipticalou](https://github.com/adamsykulski/ellipticalou)| -|[truly shift-equivariant convolutional neural networks with adaptive polyphase upsampling](https://arxiv.org/abs/2105.04040)|[truly_shift_invariant_cnns](https://github.com/achaman2/truly_shift_invariant_cnns)| -|[vehif: an accessible vegetation high-impedance fault data set format](https://arxiv.org/abs/2112.03651)|[hif_vegetation_data](https://github.com/dougpsg/hif_vegetation_data)| +|date|paper|code| +|---|---|---| +|2112.03651|[vehif: an accessible vegetation high-impedance fault data set format](https://arxiv.org/abs/2112.03651)|[hif_vegetation_data](https://github.com/dougpsg/hif_vegetation_data)| ## 2021-12-07 -|paper|code| -|---|---| -|[eeg-based emotional video classification via learning connectivity structure](https://arxiv.org/abs/1905.11678)|[bsc_lcs](https://github.com/ELEMKEP/bsc_lcs)| -|[estimating the electrical power output of industrial devices with end-to-end time-series classification in the presence of label noise](https://arxiv.org/abs/2105.00349)|[SREA](https://github.com/Castel44/SREA)| -|[under the sand: navigation and localization of a micro aerial vehicle for landmine detection with ground penetrating synthetic aperture radar](https://arxiv.org/abs/2106.10108)|[mav_findmine](https://github.com/ethz-asl/mav_findmine)| -|[my(o) armband leaks passwords: an emg and imu based keylogging side-channel attack](https://arxiv.org/abs/2112.02382)|[myo-keylogging](https://github.com/seemoo-lab/myo-keylogging)| -|[enhancement of a state-of-the-art rl-based detection algorithm for massive mimo radars](https://arxiv.org/abs/2112.02628)|[improved_rl_algorithm_mmimo_radar](https://github.com/lisifra96/improved_rl_algorithm_mmimo_radar)| -|[robust compressed sensing mri with deep generative priors](https://arxiv.org/abs/2108.01368)|[csgm-mri-langevin](https://github.com/utcsilab/csgm-mri-langevin)| -|[compressive visual representations](https://arxiv.org/abs/2109.12909)|[compressive-visual-representations](https://github.com/google-research/compressive-visual-representations)| +|date|paper|code| +|---|---|---| +|2112.02382|[my(o) armband leaks passwords: an emg and imu based keylogging side-channel attack](https://arxiv.org/abs/2112.02382)|[myo-keylogging](https://github.com/seemoo-lab/myo-keylogging)| +|2112.02628|[enhancement of a state-of-the-art rl-based detection algorithm for massive mimo radars](https://arxiv.org/abs/2112.02628)|[improved_rl_algorithm_mmimo_radar](https://github.com/lisifra96/improved_rl_algorithm_mmimo_radar)| ## 2021-12-06 -|paper|code| -|---|---| -|[irs-aided swipt: joint waveform, active and passive beamforming design under nonlinear harvester model](https://arxiv.org/abs/2012.05646)|[irs-aided-swipt-joint-waveform-active-and-passive-beamforming-design-under-nonlinear-harvester-model](https://github.com/snowztail/irs-aided-swipt-joint-waveform-active-and-passive-beamforming-design-under-nonlinear-harvester-model)| -|[stride: a flexible platform for high-performance ultrasound computed tomography](https://arxiv.org/abs/2110.03345)|[stride](https://github.com/trustimaging/stride)| -|[disentangling modes with crossover instantaneous frequencies by synchrosqueezed chirplet transforms, from theory to application](https://arxiv.org/abs/2112.01857)|[synchrosqueezed-chirplet-transforms](https://github.com/ziyuchen7/synchrosqueezed-chirplet-transforms)| +|date|paper|code| +|---|---|---| +|2112.01857|[disentangling modes with crossover instantaneous frequencies by synchrosqueezed chirplet transforms, from theory to application](https://arxiv.org/abs/2112.01857)|[synchrosqueezed-chirplet-transforms](https://github.com/ziyuchen7/synchrosqueezed-chirplet-transforms)| ## 2021-12-03 -|paper|code| -|---|---| -|[self-supervised graph representation learning via topology transformations](https://arxiv.org/abs/2105.11689)|[topo-ter](https://github.com/gyshgx868/topo-ter)| -|[embedding decomposition for artifacts removal in eeg signals](https://arxiv.org/abs/2112.00989)|[deepseparator](https://github.com/ncclabsustech/deepseparator)| -|[quantum advantage in learning from experiments](https://arxiv.org/abs/2112.00778)|[ReCirq](https://github.com/quantumlib/ReCirq)| +|date|paper|code| +|---|---|---| +|2112.00989|[embedding decomposition for artifacts removal in eeg signals](https://arxiv.org/abs/2112.00989)|[deepseparator](https://github.com/ncclabsustech/deepseparator)| +|2112.00778|[quantum advantage in learning from experiments](https://arxiv.org/abs/2112.00778)|[ReCirq](https://github.com/quantumlib/ReCirq)| ## 2021-12-02 -|paper|code| -|---|---| -|[localized fourier analysis for graph signal processing](https://arxiv.org/abs/1906.04529)|[loclets](https://bitbucket.org/batistbucket/loclets)| -|[heppcat: probabilistic pca for data with heteroscedastic noise](https://arxiv.org/abs/2101.03468)|[heteroscedastic-probabilistic-pca](https://gitlab.com/heppcat-group/heteroscedastic-probabilistic-pca)| -|[hottbox: higher order tensor toolbox](https://arxiv.org/abs/2111.15662)|[hottbox](https://github.com/hottbox/hottbox)| -|[deepaoanet: learning angle of arrival from software defined radios with deep neural networks](https://arxiv.org/abs/2112.00695)|[deepaoanet](https://github.com/zdai257/deepaoanet)| +|date|paper|code| +|---|---|---| +|2112.00695|[deepaoanet: learning angle of arrival from software defined radios with deep neural networks](https://arxiv.org/abs/2112.00695)|[deepaoanet](https://github.com/zdai257/deepaoanet)| ## 2021-12-01 -|paper|code| -|---|---| -|[validating circacp: a generic sleep-wake cycle detection algorithm](https://arxiv.org/abs/2111.14960)|[circacp](https://github.com/shanshanchen-biostat/circacp)| -|[clustering-based activity detection algorithms for grant-free random access in cell-free massive mimo](https://arxiv.org/abs/2111.15378)|[grant-free](https://github.com/emilbjornson/grant-free)| -|[scalable machine learning architecture for neonatal seizure detection on ultra-edge devices](https://arxiv.org/abs/2111.15569)|[NeonatalSeizureDetection](https://github.com/vishaln15/NeonatalSeizureDetection)| -|[mathematical models for fake news](https://arxiv.org/abs/1809.00964)|[Fake_News](https://github.com/dmmeier/Fake_News)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/01.md b/archives/2022/01.md index ec15cd99..9119c950 100644 --- a/archives/2022/01.md +++ b/archives/2022/01.md @@ -1,121 +1,87 @@ # January 2022 Archive ## 2022-01-31 -|paper|code| -|---|---| -|[quantification of mismatch error in randomly switching linear state-space models](https://arxiv.org/abs/2012.04542)|[Switching-Kalman-Filter](https://github.com/ParissKK/Switching-Kalman-Filter)| -|[a tutorial on generalized eigendecomposition for denoising, contrast enhancement, and dimension reduction in multichannel electrophysiology](https://arxiv.org/abs/2104.12356)|[GED_tutorial](https://github.com/mikexcohen/GED_tutorial)| -|[inertial navigation using an inertial sensor array](https://arxiv.org/abs/2201.11983)|[array-in](https://github.com/hcarlsso/array-in)| -|[stochastic optimization in digital pre-distortion of the signal](https://arxiv.org/abs/2201.12159)|[Sirius-2021-DPD-optimization](https://github.com/dmivilensky/Sirius-2021-DPD-optimization)| -|[lossy compression for lossless prediction](https://arxiv.org/abs/2106.10800)|[lossyless](https://github.com/YannDubs/lossyless)| +|date|paper|code| +|---|---|---| +|2201.11983|[inertial navigation using an inertial sensor array](https://arxiv.org/abs/2201.11983)|[array-in](https://github.com/hcarlsso/array-in)| +|2201.12159|[stochastic optimization in digital pre-distortion of the signal](https://arxiv.org/abs/2201.12159)|[Sirius-2021-DPD-optimization](https://github.com/dmivilensky/Sirius-2021-DPD-optimization)| ## 2022-01-28 -|paper|code| -|---|---| -|[calibration with privacy in peer review](https://arxiv.org/abs/2201.11308)|[calibration-with-privacy-in-peer-review](https://github.com/wenxind/calibration-with-privacy-in-peer-review)| +|date|paper|code| +|---|---|---| +|2201.11308|[calibration with privacy in peer review](https://arxiv.org/abs/2201.11308)|[calibration-with-privacy-in-peer-review](https://github.com/wenxind/calibration-with-privacy-in-peer-review)| ## 2022-01-27 -|paper|code| -|---|---| -|[grouped variable selection for generalized eigenvalue problems](https://arxiv.org/abs/2105.13667)|[benchmarkStudySensorSelection](https://github.com/AlexanderBertrandLab/benchmarkStudySensorSelection)| +|date|paper|code| +|---|---|---| ## 2022-01-26 -|paper|code| -|---|---| -|[low complexity channel estimation with neural network solutions](https://arxiv.org/abs/2201.09934)|[Interpolation-ResNet](https://github.com/dianixn/Interpolation-ResNet)| -|[neural architecture search for spiking neural networks](https://arxiv.org/abs/2201.10355)|[neural-architecture-search-for-spiking-neural-networks](https://github.com/intelligent-computing-lab-yale/neural-architecture-search-for-spiking-neural-networks)| +|date|paper|code| +|---|---|---| +|2201.09934|[low complexity channel estimation with neural network solutions](https://arxiv.org/abs/2201.09934)|[Interpolation-ResNet](https://github.com/dianixn/Interpolation-ResNet)| +|2201.10355|[neural architecture search for spiking neural networks](https://arxiv.org/abs/2201.10355)|[neural-architecture-search-for-spiking-neural-networks](https://github.com/intelligent-computing-lab-yale/neural-architecture-search-for-spiking-neural-networks)| ## 2022-01-25 -|paper|code| -|---|---| -|[open community platform for hearing aid algorithm research: open master hearing aid (openmha)](https://arxiv.org/abs/2103.02313)|[softx-d-21-00049](https://github.com/elseviersoftwarex/softx-d-21-00049)| -|[kalmannet: neural network aided kalman filtering for partially known dynamics](https://arxiv.org/abs/2107.10043)|[KalmanNet_TSP](https://github.com/KalmanNet/KalmanNet_TSP)| -|[a new non-negative matrix co-factorisation approach for noisy neonatal chest sound separation](https://arxiv.org/abs/2109.03275)|[heart-and-lung-sound-separation](https://github.com/egrooby-monash/heart-and-lung-sound-separation)| -|[real-time multi-level neonatal heart and lung sound quality assessment for telehealth applications](https://arxiv.org/abs/2109.15127)|[heart-and-lung-signal-quality-estimation](https://github.com/egrooby-monash/heart-and-lung-signal-quality-estimation)| -|[decoding reed-muller codes with successive codeword permutations](https://arxiv.org/abs/2109.02122)|[SPRLD](https://github.com/nghiadt05/SPRLD)| -|[an unsupervised deep unrolling framework for constrained optimization problems in wireless networks](https://arxiv.org/abs/2201.08994)|[usrmnet-hwgcn](https://github.com/soulven/usrmnet-hwgcn)| +|date|paper|code| +|---|---|---| +|2201.08994|[an unsupervised deep unrolling framework for constrained optimization problems in wireless networks](https://arxiv.org/abs/2201.08994)|[usrmnet-hwgcn](https://github.com/soulven/usrmnet-hwgcn)| ## 2022-01-20 -|paper|code| -|---|---| -|[homological time series analysis of sensor signals from power plants](https://arxiv.org/abs/2106.02493)|[TwirlFlake](https://github.com/karhunenloeve/TwirlFlake)| +|date|paper|code| +|---|---|---| ## 2022-01-19 -|paper|code| -|---|---| -|[two-dimensional multi-target detection: an autocorrelation analysis approach](https://arxiv.org/abs/2105.06765)|[MTD-2D](https://github.com/krshay/MTD-2D)| -|[optimal power allocation in downlink multicarrier noma systems: theory and fast algorithms](https://arxiv.org/abs/2107.06678)|[optimal-power-allocation-in-downlink-noma.-sum-rate-and-energy-efficiency-maximization](https://gitlab.com/sepehrrezvani/optimal-power-allocation-in-downlink-noma.-sum-rate-and-energy-efficiency-maximization)| -|[resnests and densenests: block-based dnn models with improved representation guarantees](https://arxiv.org/abs/2111.05496)|[resnest](https://github.com/kjason/resnest)| -|[visual sensor network stimulation model identification via gaussian mixture model and deep embedded features](https://arxiv.org/abs/2201.06804)|[vsn-with-ae](https://github.com/luca-varotto/vsn-with-ae)| -|[sending timely status updates through channel with random delay via online learning](https://arxiv.org/abs/2112.10400)|[infocom2022](https://github.com/loveisbasa/infocom2022)| +|date|paper|code| +|---|---|---| +|2201.06804|[visual sensor network stimulation model identification via gaussian mixture model and deep embedded features](https://arxiv.org/abs/2201.06804)|[vsn-with-ae](https://github.com/luca-varotto/vsn-with-ae)| ## 2022-01-14 -|paper|code| -|---|---| -|[spectrum surveying: active radio map estimation with autonomous uavs](https://arxiv.org/abs/2201.04125)|[spectrum_surveying_with_uavs](https://github.com/uiano/spectrum_surveying_with_uavs)| -|[performance analysis of multi-user noma wireless-powered mmtc networks: a stochastic geometry approach](https://arxiv.org/abs/2201.04784)|[mmtc-noma](https://github.com/thanhluannguyen/mmtc-noma)| +|date|paper|code| +|---|---|---| +|2201.04125|[spectrum surveying: active radio map estimation with autonomous uavs](https://arxiv.org/abs/2201.04125)|[spectrum_surveying_with_uavs](https://github.com/uiano/spectrum_surveying_with_uavs)| +|2201.04784|[performance analysis of multi-user noma wireless-powered mmtc networks: a stochastic geometry approach](https://arxiv.org/abs/2201.04784)|[mmtc-noma](https://github.com/thanhluannguyen/mmtc-noma)| ## 2022-01-13 -|paper|code| -|---|---| -|[how to find a unicorn: a novel model-free, unsupervised anomaly detection method for time series](https://arxiv.org/abs/2004.11468)|[uniqed](https://github.com/phrenico/uniqed)| -|[federated learning for covid-19 detection with generative adversarial networks in edge cloud computing](https://arxiv.org/abs/2110.07136)|[FL-GAN_COVID](https://github.com/dinhgit/FL-GAN_COVID)| -|[implementation of fgpa based channel sounder for large scale antenna systems using rfnoc on usrp platform](https://arxiv.org/abs/2201.04471)|[rfnoc-hls-winlab](https://github.com/xilinx/rfnoc-hls-winlab)| +|date|paper|code| +|---|---|---| +|2201.04471|[implementation of fgpa based channel sounder for large scale antenna systems using rfnoc on usrp platform](https://arxiv.org/abs/2201.04471)|[rfnoc-hls-winlab](https://github.com/xilinx/rfnoc-hls-winlab)| ## 2022-01-12 -|paper|code| -|---|---| -|[rnns on monitoring physical activity energy expenditure in older people](https://arxiv.org/abs/2006.01169)|[GOTOV_PAEE_publication](https://github.com/parastelios/GOTOV_PAEE_publication)| -|[evaluation of interpretability for deep learning algorithms in eeg emotion recognition: a case study in autism](https://arxiv.org/abs/2111.13208)|[deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals](https://github.com/meiyor/deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals)| +|date|paper|code| +|---|---|---| ## 2022-01-11 -|paper|code| -|---|---| -|[communication-efficient federated learning via predictive coding](https://arxiv.org/abs/2108.00918)|[predictive-coding-fl](https://github.com/kai-yue/predictive-coding-fl)| -|[stability analysis of unfolded wmmse for power allocation](https://arxiv.org/abs/2110.07471)|[stability-uwmmse](https://github.com/archo48/stability-uwmmse)| -|[noisy neonatal chest sound separation for high-quality heart and lung sounds](https://arxiv.org/abs/2201.03211)|[heart-and-lung-sound-separation](https://github.com/egrooby-monash/heart-and-lung-sound-separation)| -|[a high-level track fusion scheme for circular quantities](https://arxiv.org/abs/2201.03267)|[circularfusionoperator](https://github.com/soerenkoh/circularfusionoperator)| -|[understanding entropy coding with asymmetric numeral systems (ans): a statistician's perspective](https://arxiv.org/abs/2201.01741)|[understanding-ans](https://github.com/bamler-lab/understanding-ans)| +|date|paper|code| +|---|---|---| +|2201.03211|[noisy neonatal chest sound separation for high-quality heart and lung sounds](https://arxiv.org/abs/2201.03211)|[heart-and-lung-sound-separation](https://github.com/egrooby-monash/heart-and-lung-sound-separation)| +|2201.03267|[a high-level track fusion scheme for circular quantities](https://arxiv.org/abs/2201.03267)|[circularfusionoperator](https://github.com/soerenkoh/circularfusionoperator)| +|2201.01741|[understanding entropy coding with asymmetric numeral systems (ans): a statistician's perspective](https://arxiv.org/abs/2201.01741)|[understanding-ans](https://github.com/bamler-lab/understanding-ans)| ## 2022-01-10 -|paper|code| -|---|---| -|[automatic open-world reliability assessment](https://arxiv.org/abs/2011.05506)|[Automatic-Open-World-Reliability-Assessment](https://github.com/ROBOTICSENGINEER/Automatic-Open-World-Reliability-Assessment)| -|[min2net: end-to-end multi-task learning for subject-independent motor imagery eeg classification](https://arxiv.org/abs/2102.03814)|[min2net](https://github.com/iobt-vistec/min2net)| +|date|paper|code| +|---|---|---| ## 2022-01-07 -|paper|code| -|---|---| -|[user-centric perspective in random access cell-free aided by spatial separability](https://arxiv.org/abs/2107.10294)|[cf-ra-spatial-separability](https://github.com/victorcroisfelt/cf-ra-spatial-separability)| -|[necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables](https://arxiv.org/abs/2102.10324)|[tigramite](https://github.com/jakobrunge/tigramite)| +|date|paper|code| +|---|---|---| ## 2022-01-06 -|paper|code| -|---|---| -|[a sketching framework for reduced data transfer in photon counting lidar](https://arxiv.org/abs/2102.08732)|[sketched_lidar](https://gitlab.com/Tachella/sketched_lidar)| -|[robust photon-efficient imaging using a pixel-wise residual shrinkage network](https://arxiv.org/abs/2201.01453)|[robust-photon-efficient-imaging-using-prsnet](https://github.com/gongxinyao/robust-photon-efficient-imaging-using-prsnet)| +|date|paper|code| +|---|---|---| +|2201.01453|[robust photon-efficient imaging using a pixel-wise residual shrinkage network](https://arxiv.org/abs/2201.01453)|[robust-photon-efficient-imaging-using-prsnet](https://github.com/gongxinyao/robust-photon-efficient-imaging-using-prsnet)| ## 2022-01-05 -|paper|code| -|---|---| -|[self-supervised representation learning from 12-lead ecg data](https://arxiv.org/abs/2103.12676)|[ecg-selfsupervised](https://github.com/hhi-aml/ecg-selfsupervised)| -|[homological time series analysis of sensor signals from power plants](https://arxiv.org/abs/2106.02493)|[TwirlFlake](https://github.com/karhunenloeve/TwirlFlake)| -|[dihedral multi-reference alignment](https://arxiv.org/abs/2107.05262)|[DihedralMRA](https://github.com/nirsharon/DihedralMRA)| -|[deep learning interviews: hundreds of fully solved job interview questions from a wide range of key topics in ai](https://arxiv.org/abs/2201.00650)|[interviews.ai](https://github.com/BoltzmannEntropy/interviews.ai)| +|date|paper|code| +|---|---|---| +|2201.00650|[deep learning interviews: hundreds of fully solved job interview questions from a wide range of key topics in ai](https://arxiv.org/abs/2201.00650)|[interviews.ai](https://github.com/BoltzmannEntropy/interviews.ai)| ## 2022-01-04 -|paper|code| -|---|---| -|[a review of open-world learning and steps toward open-world learning without labels](https://arxiv.org/abs/2011.12906)|[Open_World_Learning_Without_Labels](https://github.com/ROBOTICSENGINEER/Open_World_Learning_Without_Labels)| -|[reconfigurable intelligent surfaces: a signal processing perspective with wireless applications](https://arxiv.org/abs/2102.00742)|[spm_ris](https://github.com/emilbjornson/spm_ris)| -|[ncvx: a user-friendly and scalable package for nonconvex optimization in machine learning](https://arxiv.org/abs/2111.13984)|[ncvx](https://github.com/sun-umn/ncvx)| -|[uncertainty detection in eeg neural decoding models](https://arxiv.org/abs/2201.00627)|[ue-eeg](https://github.com/tiehangd/ue-eeg)| -|[optimal representations for covariate shift](https://arxiv.org/abs/2201.00057)|[optdom](https://github.com/ryoungj/optdom)| +|date|paper|code| +|---|---|---| +|2201.00627|[uncertainty detection in eeg neural decoding models](https://arxiv.org/abs/2201.00627)|[ue-eeg](https://github.com/tiehangd/ue-eeg)| +|2201.00057|[optimal representations for covariate shift](https://arxiv.org/abs/2201.00057)|[optdom](https://github.com/ryoungj/optdom)| ## 2022-01-03 -|paper|code| -|---|---| -|[evaluation of interpretability for deep learning algorithms in eeg emotion recognition: a case study in autism](https://arxiv.org/abs/2111.13208)|[deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals](https://github.com/meiyor/deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals)| -|[elastic 3d wavefield simulation on budget gpus using the glsl shading language](https://arxiv.org/abs/2112.15071)|[GLSL-Elastic-3D-Wavefield-Simulation](https://github.com/nosemeocurreapodo/GLSL-Elastic-3D-Wavefield-Simulation)| -|[multiple testing and variable selection along the path of the least angle regression](https://arxiv.org/abs/1906.12072)|[lar_testing](https://github.com/ydecastro/lar_testing)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/02.md b/archives/2022/02.md index cfc4f77d..7b056d2d 100644 --- a/archives/2022/02.md +++ b/archives/2022/02.md @@ -1,165 +1,114 @@ # February 2022 Archive ## 2022-02-28 -|paper|code| -|---|---| -|[multi-head relu implicit neural representation networks](https://arxiv.org/abs/2110.03448)|[mh-relu-inr](https://github.com/alirezamorsali/mh-relu-inr)| -|[mixture model auto-encoders: deep clustering through dictionary learning](https://arxiv.org/abs/2110.04683)|[mixmate](https://github.com/al5250/mixmate)| -|[nearest subspace search in the signed cumulative distribution transform space for 1d signal classification](https://arxiv.org/abs/2110.05606)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| -|[fast matching pursuit with multi-gabor dictionaries](https://arxiv.org/abs/2202.12380)|[fastmpwithmultigabor](https://github.com/ltfat/fastmpwithmultigabor)| -|[a unifying theory of thompson sampling for continuous risk-averse bandits](https://arxiv.org/abs/2108.11345)|[continuous-rho-ts](https://github.com/joel-ql-chang/continuous-rho-ts)| +|date|paper|code| +|---|---|---| +|2202.12380|[fast matching pursuit with multi-gabor dictionaries](https://arxiv.org/abs/2202.12380)|[fastmpwithmultigabor](https://github.com/ltfat/fastmpwithmultigabor)| ## 2022-02-25 -|paper|code| -|---|---| -|[detection by sampling: massive mimo detector based on langevin dynamics](https://arxiv.org/abs/2202.12199)|[langevin-mimo-detector](https://github.com/nzilberstein/langevin-mimo-detector)| -|[quantum circuit design for universal distribution using a superposition of classical automata](https://arxiv.org/abs/2006.00987)|[QuBio](https://github.com/Advanced-Research-Centre/QuBio)| +|date|paper|code| +|---|---|---| +|2202.12199|[detection by sampling: massive mimo detector based on langevin dynamics](https://arxiv.org/abs/2202.12199)|[langevin-mimo-detector](https://github.com/nzilberstein/langevin-mimo-detector)| ## 2022-02-23 -|paper|code| -|---|---| -|[an experimental mmwave channel model for uav-to-uav communications](https://arxiv.org/abs/2007.11869)|[uav-to-uav-60-ghz-channel-model](https://github.com/wineslab/uav-to-uav-60-ghz-channel-model)| -|[foundations of user-centric cell-free massive mimo](https://arxiv.org/abs/2108.02541)|[cell-free-book](https://github.com/emilbjornson/cell-free-book)| -|[rawboost: a raw data boosting and augmentation method applied to automatic speaker verification anti-spoofing](https://arxiv.org/abs/2111.04433)|[RawBoost-antispoofing](https://github.com/TakHemlata/RawBoost-antispoofing)| -|[learning from an exploring demonstrator: optimal reward estimation for bandits](https://arxiv.org/abs/2106.14866)|[inverse-bandit-code-release](https://github.com/wenshuoguo/inverse-bandit-code-release)| -|[fasura: a scheme for quasi-static massive mimo unsourced random access channels](https://arxiv.org/abs/2202.11042)|[mmtc](https://github.com/engprojects/mmtc)| +|date|paper|code| +|---|---|---| +|2202.11042|[fasura: a scheme for quasi-static massive mimo unsourced random access channels](https://arxiv.org/abs/2202.11042)|[mmtc](https://github.com/engprojects/mmtc)| ## 2022-02-22 -|paper|code| -|---|---| -|[millimeter wave wireless assisted robot navigation with link state classification](https://arxiv.org/abs/2110.14789)|[mmwRobotNav](https://github.com/nyu-wireless/mmwRobotNav)| -|[a novel 1d state space for efficient music rhythmic analysis](https://arxiv.org/abs/2111.00704)|[1d-statespace](https://github.com/mjhydri/1d-statespace)| -|[embedding decomposition for artifacts removal in eeg signals](https://arxiv.org/abs/2112.00989)|[deepseparator](https://github.com/ncclabsustech/deepseparator)| -|[vehif: an accessible vegetation high-impedance fault data set format](https://arxiv.org/abs/2112.03651)|[hif_vegetation_data](https://github.com/dougpsg/hif_vegetation_data)| -|[echofilter: a deep learning segmentation model improves the automation, standardization, and timeliness for post-processing echosounder data in tidal energy streams](https://arxiv.org/abs/2202.09648)|[echofilter](https://github.com/deepsenseca/echofilter)| -|[coordinated sum-rate maximization in multicell mu-mimo with deep unrolling](https://arxiv.org/abs/2202.10371)|[gcnwmmse](https://github.com/lsky96/gcnwmmse)| -|[provably efficient machine learning for quantum many-body problems](https://arxiv.org/abs/2106.12627)|[provable-ml-quantum](https://github.com/hsinyuan-huang/provable-ml-quantum)| +|date|paper|code| +|---|---|---| +|2202.09648|[echofilter: a deep learning segmentation model improves the automation, standardization, and timeliness for post-processing echosounder data in tidal energy streams](https://arxiv.org/abs/2202.09648)|[echofilter](https://github.com/deepsenseca/echofilter)| +|2202.10371|[coordinated sum-rate maximization in multicell mu-mimo with deep unrolling](https://arxiv.org/abs/2202.10371)|[gcnwmmse](https://github.com/lsky96/gcnwmmse)| ## 2022-02-21 -|paper|code| -|---|---| -|[eeg-based cross-subject driver drowsiness recognition with an interpretable convolutional neural network](https://arxiv.org/abs/2107.09507)|[eeg-based-cross-subject-driver-drowsiness-recognition-with-an-interpretable-cnn](https://github.com/cuijiancorbin/eeg-based-cross-subject-driver-drowsiness-recognition-with-an-interpretable-cnn)| -|[feasibility of modeling orthogonal frequency-division multiplexing communication signals with unsupervised generative adversarial networks](https://arxiv.org/abs/2109.05107)|[ofdm-gan](https://github.com/usnistgov/ofdm-gan)| -|[towards best practice of interpreting deep learning models for eeg-based brain computer interfaces](https://arxiv.org/abs/2202.06948)|[Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI](https://github.com/cuijiancorbin/Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI)| -|[signal decomposition using masked proximal operators](https://arxiv.org/abs/2202.09338)|[signal-decomposition](https://github.com/cvxgrp/signal-decomposition)| -|[stratified multivariate multiscale dispersion entropy for physiological signal analysis](https://arxiv.org/abs/2202.09298)|[smvmde](https://github.com/evangeloskafantaris/smvmde)| +|date|paper|code| +|---|---|---| +|2202.06948|[towards best practice of interpreting deep learning models for eeg-based brain computer interfaces](https://arxiv.org/abs/2202.06948)|[Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI](https://github.com/cuijiancorbin/Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI)| +|2202.09338|[signal decomposition using masked proximal operators](https://arxiv.org/abs/2202.09338)|[signal-decomposition](https://github.com/cvxgrp/signal-decomposition)| +|2202.09298|[stratified multivariate multiscale dispersion entropy for physiological signal analysis](https://arxiv.org/abs/2202.09298)|[smvmde](https://github.com/evangeloskafantaris/smvmde)| ## 2022-02-18 -|paper|code| -|---|---| -|[fann-on-mcu: an open-source toolkit for energy-efficient neural network inference at the edge of the internet of things](https://arxiv.org/abs/1911.03314)|[fann-on-mcu](https://github.com/pulp-platform/fann-on-mcu)| -|[user-centric perspective in random access cell-free aided by spatial separability](https://arxiv.org/abs/2107.10294)|[cf-ra-spatial-separability](https://github.com/victorcroisfelt/cf-ra-spatial-separability)| -|[delay-oriented distributed scheduling using graph neural networks](https://arxiv.org/abs/2111.07017)|[gcn-dql](https://github.com/zhongyuanzhao/gcn-dql)| -|[two-dimensional structure functions to characterize convective rolls in the marine atmospheric boundary layer from sentinel-1 sar images](https://arxiv.org/abs/2202.08538)|[2d-structure-functions](https://github.com/cgranerob/2d-structure-functions)| +|date|paper|code| +|---|---|---| +|2202.08538|[two-dimensional structure functions to characterize convective rolls in the marine atmospheric boundary layer from sentinel-1 sar images](https://arxiv.org/abs/2202.08538)|[2d-structure-functions](https://github.com/cgranerob/2d-structure-functions)| ## 2022-02-17 -|paper|code| -|---|---| -|[direct design of biquad filter cascades with deep learning by sampling random polynomials](https://arxiv.org/abs/2110.03691)|[iirnet](https://github.com/csteinmetz1/iirnet)| -|[neural capacity estimators: how reliable are they?](https://arxiv.org/abs/2111.07401)|[nce_icc-2022](https://github.com/farhad-mrkm/nce_icc-2022)| -|[deep-learning-assisted configuration of reconfigurable intelligent surfaces in dynamic rich-scattering environments](https://arxiv.org/abs/2202.07884)|[deep_ris_tuning_for_rich_scattering_environments](https://github.com/noesyslab/deep_ris_tuning_for_rich_scattering_environments)| -|[enhancing causal estimation through unlabeled offline data](https://arxiv.org/abs/2202.07895)|[enhancing-causal-estimations](https://github.com/ronteichner/enhancing-causal-estimations)| +|date|paper|code| +|---|---|---| +|2202.07884|[deep-learning-assisted configuration of reconfigurable intelligent surfaces in dynamic rich-scattering environments](https://arxiv.org/abs/2202.07884)|[deep_ris_tuning_for_rich_scattering_environments](https://github.com/noesyslab/deep_ris_tuning_for_rich_scattering_environments)| +|2202.07895|[enhancing causal estimation through unlabeled offline data](https://arxiv.org/abs/2202.07895)|[enhancing-causal-estimations](https://github.com/ronteichner/enhancing-causal-estimations)| ## 2022-02-16 -|paper|code| -|---|---| -|[an investigation of the effectiveness of phase for audio classification](https://arxiv.org/abs/2110.02878)|[investigation-phase](https://github.com/onkyo14taro/investigation-phase)| -|[r-local sensing: improved algorithm and applications](https://arxiv.org/abs/2110.14034)|[proximal-alt-min-for-uls-udgp](https://github.com/aabbas02/proximal-alt-min-for-uls-udgp)| -|[score-based generative models for robust channel estimation](https://arxiv.org/abs/2111.08177)|[diffusion-channels](https://github.com/utcsilab/diffusion-channels)| -|[hermes: hybrid error-corrector model with inclusion of external signals for nonstationary fashion time series](https://arxiv.org/abs/2202.03224)|[f1fashiondataset](https://github.com/etidav/f1fashiondataset)| -|[understanding knowledge integration in language models with graph convolutions](https://arxiv.org/abs/2202.00964)|[gcs_ki](https://github.com/yifan-h/gcs_ki)| +|date|paper|code| +|---|---|---| +|2202.03224|[hermes: hybrid error-corrector model with inclusion of external signals for nonstationary fashion time series](https://arxiv.org/abs/2202.03224)|[f1fashiondataset](https://github.com/etidav/f1fashiondataset)| +|2202.00964|[understanding knowledge integration in language models with graph convolutions](https://arxiv.org/abs/2202.00964)|[gcs_ki](https://github.com/yifan-h/gcs_ki)| ## 2022-02-15 -|paper|code| -|---|---| -|[demystifying why local aggregation helps: convergence analysis of hierarchical sgd](https://arxiv.org/abs/2010.12998)|[hierarchical-sgd](https://github.com/c3atuofu/hierarchical-sgd)| -|[massive uncoordinated access with random user activity](https://arxiv.org/abs/2103.09721)|[uma_random_user_activity](https://github.com/khachoang1412/uma_random_user_activity)| -|[coded resnext: a network for designing disentangled information paths](https://arxiv.org/abs/2202.05343)|[coded-resnext](https://github.com/avranasa/coded-resnext)| -|[unsourced multiple access with random user activity](https://arxiv.org/abs/2202.06365)|[uma_random_user_activity](https://github.com/khachoang1412/uma_random_user_activity)| +|date|paper|code| +|---|---|---| +|2202.05343|[coded resnext: a network for designing disentangled information paths](https://arxiv.org/abs/2202.05343)|[coded-resnext](https://github.com/avranasa/coded-resnext)| +|2202.06365|[unsourced multiple access with random user activity](https://arxiv.org/abs/2202.06365)|[uma_random_user_activity](https://github.com/khachoang1412/uma_random_user_activity)| ## 2022-02-14 -|paper|code| -|---|---| -|[a dynamic response recovery framework using ambient synchrophasor data](https://arxiv.org/abs/2104.05614)|[dy_resp_pkg_new](https://github.com/ShaohuiLiu/dy_resp_pkg_new)| -|[graphon-aided joint estimation of multiple graphs](https://arxiv.org/abs/2202.05686)|[jointinf_graphs_graphon](https://github.com/mn51/jointinf_graphs_graphon)| +|date|paper|code| +|---|---|---| +|2202.05686|[graphon-aided joint estimation of multiple graphs](https://arxiv.org/abs/2202.05686)|[jointinf_graphs_graphon](https://github.com/mn51/jointinf_graphs_graphon)| ## 2022-02-11 -|paper|code| -|---|---| -|[an information-theoretic justification for model pruning](https://arxiv.org/abs/2102.08329)|[SuRP](https://github.com/BerivanIsik/SuRP)| -|[sumo: advanced sleep spindle identification with neural networks](https://arxiv.org/abs/2202.05158)|[sumo](https://github.com/dslaborg/sumo)| +|date|paper|code| +|---|---|---| +|2202.05158|[sumo: advanced sleep spindle identification with neural networks](https://arxiv.org/abs/2202.05158)|[sumo](https://github.com/dslaborg/sumo)| ## 2022-02-10 -|paper|code| -|---|---| -|[deep augmented music algorithm for data-driven doa estimation](https://arxiv.org/abs/2109.10581)|[icassp22](https://github.com/da-music/icassp22)| -|[uncertainty in data-driven kalman filtering for partially known state-space models](https://arxiv.org/abs/2110.04738)|[errcov_icassp22](https://github.com/kalmannet/errcov_icassp22)| -|[admm-dad net: a deep unfolding network for analysis compressed sensing](https://arxiv.org/abs/2110.06986)|[ADMM-DAD](https://github.com/vicky-k-19/ADMM-DAD)| -|[active sensing for communications by learning](https://arxiv.org/abs/2112.04075)|[dl-activesensing](https://github.com/foadsohrabi/dl-activesensing)| -|[adjacent-bits-swapped polar codes: a new code construction to speed up polarization](https://arxiv.org/abs/2202.04454)|[abs-polar](https://github.com/plumjelly/abs-polar)| +|date|paper|code| +|---|---|---| +|2202.04454|[adjacent-bits-swapped polar codes: a new code construction to speed up polarization](https://arxiv.org/abs/2202.04454)|[abs-polar](https://github.com/plumjelly/abs-polar)| ## 2022-02-09 -|paper|code| -|---|---| -|[a deep neural network for ssvep-based brain-computer interfaces](https://arxiv.org/abs/2011.08562)|[Deep-SSVEP-BCI](https://github.com/osmanberke/Deep-SSVEP-BCI)| -|[rtsnet: deep learning aided kalman smoothing](https://arxiv.org/abs/2110.04717)|[rtsnet_icassp22](https://github.com/kalmannet/rtsnet_icassp22)| -|[a covariant, discrete time-frequency representation tailored for zero-based signal detection](https://arxiv.org/abs/2202.03835)|[kravchuk-transform-and-its-zeros](https://github.com/bpascal-fr/kravchuk-transform-and-its-zeros)| -|[unsupervised source separation via self-supervised training](https://arxiv.org/abs/2202.03875)|[mixcycle](https://github.com/ertug/mixcycle)| +|date|paper|code| +|---|---|---| +|2202.03835|[a covariant, discrete time-frequency representation tailored for zero-based signal detection](https://arxiv.org/abs/2202.03835)|[kravchuk-transform-and-its-zeros](https://github.com/bpascal-fr/kravchuk-transform-and-its-zeros)| +|2202.03875|[unsupervised source separation via self-supervised training](https://arxiv.org/abs/2202.03875)|[mixcycle](https://github.com/ertug/mixcycle)| ## 2022-02-08 -|paper|code| -|---|---| -|[physfad: physics-based end-to-end channel modeling of ris-parametrized environments with adjustable fading](https://arxiv.org/abs/2202.02673)|[physfad](https://github.com/philipp-delhougne/physfad)| -|[inter-subject contrastive learning for subject adaptive eeg-based visual recognition](https://arxiv.org/abs/2202.02901)|[Deep-BCI](https://github.com/DeepBCI/Deep-BCI)| -|[over-the-air ensemble inference with model privacy](https://arxiv.org/abs/2202.03129)|[oac-based-private-ensembles](https://github.com/selimfirat/oac-based-private-ensembles)| -|[hermes: hybrid error-corrector model with inclusion of external signals for nonstationary fashion time series](https://arxiv.org/abs/2202.03224)|[f1fashiondataset](https://github.com/etidav/f1fashiondataset)| -|[gradient-based learning of discrete structured measurement operators for signal recovery](https://arxiv.org/abs/2202.03391)|[glodismo](https://github.com/josauder/glodismo)| -|[nearest neighbor density functional estimation from inverse laplace transform](https://arxiv.org/abs/1805.08342)|[knn-functional-estimation](https://github.com/jongharyu/knn-functional-estimation)| -|[bayesian context trees: modelling and exact inference for discrete time series](https://arxiv.org/abs/2007.14900)|[Bayesian-Suffix-Trees](https://github.com/IoannisPapageorgiou/Bayesian-Suffix-Trees)| -|[tight mutual information estimation with contrastive fenchel-legendre optimization](https://arxiv.org/abs/2107.01131)|[FLO](https://github.com/qingguo666/FLO)| -|[decoding reed-muller codes with successive codeword permutations](https://arxiv.org/abs/2109.02122)|[SPRLD](https://github.com/nghiadt05/SPRLD)| -|[parameter-free online linear optimization with side information via universal coin betting](https://arxiv.org/abs/2202.02406)|[olo-with-side-information](https://github.com/jongharyu/olo-with-side-information)| -|[lossy gradient compression: how much accuracy can one bit buy?](https://arxiv.org/abs/2202.02812)|[fl_rd](https://github.com/sadafsk/fl_rd)| -|[analog secure distributed matrix multiplication over complex numbers](https://arxiv.org/abs/2202.03352)|[sdmm-over-complex](https://github.com/okkomakkonen/sdmm-over-complex)| +|date|paper|code| +|---|---|---| +|2202.02673|[physfad: physics-based end-to-end channel modeling of ris-parametrized environments with adjustable fading](https://arxiv.org/abs/2202.02673)|[physfad](https://github.com/philipp-delhougne/physfad)| +|2202.02901|[inter-subject contrastive learning for subject adaptive eeg-based visual recognition](https://arxiv.org/abs/2202.02901)|[Deep-BCI](https://github.com/DeepBCI/Deep-BCI)| +|2202.03129|[over-the-air ensemble inference with model privacy](https://arxiv.org/abs/2202.03129)|[oac-based-private-ensembles](https://github.com/selimfirat/oac-based-private-ensembles)| +|2202.03224|[hermes: hybrid error-corrector model with inclusion of external signals for nonstationary fashion time series](https://arxiv.org/abs/2202.03224)|[f1fashiondataset](https://github.com/etidav/f1fashiondataset)| +|2202.03391|[gradient-based learning of discrete structured measurement operators for signal recovery](https://arxiv.org/abs/2202.03391)|[glodismo](https://github.com/josauder/glodismo)| +|2202.02406|[parameter-free online linear optimization with side information via universal coin betting](https://arxiv.org/abs/2202.02406)|[olo-with-side-information](https://github.com/jongharyu/olo-with-side-information)| +|2202.02812|[lossy gradient compression: how much accuracy can one bit buy?](https://arxiv.org/abs/2202.02812)|[fl_rd](https://github.com/sadafsk/fl_rd)| +|2202.03352|[analog secure distributed matrix multiplication over complex numbers](https://arxiv.org/abs/2202.03352)|[sdmm-over-complex](https://github.com/okkomakkonen/sdmm-over-complex)| ## 2022-02-07 -|paper|code| -|---|---| -|[millimeter wave wireless assisted robot navigation with link state classification](https://arxiv.org/abs/2110.14789)|[mmwRobotNav](https://github.com/nyu-wireless/mmwRobotNav)| -|[maximum likelihood estimation of optimal receiver operating characteristic curves from likelihood ratio observations](https://arxiv.org/abs/2202.01956)|[mleroc](https://github.com/veggente/mleroc)| +|date|paper|code| +|---|---|---| +|2202.01956|[maximum likelihood estimation of optimal receiver operating characteristic curves from likelihood ratio observations](https://arxiv.org/abs/2202.01956)|[mleroc](https://github.com/veggente/mleroc)| ## 2022-02-04 -|paper|code| -|---|---| -|[the terminating-knockoff filter: fast high-dimensional variable selection with false discovery rate control](https://arxiv.org/abs/2110.06048)|[tknock](https://github.com/jasinmachkour/tknock)| -|[node-screening tests for l0-penalized least-squares problem with supplementary material](https://arxiv.org/abs/2110.07308)|[bnb-screening](https://gitlab.insa-rennes.fr/Theo.Guyard/bnb-screening)| -|[mgc: a complex-valued graph convolutional network for directed graphs](https://arxiv.org/abs/2110.07570)|[MGCs](https://github.com/hazdzz/MGCs)| -|[locunet: fast urban positioning using radio maps and deep learning](https://arxiv.org/abs/2202.00738)|[LocUNet](https://github.com/CagkanYapar/LocUNet)| -|[improving lyrics alignment through joint pitch detection](https://arxiv.org/abs/2202.01646)|[lyricsalignment-mtl](https://github.com/jhuang448/lyricsalignment-mtl)| -|[approximation of images via generalized higher order singular value decomposition over finite-dimensional commutative semisimple algebra](https://arxiv.org/abs/2202.00450)|[talgebra](https://github.com/liaoliang2020/talgebra)| +|date|paper|code| +|---|---|---| +|2202.00738|[locunet: fast urban positioning using radio maps and deep learning](https://arxiv.org/abs/2202.00738)|[LocUNet](https://github.com/CagkanYapar/LocUNet)| +|2202.01646|[improving lyrics alignment through joint pitch detection](https://arxiv.org/abs/2202.01646)|[lyricsalignment-mtl](https://github.com/jhuang448/lyricsalignment-mtl)| +|2202.00450|[approximation of images via generalized higher order singular value decomposition over finite-dimensional commutative semisimple algebra](https://arxiv.org/abs/2202.00450)|[talgebra](https://github.com/liaoliang2020/talgebra)| ## 2022-02-03 -|paper|code| -|---|---| -|[online change point detection for weighted and directed random dot product graphs](https://arxiv.org/abs/2201.11222)|[cpd_rdpg](https://github.com/git-artes/cpd_rdpg)| -|[perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising](https://arxiv.org/abs/2110.08775)|[perturbative_mean_field_matrix_factorization](https://github.com/sphinxteam/perturbative_mean_field_matrix_factorization)| +|date|paper|code| +|---|---|---| ## 2022-02-02 -|paper|code| -|---|---| -|[total least squares phase retrieval](https://arxiv.org/abs/2102.00927)|[tls_phase](https://github.com/swing-research/tls_phase)| -|[practical graph signal sampling with log-linear size scaling](https://arxiv.org/abs/2102.10506)|[graph-signal-sampling-avm](https://github.com/stac-usc/graph-signal-sampling-avm)| -|[a machine-learning-based direction-of-origin filter for the identification of radio frequency interference in the search for technosignatures](https://arxiv.org/abs/2108.00559)|[doom](https://github.com/UCLA-SETI-Group/doom)| -|[deepfilternet: a low complexity speech enhancement framework for full-band audio based on deep filtering](https://arxiv.org/abs/2110.05588)|[deepfilternet](https://github.com/rikorose/deepfilternet)| -|[arrhythmia classification using cgan-augmented ecg signals](https://arxiv.org/abs/2202.00569)|[augmentation-of-ecg-training-dataset-with-cgan](https://github.com/mah533/augmentation-of-ecg-training-dataset-with-cgan)| -|[blind ecg restoration by operational cycle-gans](https://arxiv.org/abs/2202.00589)|[blind-ecg-restoration-by-operational-cycle-gans](https://github.com/ozercandevecioglu/blind-ecg-restoration-by-operational-cycle-gans)| -|[fundamental performance limits for sensor-based robot control and policy learning](https://arxiv.org/abs/2202.00129)|[performance-limits](https://github.com/irom-lab/performance-limits)| -|[non-adaptive and two-stage coding over the z-channel](https://arxiv.org/abs/2202.00136)|[Z-channel_with_1_error](https://github.com/VorobyevIlya/Z-channel_with_1_error)| +|date|paper|code| +|---|---|---| +|2202.00569|[arrhythmia classification using cgan-augmented ecg signals](https://arxiv.org/abs/2202.00569)|[augmentation-of-ecg-training-dataset-with-cgan](https://github.com/mah533/augmentation-of-ecg-training-dataset-with-cgan)| +|2202.00589|[blind ecg restoration by operational cycle-gans](https://arxiv.org/abs/2202.00589)|[blind-ecg-restoration-by-operational-cycle-gans](https://github.com/ozercandevecioglu/blind-ecg-restoration-by-operational-cycle-gans)| +|2202.00129|[fundamental performance limits for sensor-based robot control and policy learning](https://arxiv.org/abs/2202.00129)|[performance-limits](https://github.com/irom-lab/performance-limits)| +|2202.00136|[non-adaptive and two-stage coding over the z-channel](https://arxiv.org/abs/2202.00136)|[Z-channel_with_1_error](https://github.com/VorobyevIlya/Z-channel_with_1_error)| ## 2022-02-01 -|paper|code| -|---|---| -|[reconfigurable intelligent surface phase hopping for ultra-reliable communications](https://arxiv.org/abs/2107.11852)|[ris-phase-hopping](https://github.com/klb2/ris-phase-hopping)| -|[deep task-based analog-to-digital conversion](https://arxiv.org/abs/2201.12634)|[adc-learning-hyperopt](https://github.com/arielamar123/adc-learning-hyperopt)| -|[decoding reed-muller codes with successive codeword permutations](https://arxiv.org/abs/2109.02122)|[SPRLD](https://github.com/nghiadt05/SPRLD)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/03.md b/archives/2022/03.md index b6fa72ac..dea9333b 100644 --- a/archives/2022/03.md +++ b/archives/2022/03.md @@ -1,183 +1,125 @@ # March 2022 Archive ## 2022-03-31 -|paper|code| -|---|---| -|[common information, matroid representation, and secret sharing for matroid ports](https://arxiv.org/abs/2002.08108)|[common-information-and-matroid-ports](https://github.com/bmilosh/common-information-and-matroid-ports)| -|[unbiased single-scale and multi-scale quantizers for distributed optimization](https://arxiv.org/abs/2109.12497)|[Gradient-Compression](https://github.com/vineeths96/Gradient-Compression)| -|[self-dual hadamard bent sequences](https://arxiv.org/abs/2203.16439)|[hadamard_bent](https://github.com/qomo-cheng/hadamard_bent)| +|date|paper|code| +|---|---|---| +|2203.16439|[self-dual hadamard bent sequences](https://arxiv.org/abs/2203.16439)|[hadamard_bent](https://github.com/qomo-cheng/hadamard_bent)| ## 2022-03-30 -|paper|code| -|---|---| -|[multiple hypothesis testing framework for spatial signals](https://arxiv.org/abs/2108.12314)|[lfdr-smom](https://github.com/mgoelz95/lfdr-smom)| -|[an approximate expectation-maximization for two-dimensional multi-target detection](https://arxiv.org/abs/2110.02289)|[mtd-2d-em](https://github.com/krshay/mtd-2d-em)| -|[physics informed neural networks for control oriented thermal modeling of buildings](https://arxiv.org/abs/2111.12066)|[physnet_thermal_models](https://github.com/gargyagokhale/physnet_thermal_models)| -|[separate what you describe: language-queried audio source separation](https://arxiv.org/abs/2203.15147)|[lass](https://github.com/liuxubo717/lass)| -|[analysis of eeg frequency bands for envisioned speech recognition](https://arxiv.org/abs/2203.15250)|[imaginedspeechrecognition](https://github.com/ayushayt/imaginedspeechrecognition)| -|[over-the-air federated learning via second-order optimization](https://arxiv.org/abs/2203.15488)|[AirFL-2nd](https://github.com/Golden-Slumber/AirFL-2nd)| -|[approximation of images via generalized higher order singular value decomposition over finite-dimensional commutative semisimple algebra](https://arxiv.org/abs/2202.00450)|[talgebra](https://github.com/liaoliang2020/talgebra)| +|date|paper|code| +|---|---|---| +|2203.15147|[separate what you describe: language-queried audio source separation](https://arxiv.org/abs/2203.15147)|[lass](https://github.com/liuxubo717/lass)| +|2203.15250|[analysis of eeg frequency bands for envisioned speech recognition](https://arxiv.org/abs/2203.15250)|[imaginedspeechrecognition](https://github.com/ayushayt/imaginedspeechrecognition)| +|2203.15488|[over-the-air federated learning via second-order optimization](https://arxiv.org/abs/2203.15488)|[AirFL-2nd](https://github.com/Golden-Slumber/AirFL-2nd)| ## 2022-03-29 -|paper|code| -|---|---| -|[deep unfolding basis pursuit: improving sparse channel reconstruction via data-driven measurement matrices](https://arxiv.org/abs/2007.05177)|[DeepBP-AE](https://github.com/pengxiawu/DeepBP-AE)| -|[parametric scattering networks](https://arxiv.org/abs/2107.09539)|[ParametricScatteringNetworks](https://github.com/bentherien/ParametricScatteringNetworks)| -|[predicting the impact of formation protocols on battery lifetime immediately after manufacturing](https://arxiv.org/abs/2203.14158)|[fast-formation](https://github.com/wengandrew/fast-formation)| -|[distributed link sparsification for scalable scheduling using graph neural networks](https://arxiv.org/abs/2203.14339)|[gcn-sparsify](https://github.com/zhongyuanzhao/gcn-sparsify)| -|[online meta-learning for hybrid model-based deep receivers](https://arxiv.org/abs/2203.14359)|[metadeepsic](https://github.com/tomerraviv95/metadeepsic)| -|[q-ppg: energy-efficient ppg-based heart rate monitoring on wearable devices](https://arxiv.org/abs/2203.14907)|[q-ppg](https://github.com/embeddedml-edagroup/q-ppg)| -|[neural vocoder is all you need for speech super-resolution](https://arxiv.org/abs/2203.14941)|[ssr_eval](https://github.com/haoheliu/ssr_eval)| +|date|paper|code| +|---|---|---| +|2203.14158|[predicting the impact of formation protocols on battery lifetime immediately after manufacturing](https://arxiv.org/abs/2203.14158)|[fast-formation](https://github.com/wengandrew/fast-formation)| +|2203.14339|[distributed link sparsification for scalable scheduling using graph neural networks](https://arxiv.org/abs/2203.14339)|[gcn-sparsify](https://github.com/zhongyuanzhao/gcn-sparsify)| +|2203.14359|[online meta-learning for hybrid model-based deep receivers](https://arxiv.org/abs/2203.14359)|[metadeepsic](https://github.com/tomerraviv95/metadeepsic)| +|2203.14907|[q-ppg: energy-efficient ppg-based heart rate monitoring on wearable devices](https://arxiv.org/abs/2203.14907)|[q-ppg](https://github.com/embeddedml-edagroup/q-ppg)| +|2203.14941|[neural vocoder is all you need for speech super-resolution](https://arxiv.org/abs/2203.14941)|[ssr_eval](https://github.com/haoheliu/ssr_eval)| ## 2022-03-28 -|paper|code| -|---|---| -|[bddm: bilateral denoising diffusion models for fast and high-quality speech synthesis](https://arxiv.org/abs/2203.13508)|[bddm](https://github.com/tencent-ailab/bddm)| +|date|paper|code| +|---|---|---| +|2203.13508|[bddm: bilateral denoising diffusion models for fast and high-quality speech synthesis](https://arxiv.org/abs/2203.13508)|[bddm](https://github.com/tencent-ailab/bddm)| ## 2022-03-25 -|paper|code| -|---|---| -|[complex frequency domain linear prediction: a tool to compute modulation spectrum of speech](https://arxiv.org/abs/2203.13216)|[fdlp_spectrogram](https://github.com/sadhusamik/fdlp_spectrogram)| -|[distilling ghz states using stabilizer codes](https://arxiv.org/abs/2109.06248)|[ghz_distillation_qec](https://github.com/nrenga/ghz_distillation_qec)| +|date|paper|code| +|---|---|---| +|2203.13216|[complex frequency domain linear prediction: a tool to compute modulation spectrum of speech](https://arxiv.org/abs/2203.13216)|[fdlp_spectrogram](https://github.com/sadhusamik/fdlp_spectrogram)| ## 2022-03-24 -|paper|code| -|---|---| -|[lggnet: learning from local-global-graph representations for brain-computer interface](https://arxiv.org/abs/2105.02786)|[LGG](https://github.com/yi-ding-cs/LGG)| -|[estimation of consistent time delays in subsample via auxiliary-function-based iterative updates](https://arxiv.org/abs/2203.09723)|[auxtde](https://github.com/onolab-tmu/auxtde)| -|[transsleep: transitioning-aware attention-based deep neural network for sleep staging](https://arxiv.org/abs/2203.12590)|[transsleep](https://github.com/ku-milab/transsleep)| -|[deep learning based intelligent coin-tap test for defect recognition](https://arxiv.org/abs/2203.12594)|[torch-tapnet](https://github.com/pphub-hy/torch-tapnet)| -|[physiomtl: personalizing physiological patterns using optimal transport multi-task regression](https://arxiv.org/abs/2203.12595)|[mmash](https://github.com/rossialessio/mmash)| -|[fast quantum state reconstruction via accelerated non-convex programming](https://arxiv.org/abs/2104.07006)|[MiFGD](https://github.com/gidiko/MiFGD)| -|[scale-invariant representation of machine learning](https://arxiv.org/abs/2109.02914)|[powerlaw_ml](https://github.com/sungyeop/powerlaw_ml)| -|[node representation learning in graph via node-to-neighbourhood mutual information maximization](https://arxiv.org/abs/2203.12265)|[n2n](https://github.com/dongwei156/n2n)| -|[the impact of partial packet recovery on the inherent secrecy of random linear coding](https://arxiv.org/abs/2203.12336)|[vtc2022-spring](https://github.com/ioannischatzigeorgiou/vtc2022-spring)| +|date|paper|code| +|---|---|---| +|2203.09723|[estimation of consistent time delays in subsample via auxiliary-function-based iterative updates](https://arxiv.org/abs/2203.09723)|[auxtde](https://github.com/onolab-tmu/auxtde)| +|2203.12590|[transsleep: transitioning-aware attention-based deep neural network for sleep staging](https://arxiv.org/abs/2203.12590)|[transsleep](https://github.com/ku-milab/transsleep)| +|2203.12594|[deep learning based intelligent coin-tap test for defect recognition](https://arxiv.org/abs/2203.12594)|[torch-tapnet](https://github.com/pphub-hy/torch-tapnet)| +|2203.12595|[physiomtl: personalizing physiological patterns using optimal transport multi-task regression](https://arxiv.org/abs/2203.12595)|[mmash](https://github.com/rossialessio/mmash)| +|2203.12265|[node representation learning in graph via node-to-neighbourhood mutual information maximization](https://arxiv.org/abs/2203.12265)|[n2n](https://github.com/dongwei156/n2n)| +|2203.12336|[the impact of partial packet recovery on the inherent secrecy of random linear coding](https://arxiv.org/abs/2203.12336)|[vtc2022-spring](https://github.com/ioannischatzigeorgiou/vtc2022-spring)| ## 2022-03-23 -|paper|code| -|---|---| -|[signal2image modules in deep neural networks for eeg classification](https://arxiv.org/abs/1904.13216)|[signal2image-modules-in-deep-neural-networks-for-eeg-classification](https://github.com/pbizopoulos/signal2image-modules-in-deep-neural-networks-for-eeg-classification)| -|[sionna: an open-source library for next-generation physical layer research](https://arxiv.org/abs/2203.11854)|[sionna](https://github.com/nvlabs/sionna)| +|date|paper|code| +|---|---|---| +|2203.11854|[sionna: an open-source library for next-generation physical layer research](https://arxiv.org/abs/2203.11854)|[sionna](https://github.com/nvlabs/sionna)| ## 2022-03-22 -|paper|code| -|---|---| -|[phase collapse in neural networks](https://arxiv.org/abs/2110.05283)|[phasecollapse](https://github.com/florentinguth/phasecollapse)| -|[neural capacity estimators: how reliable are they?](https://arxiv.org/abs/2111.07401)|[nce_icc-2022](https://github.com/farhad-mrkm/nce_icc-2022)| -|[physics informed neural networks for control oriented thermal modeling of buildings](https://arxiv.org/abs/2111.12066)|[physnet_thermal_models](https://github.com/gargyagokhale/physnet_thermal_models)| -|[efficient doa estimation method for reconfigurable intelligent surfaces aided uav swarm](https://arxiv.org/abs/2203.10219)|[adpp](https://github.com/chenpengseu/adpp)| -|[sdoanet: an efficient deep learning-based doa estimation network for imperfect array](https://arxiv.org/abs/2203.10231)|[sdoanet](https://github.com/chenpengseu/sdoanet)| -|[graph neural networks for wireless communications: from theory to practice](https://arxiv.org/abs/2203.10800)|[gnn4com](https://github.com/yshenaw/gnn4com)| -|[learning resilient radio resource management policies with graph neural networks](https://arxiv.org/abs/2203.11012)|[Resilient_RRM_GNN](https://github.com/navid-naderi/Resilient_RRM_GNN)| -|[towards optimally efficient search with deep learning for large-scale mimo systems](https://arxiv.org/abs/2101.02420)|[hats](https://github.com/skypitcher/hats)| +|date|paper|code| +|---|---|---| +|2203.10219|[efficient doa estimation method for reconfigurable intelligent surfaces aided uav swarm](https://arxiv.org/abs/2203.10219)|[adpp](https://github.com/chenpengseu/adpp)| +|2203.10231|[sdoanet: an efficient deep learning-based doa estimation network for imperfect array](https://arxiv.org/abs/2203.10231)|[sdoanet](https://github.com/chenpengseu/sdoanet)| +|2203.10800|[graph neural networks for wireless communications: from theory to practice](https://arxiv.org/abs/2203.10800)|[gnn4com](https://github.com/yshenaw/gnn4com)| +|2203.11012|[learning resilient radio resource management policies with graph neural networks](https://arxiv.org/abs/2203.11012)|[Resilient_RRM_GNN](https://github.com/navid-naderi/Resilient_RRM_GNN)| ## 2022-03-21 -|paper|code| -|---|---| -|[lead-agnostic self-supervised learning for local and global representations of electrocardiogram](https://arxiv.org/abs/2203.06889)|[fairseq-signals](https://github.com/jwoo5/fairseq-signals)| -|[generative principal component analysis](https://arxiv.org/abs/2203.09693)|[GenerativePCA](https://github.com/liuzq09/GenerativePCA)| +|date|paper|code| +|---|---|---| +|2203.06889|[lead-agnostic self-supervised learning for local and global representations of electrocardiogram](https://arxiv.org/abs/2203.06889)|[fairseq-signals](https://github.com/jwoo5/fairseq-signals)| +|2203.09693|[generative principal component analysis](https://arxiv.org/abs/2203.09693)|[GenerativePCA](https://github.com/liuzq09/GenerativePCA)| ## 2022-03-18 -|paper|code| -|---|---| -|[enhancement of a state-of-the-art rl-based detection algorithm for massive mimo radars](https://arxiv.org/abs/2112.02628)|[improved_rl_algorithm_mmimo_radar](https://github.com/lisifra96/improved_rl_algorithm_mmimo_radar)| +|date|paper|code| +|---|---|---| ## 2022-03-17 -|paper|code| -|---|---| -|[robust equivariant imaging: a fully unsupervised framework for learning to image from noisy and partial measurements](https://arxiv.org/abs/2111.12855)|[rei](https://github.com/edongdongchen/rei)| -|[lossless compression with probabilistic circuits](https://arxiv.org/abs/2111.11632)|[pressedjuice.jl](https://github.com/juice-jl/pressedjuice.jl)| +|date|paper|code| +|---|---|---| ## 2022-03-16 -|paper|code| -|---|---| -|[ensemble neural representation networks](https://arxiv.org/abs/2110.04124)|[enrp](https://github.com/alirezamorsali/enrp)| -|[a regularization method to improve adversarial robustness of neural networks for ecg signal classification](https://arxiv.org/abs/2110.09759)|[robust_dnn_for_ecg](https://github.com/sarielma/robust_dnn_for_ecg)| -|[benchmarking and interpreting end-to-end learning of mimo and multi-user communication](https://arxiv.org/abs/2203.07703)|[DeepLearning_MIMO](https://github.com/JSChalmers/DeepLearning_MIMO)| -|[generalized rectifier wavelet covariance models for texture synthesis](https://arxiv.org/abs/2203.07902)|[wavelet-texture-synthesis](https://github.com/abrochar/wavelet-texture-synthesis)| -|[minimal algorithmic information loss methods for dimension reduction, feature selection and network sparsification](https://arxiv.org/abs/1802.05843)|[Network-Robustness-by-Kolmogorov-Complexity](https://github.com/andandandand/Network-Robustness-by-Kolmogorov-Complexity)| -|[optimal representations for covariate shift](https://arxiv.org/abs/2201.00057)|[optdom](https://github.com/ryoungj/optdom)| -|[optimizing the communication-accuracy trade-off in federated learning with rate-distortion theory](https://arxiv.org/abs/2201.02664)|[compressed_communication](https://github.com/google-research/federated/tree/1b31b84/compressed_communication)| -|[optimal denoising of rotationally invariant rectangular matrices](https://arxiv.org/abs/2203.07752)|[rectangular_rie](https://github.com/penombraet/rectangular_rie)| +|date|paper|code| +|---|---|---| +|2203.07703|[benchmarking and interpreting end-to-end learning of mimo and multi-user communication](https://arxiv.org/abs/2203.07703)|[DeepLearning_MIMO](https://github.com/JSChalmers/DeepLearning_MIMO)| +|2203.07902|[generalized rectifier wavelet covariance models for texture synthesis](https://arxiv.org/abs/2203.07902)|[wavelet-texture-synthesis](https://github.com/abrochar/wavelet-texture-synthesis)| +|2203.07752|[optimal denoising of rotationally invariant rectangular matrices](https://arxiv.org/abs/2203.07752)|[rectangular_rie](https://github.com/penombraet/rectangular_rie)| ## 2022-03-15 -|paper|code| -|---|---| -|[self-supervised graph neural networks for improved electroencephalographic seizure analysis](https://arxiv.org/abs/2104.08336)|[eeg-gnn-ssl](https://github.com/tsy935/eeg-gnn-ssl)| -|[neural architecture search for spiking neural networks](https://arxiv.org/abs/2201.10355)|[neural-architecture-search-for-spiking-neural-networks](https://github.com/intelligent-computing-lab-yale/neural-architecture-search-for-spiking-neural-networks)| -|[modelling non-smooth signals with complex spectral structure](https://arxiv.org/abs/2203.06997)|[gpcm](https://github.com/wesselb/gpcm)| -|[a novel approach to the partial information decomposition](https://arxiv.org/abs/1908.08642)|[redundancy](https://github.com/artemyk/redundancy)| +|date|paper|code| +|---|---|---| +|2203.06997|[modelling non-smooth signals with complex spectral structure](https://arxiv.org/abs/2203.06997)|[gpcm](https://github.com/wesselb/gpcm)| ## 2022-03-14 -|paper|code| -|---|---| -|[kalmannet: neural network aided kalman filtering for partially known dynamics](https://arxiv.org/abs/2107.10043)|[KalmanNet_TSP](https://github.com/KalmanNet/KalmanNet_TSP)| -|[nearest neighbor density functional estimation from inverse laplace transform](https://arxiv.org/abs/1805.08342)|[knn-functional-estimation](https://github.com/jongharyu/knn-functional-estimation)| +|date|paper|code| +|---|---|---| ## 2022-03-11 -|paper|code| -|---|---| -|[exploring scalable, distributed real-time anomaly detection for bridge health monitoring](https://arxiv.org/abs/2203.02380)|[real_time_bhm](https://github.com/miirho3ein/real_time_bhm)| +|date|paper|code| +|---|---|---| +|2203.02380|[exploring scalable, distributed real-time anomaly detection for bridge health monitoring](https://arxiv.org/abs/2203.02380)|[real_time_bhm](https://github.com/miirho3ein/real_time_bhm)| ## 2022-03-09 -|paper|code| -|---|---| -|[reconfigurable intelligent surfaces: a signal processing perspective with wireless applications](https://arxiv.org/abs/2102.00742)|[spm_ris](https://github.com/emilbjornson/spm_ris)| -|[the terminating-knockoff filter: fast high-dimensional variable selection with false discovery rate control](https://arxiv.org/abs/2110.06048)|[tknock](https://github.com/jasinmachkour/tknock)| -|[roadside lidar vehicle detection and tracking using range and intensity background subtraction](https://arxiv.org/abs/2201.04756)|[roadside-lidar-vehicle-detection-and-tracking-background-subtraction](https://github.com/teryzh/roadside-lidar-vehicle-detection-and-tracking-background-subtraction)| -|[coding theory package for macaulay2](https://arxiv.org/abs/2007.06795)|[Workshop-2020-Cleveland](https://github.com/Macaulay2/Workshop-2020-Cleveland)| -|[information theoretic structured generative modeling](https://arxiv.org/abs/2110.05794)|[structured-generative-modeling](https://github.com/bohu615/structured-generative-modeling)| -|[fasura: a scheme for quasi-static massive mimo unsourced random access channels](https://arxiv.org/abs/2202.11042)|[mmtc](https://github.com/engprojects/mmtc)| +|date|paper|code| +|---|---|---| ## 2022-03-08 -|paper|code| -|---|---| -|[biologically plausible single-layer networks for nonnegative independent component analysis](https://arxiv.org/abs/2010.12632)|[bio-nica](https://github.com/flatironinstitute/bio-nica)| -|[decentralized beamforming for cell-free massive mimo with unsupervised learning](https://arxiv.org/abs/2106.16194)|[CF-mMIMO-HBF](https://github.com/HamedHojatian/CF-mMIMO-HBF)| -|[predicting flat-fading channels via meta-learned closed-form linear filters and equilibrium propagation](https://arxiv.org/abs/2110.00414)|[scalar-channel-meta-prediction](https://github.com/kclip/scalar-channel-meta-prediction)| -|[unrolling palm for sparse semi-blind source separation](https://arxiv.org/abs/2112.05694)|[lpalm](https://github.com/mfahes/lpalm)| -|[early stopping for deep image prior](https://arxiv.org/abs/2112.06074)|[early_stopping_for_dip](https://github.com/sun-umn/early_stopping_for_dip)| -|[transformers in time series: a survey](https://arxiv.org/abs/2202.07125)|[time-series-transformers-review](https://github.com/qingsongedu/time-series-transformers-review)| -|[hrtf measurement for accurate identification of binaural sound localization cues](https://arxiv.org/abs/2203.03166)|[hrtf-construction](https://github.com/hansaram80/hrtf-construction)| +|date|paper|code| +|---|---|---| +|2203.03166|[hrtf measurement for accurate identification of binaural sound localization cues](https://arxiv.org/abs/2203.03166)|[hrtf-construction](https://github.com/hansaram80/hrtf-construction)| ## 2022-03-07 -|paper|code| -|---|---| -|[relay-assisted cooperative federated learning](https://arxiv.org/abs/2107.09518)|[relay-fl](https://github.com/zhlinup/relay-fl)| -|[two-dimensional structure functions to characterize convective rolls in the marine atmospheric boundary layer from sentinel-1 sar images](https://arxiv.org/abs/2202.08538)|[2d-structure-functions](https://github.com/cgranerob/2d-structure-functions)| -|[beats: an open-source, high-precision, multi-channel eeg acquisition tool system](https://arxiv.org/abs/2203.02102)|[beats](https://github.com/bingzant/beats)| -|[towards optimally efficient search with deep learning for large-scale mimo systems](https://arxiv.org/abs/2101.02420)|[hats](https://github.com/skypitcher/hats)| -|[a unified spatially coupled code design: threshold, cycles, and locality](https://arxiv.org/abs/2203.02052)|[unified_sc_ldpcl](https://github.com/hesfahanizadeh/unified_sc_ldpcl)| -|[programmable optical data transmission through multimode fibres enabling confidentiality by physical layer security](https://arxiv.org/abs/2203.02064)|[mmf-physec](https://github.com/klb2/mmf-physec)| +|date|paper|code| +|---|---|---| +|2203.02102|[beats: an open-source, high-precision, multi-channel eeg acquisition tool system](https://arxiv.org/abs/2203.02102)|[beats](https://github.com/bingzant/beats)| +|2203.02052|[a unified spatially coupled code design: threshold, cycles, and locality](https://arxiv.org/abs/2203.02052)|[unified_sc_ldpcl](https://github.com/hesfahanizadeh/unified_sc_ldpcl)| +|2203.02064|[programmable optical data transmission through multimode fibres enabling confidentiality by physical layer security](https://arxiv.org/abs/2203.02064)|[mmf-physec](https://github.com/klb2/mmf-physec)| ## 2022-03-04 -|paper|code| -|---|---| -|[label-aware ranked loss for robust people counting using automotive in-cabin radar](https://arxiv.org/abs/2110.05876)|[labelawareranked-loss](https://github.com/2geeks2/labelawareranked-loss)| +|date|paper|code| +|---|---|---| ## 2022-03-03 -|paper|code| -|---|---| -|[leveraging power grid topology in machine learning assisted optimal power flow](https://arxiv.org/abs/2110.00306)|[MLOPF.jl](https://github.com/tdfalc/MLOPF.jl)| -|[a fast and scalable polyatomic frank-wolfe algorithm for the lasso](https://arxiv.org/abs/2112.02890)|[PolyatomicFW_SPL](https://github.com/AdriaJ/PolyatomicFW_SPL)| -|[signal decomposition using masked proximal operators](https://arxiv.org/abs/2202.09338)|[signal-decomposition](https://github.com/cvxgrp/signal-decomposition)| -|[sketched rt3d: how to reconstruct billions of photons per second](https://arxiv.org/abs/2203.00952)|[real-time-sp-lidar](https://gitlab.com/tachella/real-time-sp-lidar)| +|date|paper|code| +|---|---|---| +|2203.00952|[sketched rt3d: how to reconstruct billions of photons per second](https://arxiv.org/abs/2203.00952)|[real-time-sp-lidar](https://gitlab.com/tachella/real-time-sp-lidar)| ## 2022-03-02 -|paper|code| -|---|---| -|[two-dimensional multi-target detection: an autocorrelation analysis approach](https://arxiv.org/abs/2105.06765)|[MTD-2D](https://github.com/krshay/MTD-2D)| -|[phycom: a multi-layer parametric network for joint linear impairments compensation and symbol detection](https://arxiv.org/abs/2203.00266)|[PhyCOM](https://github.com/vincentchoqueuse/PhyCOM)| -|[tcmi: a non-parametric mutual-dependence estimator for multivariate continuous distributions](https://arxiv.org/abs/2001.11212)|[tcmi](https://github.com/BenjaminRegler/tcmi)| +|date|paper|code| +|---|---|---| +|2203.00266|[phycom: a multi-layer parametric network for joint linear impairments compensation and symbol detection](https://arxiv.org/abs/2203.00266)|[PhyCOM](https://github.com/vincentchoqueuse/PhyCOM)| ## 2022-03-01 -|paper|code| -|---|---| -|[depth estimation from monocular images and sparse radar using deep ordinal regression network](https://arxiv.org/abs/2107.07596)|[DORN_radar](https://github.com/lochenchou/DORN_radar)| -|[automated parkinson's disease detection and affective analysis from emotional eeg signals](https://arxiv.org/abs/2202.12936)|[pd-eeg](https://github.com/ravikiranrao/pd-eeg)| -|[signal-to-noise ratio is more important than sampling rate in beat-to-beat interval estimation from optical sensors](https://arxiv.org/abs/2202.13651)|[ppg_sim_snr_fs](https://github.com/kismed-tuda/ppg_sim_snr_fs)| -|[fast off-the-grid sparse recovery with over-parametrized projected gradient descent](https://arxiv.org/abs/2202.13757)|[opcomp_sparse_recovery](https://github.com/pjbenard/opcomp_sparse_recovery)| -|[admm-dad net: a deep unfolding network for analysis compressed sensing](https://arxiv.org/abs/2110.06986)|[ADMM-DAD](https://github.com/vicky-k-19/ADMM-DAD)| -|[sparsity-aware neural user behavior modeling in online interaction platforms](https://arxiv.org/abs/2202.13491)|[Inf-VAE](https://github.com/aravindsankar28/Inf-VAE)| -|[kl divergence estimation with multi-group attribution](https://arxiv.org/abs/2202.13576)|[multigroup-kl](https://github.com/vatsalsharan/multigroup-kl)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/04.md b/archives/2022/04.md index 562dde41..55c2a521 100644 --- a/archives/2022/04.md +++ b/archives/2022/04.md @@ -1,108 +1,79 @@ # April 2022 Archive ## 2022-04-29 -|paper|code| -|---|---| -|[real-time outdoor localization using radio maps: a deep learning approach](https://arxiv.org/abs/2106.12556)|[LocUNet](https://github.com/CagkanYapar/LocUNet)| -|[attention based neural networks for wireless channel estimation](https://arxiv.org/abs/2204.13465)|[Attention_Based_Neural_Networks_for_Wireless_Channel_Estimation](https://github.com/dianixn/Attention_Based_Neural_Networks_for_Wireless_Channel_Estimation)| -|[interpretable collective intelligence of non-rational human agents](https://arxiv.org/abs/2204.13424)|[collective-intelligence-research](https://github.com/nicknick85/collective-intelligence-research)| +|date|paper|code| +|---|---|---| +|2204.13465|[attention based neural networks for wireless channel estimation](https://arxiv.org/abs/2204.13465)|[Attention_Based_Neural_Networks_for_Wireless_Channel_Estimation](https://github.com/dianixn/Attention_Based_Neural_Networks_for_Wireless_Channel_Estimation)| +|2204.13424|[interpretable collective intelligence of non-rational human agents](https://arxiv.org/abs/2204.13424)|[collective-intelligence-research](https://github.com/nicknick85/collective-intelligence-research)| ## 2022-04-28 -|paper|code| -|---|---| -|[1-bit compressive sensing via approximate message passing with built-in parameter estimation](https://arxiv.org/abs/2007.07679)|[1Bit-CS](https://github.com/shuai-huang/1Bit-CS)| -|[salience: an unsupervised user adaptation model for multiple wearable sensors based human activity recognition](https://arxiv.org/abs/2108.10213)|[SALIENCE](https://github.com/wdkhuans/SALIENCE)| -|[leveraging power grid topology in machine learning assisted optimal power flow](https://arxiv.org/abs/2110.00306)|[MLOPF.jl](https://github.com/tdfalc/MLOPF.jl)| -|[music source separation with generative flow](https://arxiv.org/abs/2204.09079)|[generativesourceseparation](https://github.com/gzhu06/generativesourceseparation)| +|date|paper|code| +|---|---|---| +|2204.09079|[music source separation with generative flow](https://arxiv.org/abs/2204.09079)|[generativesourceseparation](https://github.com/gzhu06/generativesourceseparation)| ## 2022-04-27 -|paper|code| -|---|---| -|[block alternating bregman majorization minimization with extrapolation](https://arxiv.org/abs/2107.04395)|[BMME](https://github.com/LeThiKhanhHien/BMME)| -|[encoding cardiopulmonary exercise testing time series as images for classification using convolutional neural network](https://arxiv.org/abs/2204.12432)|[multivariatetimeseries](https://github.com/yashsharma/multivariatetimeseries)| +|date|paper|code| +|---|---|---| +|2204.12432|[encoding cardiopulmonary exercise testing time series as images for classification using convolutional neural network](https://arxiv.org/abs/2204.12432)|[multivariatetimeseries](https://github.com/yashsharma/multivariatetimeseries)| ## 2022-04-26 -|paper|code| -|---|---| -|[experiments with mmwave automotive radar test-bed](https://arxiv.org/abs/1912.12566)|[mmWave-radar-signal-processing-and-microDoppler-classification](https://github.com/Xiangyu-Gao/mmWave-radar-signal-processing-and-microDoppler-classification)| -|[probabilistic rainfall estimation from automotive lidar](https://arxiv.org/abs/2104.11467)|[rainfall_modeling_open](https://github.com/tier4/rainfall_modeling_open)| -|[pyffs: a python library for fast fourier series computation and interpolation with gpu acceleration](https://arxiv.org/abs/2110.00262)|[pyFFS](https://github.com/imagingofthings/pyFFS)| -|[a ris-based passive doa estimation method for integrated sensing and communication system](https://arxiv.org/abs/2204.11626)|[passivedoa-isac-ris](https://github.com/chenpengseu/passivedoa-isac-ris)| +|date|paper|code| +|---|---|---| +|2204.11626|[a ris-based passive doa estimation method for integrated sensing and communication system](https://arxiv.org/abs/2204.11626)|[passivedoa-isac-ris](https://github.com/chenpengseu/passivedoa-isac-ris)| ## 2022-04-25 -|paper|code| -|---|---| -|[sinr: deconvolving circular sas images using implicit neural representations](https://arxiv.org/abs/2204.10428)|[csas_deconvolution_inr](https://github.com/awreed/csas_deconvolution_inr)| +|date|paper|code| +|---|---|---| +|2204.10428|[sinr: deconvolving circular sas images using implicit neural representations](https://arxiv.org/abs/2204.10428)|[csas_deconvolution_inr](https://github.com/awreed/csas_deconvolution_inr)| ## 2022-04-22 -|paper|code| -|---|---| -|[ultra marginal feature importance](https://arxiv.org/abs/2204.09938)|[umfi](https://github.com/joej1997/umfi)| +|date|paper|code| +|---|---|---| +|2204.09938|[ultra marginal feature importance](https://arxiv.org/abs/2204.09938)|[umfi](https://github.com/joej1997/umfi)| ## 2022-04-21 -|paper|code| -|---|---| -|[atlas fusion -- modern framework for autonomous agent sensor data fusion](https://arxiv.org/abs/2010.11991)|[Atlas-Fusion](https://github.com/Robotics-BUT/Atlas-Fusion)| -|[dual aspect self-attention based on transformer for remaining useful life prediction](https://arxiv.org/abs/2106.15842)|[dast](https://github.com/zzzsdu/dast)| -|[rewis: reliable wi-fi sensing through few-shot multi-antenna multi-receiver csi learning](https://arxiv.org/abs/2201.00869)|[rewis](https://github.com/niloobah/rewis)| -|[syncnet: using causal convolutions and correlating objective for time delay estimation in audio signals](https://arxiv.org/abs/2203.14639)|[2022_syncnet](https://github.com/madhavlab/2022_syncnet)| -|[music source separation with generative flow](https://arxiv.org/abs/2204.09079)|[generativesourceseparation](https://github.com/gzhu06/generativesourceseparation)| -|[radiology text analysis system (radtext): architecture and evaluation](https://arxiv.org/abs/2204.09599)|[radtext](https://github.com/bionlplab/radtext)| +|date|paper|code| +|---|---|---| +|2204.09079|[music source separation with generative flow](https://arxiv.org/abs/2204.09079)|[generativesourceseparation](https://github.com/gzhu06/generativesourceseparation)| +|2204.09599|[radiology text analysis system (radtext): architecture and evaluation](https://arxiv.org/abs/2204.09599)|[radtext](https://github.com/bionlplab/radtext)| ## 2022-04-11 -|paper|code| -|---|---| -|[cnn-based approaches for cross-subject classification in motor imagery: from the state-of-the-art to dynamicnet](https://arxiv.org/abs/2105.07917)|[Dynamic-PyTorch-Net](https://github.com/jesus-333/Dynamic-PyTorch-Net)| -|[multi-centroid hyperdimensional computing approach for epileptic seizure detection](https://arxiv.org/abs/2111.08463)|[](https://c4science.ch/source/MultiCentroidHD_public/)| -|[deconvolution of the functional ultrasound response in the mouse visual pathway using block-term decomposition](https://arxiv.org/abs/2204.03711)|[btd_deconv](https://github.com/ayerol/btd_deconv)| -|[design of an optimal testbed for tracking of tagged marine megafauna](https://arxiv.org/abs/2204.04155)|[receiver-deployment](https://github.com/kerentalmon/receiver-deployment)| -|[automatic data augmentation selection and parametrization in contrastive self-supervised speech representation learning](https://arxiv.org/abs/2204.04170)|[augmentations](https://github.com/salah-zaiem/augmentations)| -|[recovering or testing extended-affine equivalence](https://arxiv.org/abs/2103.00078)|[EA_equivalence_for_quadratic_functions](https://github.com/alaincouvreur/EA_equivalence_for_quadratic_functions)| +|date|paper|code| +|---|---|---| +|2204.03711|[deconvolution of the functional ultrasound response in the mouse visual pathway using block-term decomposition](https://arxiv.org/abs/2204.03711)|[btd_deconv](https://github.com/ayerol/btd_deconv)| +|2204.04155|[design of an optimal testbed for tracking of tagged marine megafauna](https://arxiv.org/abs/2204.04155)|[receiver-deployment](https://github.com/kerentalmon/receiver-deployment)| +|2204.04170|[automatic data augmentation selection and parametrization in contrastive self-supervised speech representation learning](https://arxiv.org/abs/2204.04170)|[augmentations](https://github.com/salah-zaiem/augmentations)| ## 2022-04-08 -|paper|code| -|---|---| -|[wifieye -- seeing over wifi made accessible](https://arxiv.org/abs/2204.01830)|[wifieye](https://github.com/pkindt/wifieye)| -|[muleeg: a multi-view representation learning on eeg signals](https://arxiv.org/abs/2204.03272)|[muleeg](https://github.com/likith012/muleeg)| -|[binary spatial random field reconstruction from non-gaussian inhomogeneous time-series observations](https://arxiv.org/abs/2204.03343)|[WarpedGaussianProcesses](https://github.com/ShunanSheng/WarpedGaussianProcesses)| -|[rf signal transformation and classification using deep neural networks](https://arxiv.org/abs/2204.03564)|[rf_classification](https://github.com/umarkhalidcs/rf_classification)| -|[structured gradient descent for fast robust low-rank hankel matrix completion](https://arxiv.org/abs/2204.03316)|[hsgd](https://github.com/caesarcai/hsgd)| +|date|paper|code| +|---|---|---| +|2204.01830|[wifieye -- seeing over wifi made accessible](https://arxiv.org/abs/2204.01830)|[wifieye](https://github.com/pkindt/wifieye)| +|2204.03272|[muleeg: a multi-view representation learning on eeg signals](https://arxiv.org/abs/2204.03272)|[muleeg](https://github.com/likith012/muleeg)| +|2204.03343|[binary spatial random field reconstruction from non-gaussian inhomogeneous time-series observations](https://arxiv.org/abs/2204.03343)|[WarpedGaussianProcesses](https://github.com/ShunanSheng/WarpedGaussianProcesses)| +|2204.03564|[rf signal transformation and classification using deep neural networks](https://arxiv.org/abs/2204.03564)|[rf_classification](https://github.com/umarkhalidcs/rf_classification)| +|2204.03316|[structured gradient descent for fast robust low-rank hankel matrix completion](https://arxiv.org/abs/2204.03316)|[hsgd](https://github.com/caesarcai/hsgd)| ## 2022-04-07 -|paper|code| -|---|---| -|[hrtf measurement for accurate sound localization cues](https://arxiv.org/abs/2203.03166)|[hrtf-hats-kaist](https://github.com/han-saram/hrtf-hats-kaist)| -|[pareto-optimal clustering with the primal deterministic information bottleneck](https://arxiv.org/abs/2204.02489)|[pareto_dib](https://github.com/andrewktan/pareto_dib)| +|date|paper|code| +|---|---|---| +|2204.02489|[pareto-optimal clustering with the primal deterministic information bottleneck](https://arxiv.org/abs/2204.02489)|[pareto_dib](https://github.com/andrewktan/pareto_dib)| ## 2022-04-06 -|paper|code| -|---|---| -|[the generalized method of moments for multi-reference alignment](https://arxiv.org/abs/2103.02215)|[gmm-cryo](https://github.com/abasasa/gmm-cryo)| -|[patient contrastive learning: a performant, expressive, and practical approach to ecg modeling](https://arxiv.org/abs/2104.04569)|[ml4h](https://github.com/broadinstitute/ml4h)| -|[gan-based joint activity detection and channel estimation for grant-free random access](https://arxiv.org/abs/2204.01731)|[jadce](https://github.com/deeeeeeplearning/jadce)| +|date|paper|code| +|---|---|---| +|2204.01731|[gan-based joint activity detection and channel estimation for grant-free random access](https://arxiv.org/abs/2204.01731)|[jadce](https://github.com/deeeeeeplearning/jadce)| ## 2022-04-05 -|paper|code| -|---|---| -|[vehicular visible light positioning for collision avoidance and platooning: a survey](https://arxiv.org/abs/2010.09858)|[vehicular-vlp-simulations](https://github.com/sonebu/vehicular-vlp-simulations)| -|[electrocardio panorama: synthesizing new ecg views with self-supervision](https://arxiv.org/abs/2105.06293)|[Electrocardio-Panorama](https://github.com/WhatAShot/Electrocardio-Panorama)| -|[fbdnn: filter banks and deep neural networks for portable and fast brain-computer interfaces](https://arxiv.org/abs/2109.02165)|[fbcnn](https://github.com/pedrorasb/fbcnn)| -|[power allocation for wireless federated learning using graph neural networks](https://arxiv.org/abs/2111.07480)|[wirelessfl-pdgnet](https://github.com/bl166/wirelessfl-pdgnet)| -|[variational message passing for online polynomial narmax identification](https://arxiv.org/abs/2204.00769)|[acc2022-vmpnarmax](https://github.com/biaslab/acc2022-vmpnarmax)| +|date|paper|code| +|---|---|---| +|2204.00769|[variational message passing for online polynomial narmax identification](https://arxiv.org/abs/2204.00769)|[acc2022-vmpnarmax](https://github.com/biaslab/acc2022-vmpnarmax)| ## 2022-04-04 -|paper|code| -|---|---| -|[a fast transformer-based general-purpose lossless compressor](https://arxiv.org/abs/2203.16114)|[a-fast-transformer-based-general-purpose-losslesscompressor](https://github.com/mynotwo/a-fast-transformer-based-general-purpose-losslesscompressor)| -|[robust remote estimation over the collision channel in the presence of an intelligent jammer](https://arxiv.org/abs/2204.00148)|[cdc22](https://github.com/mullervasconcelos/cdc22)| +|date|paper|code| +|---|---|---| +|2204.00148|[robust remote estimation over the collision channel in the presence of an intelligent jammer](https://arxiv.org/abs/2204.00148)|[cdc22](https://github.com/mullervasconcelos/cdc22)| ## 2022-04-01 -|paper|code| -|---|---| -|[single-pixel compressive imaging in shift-invariant spaces via exact wavelet frames](https://arxiv.org/abs/2106.00404)|[compressive_imaging_in_si_spaces](https://github.com/retiro/compressive_imaging_in_si_spaces)| -|[time-coded spiking fourier transform in neuromorphic hardware](https://arxiv.org/abs/2202.12650)|[time-coded-SFT](https://github.com/KI-ASIC-TUM/time-coded-SFT)| -|[direction of arrival estimation of sound sources using icosahedral cnns](https://arxiv.org/abs/2203.16940)|[icodoa](https://github.com/daviddiazguerra/icodoa)| -|[vqf: highly accurate imu orientation estimation with bias estimation and magnetic disturbance rejection](https://arxiv.org/abs/2203.17024)|[vqf](https://github.com/dlaidig/vqf)| -|[differentially private federated learning via reconfigurable intelligent surface](https://arxiv.org/abs/2203.17028)|[fl_privacy_blockcrossing](https://github.com/mengcongwo/fl_privacy_blockcrossing)| -|[lead1.0: a large-scale annotated dataset for energy anomaly detection in commercial buildings](https://arxiv.org/abs/2203.17256)|[lead-dataset](https://github.com/samy101/lead-dataset)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/05.md b/archives/2022/05.md index ce53193a..e5815b1a 100644 --- a/archives/2022/05.md +++ b/archives/2022/05.md @@ -1,166 +1,124 @@ # May 2022 Archive ## 2022-05-31 -|paper|code| -|---|---| -|[transfer learning-based channel estimation in orthogonal frequency division multiplexing systems using data-nulling superimposed pilots](https://arxiv.org/abs/2205.14308)|[transferlearningbasedcebydnsp](https://github.com/leiunnn/transferlearningbasedcebydnsp)| -|[recovery of future data via convolution nuclear norm minimization](https://arxiv.org/abs/1909.03889)|[CNNM](https://github.com/gcliu1982/CNNM)| +|date|paper|code| +|---|---|---| +|2205.14308|[transfer learning-based channel estimation in orthogonal frequency division multiplexing systems using data-nulling superimposed pilots](https://arxiv.org/abs/2205.14308)|[transferlearningbasedcebydnsp](https://github.com/leiunnn/transferlearningbasedcebydnsp)| ## 2022-05-30 -|paper|code| -|---|---| -|[a semidefinite relaxation for sums of heterogeneous quadratics on the stiefel manifold](https://arxiv.org/abs/2205.13653)|[sums-of-heterogeneous-quadratics](https://github.com/kgilman/sums-of-heterogeneous-quadratics)| -|[generalizing brain decoding across subjects with deep learning](https://arxiv.org/abs/2205.14102)|[meg-group-decode](https://github.com/ricsinaruto/meg-group-decode)| -|[auditing differential privacy in high dimensions with the kernel quantum r\'enyi divergence](https://arxiv.org/abs/2205.13941)|[kernel_renyi_dp](https://github.com/cdenrich/kernel_renyi_dp)| +|date|paper|code| +|---|---|---| +|2205.13653|[a semidefinite relaxation for sums of heterogeneous quadratics on the stiefel manifold](https://arxiv.org/abs/2205.13653)|[sums-of-heterogeneous-quadratics](https://github.com/kgilman/sums-of-heterogeneous-quadratics)| +|2205.14102|[generalizing brain decoding across subjects with deep learning](https://arxiv.org/abs/2205.14102)|[meg-group-decode](https://github.com/ricsinaruto/meg-group-decode)| +|2205.13941|[auditing differential privacy in high dimensions with the kernel quantum r\'enyi divergence](https://arxiv.org/abs/2205.13941)|[kernel_renyi_dp](https://github.com/cdenrich/kernel_renyi_dp)| ## 2022-05-27 -|paper|code| -|---|---| -|[multi-layer state evolution under random convolutional design](https://arxiv.org/abs/2205.13503)|[conv-ml-amp](https://github.com/mdnls/conv-ml-amp)| +|date|paper|code| +|---|---|---| +|2205.13503|[multi-layer state evolution under random convolutional design](https://arxiv.org/abs/2205.13503)|[conv-ml-amp](https://github.com/mdnls/conv-ml-amp)| ## 2022-05-26 -|paper|code| -|---|---| -|[over-the-air design of gan training for mmwave mimo channel estimation](https://arxiv.org/abs/2205.12445)|[ota-gan-mimo-ce](https://github.com/akashsdoshi96/ota-gan-mimo-ce)| -|[a real-world radio frequency signal dataset based on lte system and variable channels](https://arxiv.org/abs/2205.12577)|[xsrpdataset](https://github.com/njuptzsp/xsrpdataset)| -|[ultra-compact binary neural networks for human activity recognition on risc-v processors](https://arxiv.org/abs/2205.12781)|[ultracompactbnn](https://github.com/francescodaghero/ultracompactbnn)| +|date|paper|code| +|---|---|---| +|2205.12445|[over-the-air design of gan training for mmwave mimo channel estimation](https://arxiv.org/abs/2205.12445)|[ota-gan-mimo-ce](https://github.com/akashsdoshi96/ota-gan-mimo-ce)| +|2205.12577|[a real-world radio frequency signal dataset based on lte system and variable channels](https://arxiv.org/abs/2205.12577)|[xsrpdataset](https://github.com/njuptzsp/xsrpdataset)| +|2205.12781|[ultra-compact binary neural networks for human activity recognition on risc-v processors](https://arxiv.org/abs/2205.12781)|[ultracompactbnn](https://github.com/francescodaghero/ultracompactbnn)| ## 2022-05-25 -|paper|code| -|---|---| -|[a tutorial on terahertz-band localization for 6g communication systems](https://arxiv.org/abs/2110.08581)|[radio_localization](https://github.com/chenhui07c8/radio_localization)| -|[towards practical physics-informed ml design and evaluation for power grid](https://arxiv.org/abs/2205.03673)|[gridwarm](https://github.com/ohcindy/gridwarm)| -|[multi-agent feedback enabled neural networks for intelligent communications](https://arxiv.org/abs/2205.10750)|[MAFENN_TRANS_2022](https://github.com/liyang619/MAFENN_TRANS_2022)| +|date|paper|code| +|---|---|---| +|2205.03673|[towards practical physics-informed ml design and evaluation for power grid](https://arxiv.org/abs/2205.03673)|[gridwarm](https://github.com/ohcindy/gridwarm)| +|2205.10750|[multi-agent feedback enabled neural networks for intelligent communications](https://arxiv.org/abs/2205.10750)|[MAFENN_TRANS_2022](https://github.com/liyang619/MAFENN_TRANS_2022)| ## 2022-05-24 -|paper|code| -|---|---| -|[position aided beam prediction in the real world: how useful gps locations actually are?](https://arxiv.org/abs/2205.09054)|[position-beam-prediction](https://github.com/jmoraispk/position-beam-prediction)| -|[approximate message passing with parameter estimation for heavily quantized measurements](https://arxiv.org/abs/2205.10448)|[1Bit-CS](https://github.com/shuai-huang/1Bit-CS)| -|[antenna selection in switch-based mimo arrays via doa threshold region approximation](https://arxiv.org/abs/2205.10807)|[radio_localization](https://github.com/chenhui07c8/radio_localization)| -|[neural augmented min-sum decoding of short block codes for fading channels](https://arxiv.org/abs/2205.10684)|[nams](https://github.com/sravan-ankireddy/nams)| +|date|paper|code| +|---|---|---| +|2205.09054|[position aided beam prediction in the real world: how useful gps locations actually are?](https://arxiv.org/abs/2205.09054)|[position-beam-prediction](https://github.com/jmoraispk/position-beam-prediction)| +|2205.10448|[approximate message passing with parameter estimation for heavily quantized measurements](https://arxiv.org/abs/2205.10448)|[1Bit-CS](https://github.com/shuai-huang/1Bit-CS)| +|2205.10807|[antenna selection in switch-based mimo arrays via doa threshold region approximation](https://arxiv.org/abs/2205.10807)|[radio_localization](https://github.com/chenhui07c8/radio_localization)| +|2205.10684|[neural augmented min-sum decoding of short block codes for fading channels](https://arxiv.org/abs/2205.10684)|[nams](https://github.com/sravan-ankireddy/nams)| ## 2022-05-23 -|paper|code| -|---|---| -|[a subspace method for time series anomaly detection in cyber-physical systems](https://arxiv.org/abs/2205.09959)|[pad](https://github.com/carlosjva/pad)| -|[multivariate public key cryptosystem from sidon spaces](https://arxiv.org/abs/2106.07785)|[Sidon-Cryptosystem](https://github.com/b-langton/Sidon-Cryptosystem)| -|[optimizing the communication-accuracy trade-off in federated learning with rate-distortion theory](https://arxiv.org/abs/2201.02664)|[compressed_communication](https://github.com/google-research/federated/tree/1b31b84/compressed_communication)| +|date|paper|code| +|---|---|---| +|2205.09959|[a subspace method for time series anomaly detection in cyber-physical systems](https://arxiv.org/abs/2205.09959)|[pad](https://github.com/carlosjva/pad)| ## 2022-05-20 -|paper|code| -|---|---| -|[denoising noisy neural networks: a bayesian approach with compensation](https://arxiv.org/abs/2105.10699)|[NoisyNN](https://github.com/lynshao/NoisyNN)| +|date|paper|code| +|---|---|---| ## 2022-05-19 -|paper|code| -|---|---| -|[link scheduling using graph neural networks](https://arxiv.org/abs/2109.05536)|[distgcn](https://github.com/zhongyuanzhao/distgcn)| -|[stride: a flexible platform for high-performance ultrasound computed tomography](https://arxiv.org/abs/2110.03345)|[stride](https://github.com/trustimaging/stride)| -|[robust photon-efficient imaging using a pixel-wise residual shrinkage network](https://arxiv.org/abs/2201.01453)|[robust-photon-efficient-imaging-using-prsnet](https://github.com/y2w-oc/robust-photon-efficient-imaging-using-prsnet)| -|[approximation of images via generalized higher order singular value decomposition over finite-dimensional commutative semisimple algebra](https://arxiv.org/abs/2202.00450)|[talgebra](https://github.com/liaoliang2020/talgebra)| -|[lower-bounds on the bayesian risk in estimation procedures via $f$-divergences](https://arxiv.org/abs/2202.02557)|[f_divergences_lower_bounds](https://github.com/Adirlou/f_divergences_lower_bounds)| +|date|paper|code| +|---|---|---| ## 2022-05-18 -|paper|code| -|---|---| -|[signal2image modules in deep neural networks for eeg classification](https://arxiv.org/abs/1904.13216)|[signal2image-modules-in-deep-neural-networks-for-eeg-classification](https://github.com/pbizopoulos/signal2image-modules-in-deep-neural-networks-for-eeg-classification)| -|[r-local unlabeled sensing: a novel graph matching approach for multiview unlabeled sensing under local permutations](https://arxiv.org/abs/1911.06382)|[QAP-for-ULS](https://github.com/aabbas02/QAP-for-ULS)| -|[visual sensor network stimulation model identification via gaussian mixture model and deep embedded features](https://arxiv.org/abs/2201.06804)|[vsn-with-ae](https://github.com/luca-varotto/vsn-with-ae)| -|[near out-of-distribution detection for low-resolution radar micro-doppler signatures](https://arxiv.org/abs/2205.07869)|[doppler-signatures-generation](https://github.com/blupblupblup/doppler-signatures-generation)| +|date|paper|code| +|---|---|---| +|2205.07869|[near out-of-distribution detection for low-resolution radar micro-doppler signatures](https://arxiv.org/abs/2205.07869)|[doppler-signatures-generation](https://github.com/blupblupblup/doppler-signatures-generation)| ## 2022-05-17 -|paper|code| -|---|---| -|[two-dimensional multi-target detection: an autocorrelation analysis approach](https://arxiv.org/abs/2105.06765)|[MTD-2D](https://github.com/krshay/MTD-2D)| -|[generalized autocorrelation analysis for multi-target detection](https://arxiv.org/abs/2109.11813)|[mtd-gmm](https://github.com/krshay/mtd-gmm)| -|[an approximate expectation-maximization for two-dimensional multi-target detection](https://arxiv.org/abs/2110.02289)|[mtd-2d-em](https://github.com/krshay/mtd-2d-em)| -|[over-the-air ensemble inference with model privacy](https://arxiv.org/abs/2202.03129)|[oac-based-private-ensembles](https://github.com/selimfirat/oac-based-private-ensembles)| -|[recovering or testing extended-affine equivalence](https://arxiv.org/abs/2103.00078)|[EA_equivalence_for_quadratic_functions](https://github.com/alaincouvreur/EA_equivalence_for_quadratic_functions)| -|[hybrid beam alignment for multi-path channels: a group testing viewpoint](https://arxiv.org/abs/2111.08159)|[beamforming](https://github.com/ozleemyildiz/beamforming)| -|[analog secure distributed matrix multiplication over complex numbers](https://arxiv.org/abs/2202.03352)|[sdmm-over-complex](https://github.com/okkomakkonen/sdmm-over-complex)| -|[mind: maximum mutual information based neural decoder](https://arxiv.org/abs/2205.07061)|[mind-neural-decoder](https://github.com/tonellolab/mind-neural-decoder)| +|date|paper|code| +|---|---|---| +|2205.07061|[mind: maximum mutual information based neural decoder](https://arxiv.org/abs/2205.07061)|[mind-neural-decoder](https://github.com/tonellolab/mind-neural-decoder)| ## 2022-05-16 -|paper|code| -|---|---| -|[r-local sensing: improved algorithm and applications](https://arxiv.org/abs/2110.14034)|[proximal-alt-min-for-uls-udgp](https://github.com/aabbas02/proximal-alt-min-for-uls-udgp)| -|[probabilistic estimation of chirp instantaneous frequency using gaussian processes](https://arxiv.org/abs/2205.06306)|[chirpgp](https://github.com/spdes/chirpgp)| -|[data-driven upper bounds on channel capacity](https://arxiv.org/abs/2205.06471)|[upper_capacity_bounds](https://github.com/chaeger/upper_capacity_bounds)| +|date|paper|code| +|---|---|---| +|2205.06306|[probabilistic estimation of chirp instantaneous frequency using gaussian processes](https://arxiv.org/abs/2205.06306)|[chirpgp](https://github.com/spdes/chirpgp)| +|2205.06471|[data-driven upper bounds on channel capacity](https://arxiv.org/abs/2205.06471)|[upper_capacity_bounds](https://github.com/chaeger/upper_capacity_bounds)| ## 2022-05-13 -|paper|code| -|---|---| -|[annealed langevin dynamics for massive mimo detection](https://arxiv.org/abs/2205.05776)|[langevin-mimo-detector](https://github.com/nzilberstein/langevin-mimo-detector)| -|[how well does surprisal explain n400 amplitude under different experimental conditions?](https://arxiv.org/abs/2010.04844)|[does-surprisal-explain-n400](https://github.com/jmichaelov/does-surprisal-explain-n400)| +|date|paper|code| +|---|---|---| +|2205.05776|[annealed langevin dynamics for massive mimo detection](https://arxiv.org/abs/2205.05776)|[langevin-mimo-detector](https://github.com/nzilberstein/langevin-mimo-detector)| ## 2022-05-12 -|paper|code| -|---|---| -|[advanced sleep spindle identification with neural networks](https://arxiv.org/abs/2202.05158)|[sumo](https://github.com/dslaborg/sumo)| -|[intelligent reflecting surface configurations for smart radio using deep reinforcement learning](https://arxiv.org/abs/2205.05269)|[irsconfigurationdrl](https://github.com/weiwang-wys/irsconfigurationdrl)| -|[deepfilternet2: towards real-time speech enhancement on embedded devices for full-band audio](https://arxiv.org/abs/2205.05474)|[deepfilternet](https://github.com/rikorose/deepfilternet)| +|date|paper|code| +|---|---|---| +|2205.05269|[intelligent reflecting surface configurations for smart radio using deep reinforcement learning](https://arxiv.org/abs/2205.05269)|[irsconfigurationdrl](https://github.com/weiwang-wys/irsconfigurationdrl)| +|2205.05474|[deepfilternet2: towards real-time speech enhancement on embedded devices for full-band audio](https://arxiv.org/abs/2205.05474)|[deepfilternet](https://github.com/rikorose/deepfilternet)| ## 2022-05-11 -|paper|code| -|---|---| -|[learning to continuously optimize wireless resource in a dynamic environment: a bilevel optimization perspective](https://arxiv.org/abs/2105.01696)|[TSP_CL](https://github.com/Haoran-S/TSP_CL)| -|[energy and age pareto optimal trajectories in uav-assisted wireless data collection](https://arxiv.org/abs/2106.03822)|[aoienergyuavtraopt](https://github.com/yuanliaoo/aoienergyuavtraopt)| -|[variational sparse coding with learned thresholding](https://arxiv.org/abs/2205.03665)|[variational-sparse-coding](https://github.com/kfallah/variational-sparse-coding)| -|[gridwarm: towards practical physics-informed ml design and evaluation for power grid](https://arxiv.org/abs/2205.03673)|[gridwarm](https://github.com/ohcindy/gridwarm)| -|[pervasive machine learning for smart radio environments enabled by reconfigurable intelligent surfaces](https://arxiv.org/abs/2205.03793)|[drl_ris_tutorial](https://github.com/noesyslab/drl_ris_tutorial)| -|[zeros of gaussian weyl-heisenberg functions and hyperuniformity of charge](https://arxiv.org/abs/2012.12298)|[gwhf](https://github.com/gkoliander/gwhf)| -|[universal caching](https://arxiv.org/abs/2205.04860)|[universalcaching](https://github.com/ativjoshi/universalcaching)| +|date|paper|code| +|---|---|---| +|2205.03665|[variational sparse coding with learned thresholding](https://arxiv.org/abs/2205.03665)|[variational-sparse-coding](https://github.com/kfallah/variational-sparse-coding)| +|2205.03673|[gridwarm: towards practical physics-informed ml design and evaluation for power grid](https://arxiv.org/abs/2205.03673)|[gridwarm](https://github.com/ohcindy/gridwarm)| +|2205.03793|[pervasive machine learning for smart radio environments enabled by reconfigurable intelligent surfaces](https://arxiv.org/abs/2205.03793)|[drl_ris_tutorial](https://github.com/noesyslab/drl_ris_tutorial)| +|2205.04860|[universal caching](https://arxiv.org/abs/2205.04860)|[universalcaching](https://github.com/ativjoshi/universalcaching)| ## 2022-05-10 -|paper|code| -|---|---| -|[using a drone sounder to measure channels for cell-free massive mimo systems](https://arxiv.org/abs/2106.15276)|[CF-mMIMO](https://github.com/tomathchoi/CF-mMIMO)| -|[hierarchical dirichlet process based gamma mixture modelling for terahertz band wireless communication channels](https://arxiv.org/abs/2205.03812)|[DPGMM-Channel-Modelling](https://github.com/erhankarakoca/DPGMM-Channel-Modelling)| -|[far from asymptopia](https://arxiv.org/abs/2205.03343)|[atomicpriors.jl](https://github.com/mcabbott/atomicpriors.jl)| +|date|paper|code| +|---|---|---| +|2205.03812|[hierarchical dirichlet process based gamma mixture modelling for terahertz band wireless communication channels](https://arxiv.org/abs/2205.03812)|[DPGMM-Channel-Modelling](https://github.com/erhankarakoca/DPGMM-Channel-Modelling)| +|2205.03343|[far from asymptopia](https://arxiv.org/abs/2205.03343)|[atomicpriors.jl](https://github.com/mcabbott/atomicpriors.jl)| ## 2022-05-09 -|paper|code| -|---|---| -|[a dynamic response recovery framework using ambient synchrophasor data](https://arxiv.org/abs/2104.05614)|[dy_resp_pkg_new](https://github.com/ShaohuiLiu/dy_resp_pkg_new)| -|[information fragmentation, encryption and information flow in complex biological networks](https://arxiv.org/abs/2105.13585)|[fragmentation_replication_instructions](https://github.com/cliff-bohm/fragmentation_replication_instructions)| -|[fundamental performance limits for sensor-based robot control and policy learning](https://arxiv.org/abs/2202.00129)|[performance-limits](https://github.com/irom-lab/performance-limits)| +|date|paper|code| +|---|---|---| ## 2022-05-06 -|paper|code| -|---|---| -|[minimax estimation of partially-observed vector autoregressions](https://arxiv.org/abs/2106.09327)|[POVAR.jl](https://github.com/gdalle/POVAR.jl)| -|[approximation of images via generalized higher order singular value decomposition over finite-dimensional commutative semisimple algebra](https://arxiv.org/abs/2202.00450)|[talgebra](https://github.com/liaoliang2020/talgebra)| +|date|paper|code| +|---|---|---| ## 2022-05-05 -|paper|code| -|---|---| -|[signal decomposition using masked proximal operators](https://arxiv.org/abs/2202.09338)|[signal-decomposition](https://github.com/cvxgrp/signal-decomposition)| -|[multiple testing and variable selection along the path of the least angle regression](https://arxiv.org/abs/1906.12072)|[lar_testing](https://github.com/ydecastro/lar_testing)| -|[aligning random graphs with a sub-tree similarity message-passing algorithm](https://arxiv.org/abs/2112.13079)|[graph_alignment](https://github.com/giovannipiccioli/graph_alignment)| +|date|paper|code| +|---|---|---| ## 2022-05-04 -|paper|code| -|---|---| -|[reconfigurable intelligent surface phase hopping for ultra-reliable communications](https://arxiv.org/abs/2107.11852)|[ris-phase-hopping](https://github.com/klb2/ris-phase-hopping)| -|[zeros of gaussian weyl-heisenberg functions and hyperuniformity of charge](https://arxiv.org/abs/2012.12298)|[gwhf](https://github.com/gkoliander/gwhf)| -|[modeling and correcting bias in sequential evaluation](https://arxiv.org/abs/2205.01607)|[sequential-bias](https://github.com/jingyanw/sequential-bias)| +|date|paper|code| +|---|---|---| +|2205.01607|[modeling and correcting bias in sequential evaluation](https://arxiv.org/abs/2205.01607)|[sequential-bias](https://github.com/jingyanw/sequential-bias)| ## 2022-05-03 -|paper|code| -|---|---| -|[mgait: model-based gait analysis using wearable bend and inertial sensors](https://arxiv.org/abs/2102.11895)|[mgait](https://github.com/sizhean/mgait)| -|[storseismic: a new paradigm in deep learning for seismic processing](https://arxiv.org/abs/2205.00222)|[storseismic](https://github.com/swag-kaust/storseismic)| -|[end-to-end signal classification in signed cumulative distribution transform space](https://arxiv.org/abs/2205.00348)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| -|[gmss: graph-based multi-task self-supervised learning for eeg emotion recognition](https://arxiv.org/abs/2205.01030)|[gmss](https://github.com/chen-xdu/gmss)| -|[admm-dad net: a deep unfolding network for analysis compressed sensing](https://arxiv.org/abs/2110.06986)|[ADMM-DAD](https://github.com/vicky-k-19/ADMM-DAD)| -|[deep learning-enabled semantic communication systems with task-unaware transmitter and dynamic data](https://arxiv.org/abs/2205.00271)|[semantic-communication-systems](https://github.com/sjtu-mxtao/semantic-communication-systems)| -|[ridgeless regression with random features](https://arxiv.org/abs/2205.00477)|[ridgeless-regression-with-random-features](https://github.com/superlj666/ridgeless-regression-with-random-features)| +|date|paper|code| +|---|---|---| +|2205.00222|[storseismic: a new paradigm in deep learning for seismic processing](https://arxiv.org/abs/2205.00222)|[storseismic](https://github.com/swag-kaust/storseismic)| +|2205.00348|[end-to-end signal classification in signed cumulative distribution transform space](https://arxiv.org/abs/2205.00348)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| +|2205.01030|[gmss: graph-based multi-task self-supervised learning for eeg emotion recognition](https://arxiv.org/abs/2205.01030)|[gmss](https://github.com/chen-xdu/gmss)| +|2205.00271|[deep learning-enabled semantic communication systems with task-unaware transmitter and dynamic data](https://arxiv.org/abs/2205.00271)|[semantic-communication-systems](https://github.com/sjtu-mxtao/semantic-communication-systems)| +|2205.00477|[ridgeless regression with random features](https://arxiv.org/abs/2205.00477)|[ridgeless-regression-with-random-features](https://github.com/superlj666/ridgeless-regression-with-random-features)| ## 2022-05-02 -|paper|code| -|---|---| -|[ramp-cnn: a novel neural network for enhanced automotive radar object recognition](https://arxiv.org/abs/2011.08981)|[radar-multiple-perspective-object-detection](https://github.com/xiangyu-gao/radar-multiple-perspective-object-detection)| -|[an investigation of the effectiveness of phase for audio classification](https://arxiv.org/abs/2110.02878)|[investigation-phase](https://github.com/onkyo14taro/investigation-phase)| -|[linguistic dependencies and statistical dependence](https://arxiv.org/abs/2104.08685)|[cpmi-dependencies](https://github.com/mcqll/cpmi-dependencies)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/06.md b/archives/2022/06.md index 8edf78d8..c2f84e95 100644 --- a/archives/2022/06.md +++ b/archives/2022/06.md @@ -1,176 +1,124 @@ # June 2022 Archive ## 2022-06-30 -|paper|code| -|---|---| -|[robust photon-efficient imaging using a pixel-wise residual shrinkage network](https://arxiv.org/abs/2201.01453)|[robust-photon-efficient-imaging-using-prsnet](https://github.com/y2w-oc/robust-photon-efficient-imaging-using-prsnet)| -|[correctly modeling tx and rx chain in (distributed) massive mimo -- new fundamental insights on coherency](https://arxiv.org/abs/2206.14752)|[Correctly-Modeling-TX-and-RX-Chain-in-Massive-MIMO](https://github.com/rnissel/Correctly-Modeling-TX-and-RX-Chain-in-Massive-MIMO)| -|[depth-2 neural networks under a data-poisoning attack](https://arxiv.org/abs/2005.01699)|[neurotron_experiments](https://github.com/papamarkou/neurotron_experiments)| +|date|paper|code| +|---|---|---| +|2206.14752|[correctly modeling tx and rx chain in (distributed) massive mimo -- new fundamental insights on coherency](https://arxiv.org/abs/2206.14752)|[Correctly-Modeling-TX-and-RX-Chain-in-Massive-MIMO](https://github.com/rnissel/Correctly-Modeling-TX-and-RX-Chain-in-Massive-MIMO)| ## 2022-06-29 -|paper|code| -|---|---| -|[aivc: artificial intelligence based video codec](https://arxiv.org/abs/2202.04365)|[AIVC](https://github.com/Orange-OpenSource/AIVC)| -|[stratified multivariate multiscale dispersion entropy for physiological signal analysis](https://arxiv.org/abs/2202.09298)|[smvmde](https://github.com/evangeloskafantaris/smvmde)| +|date|paper|code| +|---|---|---| ## 2022-06-28 -|paper|code| -|---|---| -|[audio dequantization using (co)sparse (non)convex methods](https://arxiv.org/abs/2010.16386)|[audio_dequantization](https://github.com/zawi01/audio_dequantization)| -|[graph neural network aided mu-mimo detectors](https://arxiv.org/abs/2206.09381)|[GNN-based-MIMO-Detection](https://github.com/GNN-based-MIMO-Detection/GNN-based-MIMO-Detection)| -|[adaptive decoding mechanisms for uav-enabled double-uplink coordinated noma](https://arxiv.org/abs/2206.13370)|[uav-noma-adm](https://github.com/thanhluannguyen/uav-noma-adm)| -|[a unified treatment of partial stragglers and sparse matrices in coded matrix computation](https://arxiv.org/abs/2109.12070)|[unifiedtreatment](https://github.com/anindyabijoydas/unifiedtreatment)| -|[mutual-information based optimal experimental design for hyperpolarized $^{13}$c-pyruvate mri](https://arxiv.org/abs/2206.12509)|[hyperpolarizedmri](https://github.com/prashjha/hyperpolarizedmri)| +|date|paper|code| +|---|---|---| +|2206.09381|[graph neural network aided mu-mimo detectors](https://arxiv.org/abs/2206.09381)|[GNN-based-MIMO-Detection](https://github.com/GNN-based-MIMO-Detection/GNN-based-MIMO-Detection)| +|2206.13370|[adaptive decoding mechanisms for uav-enabled double-uplink coordinated noma](https://arxiv.org/abs/2206.13370)|[uav-noma-adm](https://github.com/thanhluannguyen/uav-noma-adm)| +|2206.12509|[mutual-information based optimal experimental design for hyperpolarized $^{13}$c-pyruvate mri](https://arxiv.org/abs/2206.12509)|[hyperpolarizedmri](https://github.com/prashjha/hyperpolarizedmri)| ## 2022-06-27 -|paper|code| -|---|---| -|[a framework of inertial alternating direction method of multipliers for non-convex non-smooth optimization](https://arxiv.org/abs/2102.05433)|[iADMM](https://github.com/nhatpd/iADMM)| -|[frame-type sensitive rdo control for content-adaptive-encoding](https://arxiv.org/abs/2206.11976)|[icip2022](https://gitlab.com/mindfreeze/icip2022)| -|[multi-modal sensor data fusion for in-situ classification of animal behavior using accelerometry and gnss data](https://arxiv.org/abs/2206.12078)|[animal_behavior_classification_acc_gnss](https://github.com/reza219/animal_behavior_classification_acc_gnss)| -|[deep-learning-aided distributed clock synchronization for wireless networks](https://arxiv.org/abs/2206.12097)|[distributed-dnn-aided-time-synchronization](https://github.com/emekagdswill/distributed-dnn-aided-time-synchronization)| -|[accelerated information gradient flow](https://arxiv.org/abs/1909.02102)|[Accelerated-Information-Gradient-flow](https://github.com/YiifeiWang/Accelerated-Information-Gradient-flow)| -|[source localization of graph diffusion via variational autoencoders for graph inverse problems](https://arxiv.org/abs/2206.12327)|[slvae](https://github.com/triplej0079/slvae)| -|[deep generation of heterogeneous networks](https://arxiv.org/abs/2206.12336)|[hgen](https://github.com/lingchen0331/hgen)| +|date|paper|code| +|---|---|---| +|2206.11976|[frame-type sensitive rdo control for content-adaptive-encoding](https://arxiv.org/abs/2206.11976)|[icip2022](https://gitlab.com/mindfreeze/icip2022)| +|2206.12078|[multi-modal sensor data fusion for in-situ classification of animal behavior using accelerometry and gnss data](https://arxiv.org/abs/2206.12078)|[animal_behavior_classification_acc_gnss](https://github.com/reza219/animal_behavior_classification_acc_gnss)| +|2206.12097|[deep-learning-aided distributed clock synchronization for wireless networks](https://arxiv.org/abs/2206.12097)|[distributed-dnn-aided-time-synchronization](https://github.com/emekagdswill/distributed-dnn-aided-time-synchronization)| +|2206.12327|[source localization of graph diffusion via variational autoencoders for graph inverse problems](https://arxiv.org/abs/2206.12327)|[slvae](https://github.com/triplej0079/slvae)| +|2206.12336|[deep generation of heterogeneous networks](https://arxiv.org/abs/2206.12336)|[hgen](https://github.com/lingchen0331/hgen)| ## 2022-06-24 -|paper|code| -|---|---| -|[a large collection of real-world pediatric sleep studies](https://arxiv.org/abs/2102.13284)|[sleep_study](https://github.com/liboyue/sleep_study)| -|[a nonlinear beamforming for enhanced spatiotemporal sensitivity in high frame rate ultrasound flow imaging](https://arxiv.org/abs/2108.02688)|[nonlinear_beamforming](https://github.com/madhavanunni/nonlinear_beamforming)| -|[vehif: an accessible vegetation high-impedance fault data set format](https://arxiv.org/abs/2112.03651)|[hif_vegetation_data](https://github.com/dougpsg/hif_vegetation_data)| -|[arbitrary-length analogs to de bruijn sequences](https://arxiv.org/abs/2108.07759)|[pkl](https://github.com/nelloreward/pkl)| +|date|paper|code| +|---|---|---| ## 2022-06-23 -|paper|code| -|---|---| -|[scaling and scalability: provable nonconvex low-rank tensor estimation from incomplete measurements](https://arxiv.org/abs/2104.14526)|[ScaledGD](https://github.com/Titan-Tong/ScaledGD)| -|[identifying electrocardiogram abnormalities using a handcrafted-rule-enhanced neural network](https://arxiv.org/abs/2206.10592)|[ecg_processing](https://github.com/alwaysbyx/ecg_processing)| -|[model-driven deep learning-based mimo-ofdm detector: design, simulation, and experimental results](https://arxiv.org/abs/2206.10909)|[cg-oamp-net](https://github.com/starainz/cg-oamp-net)| -|[adaptive regularized zero-forcing beamforming in massive mimo with multi-antenna users](https://arxiv.org/abs/2107.00853)|[Adaptive-Regularized-Zero-Forcing-Beamforming-in-Massive-MIMO-with-Multi-Antenna-Users](https://github.com/eugenbobrov/Adaptive-Regularized-Zero-Forcing-Beamforming-in-Massive-MIMO-with-Multi-Antenna-Users)| -|[self-dual hadamard bent sequences](https://arxiv.org/abs/2203.16439)|[hadamard_bent](https://github.com/qomo-cheng/hadamard_bent)| -|[differentially private maximal information coefficients](https://arxiv.org/abs/2206.10685)|[dp-mic](https://github.com/jlazarsfeld/dp-mic)| -|[beating the sum-rate capacity of the binary adder channel with non-signaling correlations](https://arxiv.org/abs/2206.10968)|[mac_ns_lp](https://github.com/pferme/mac_ns_lp)| +|date|paper|code| +|---|---|---| +|2206.10592|[identifying electrocardiogram abnormalities using a handcrafted-rule-enhanced neural network](https://arxiv.org/abs/2206.10592)|[ecg_processing](https://github.com/alwaysbyx/ecg_processing)| +|2206.10909|[model-driven deep learning-based mimo-ofdm detector: design, simulation, and experimental results](https://arxiv.org/abs/2206.10909)|[cg-oamp-net](https://github.com/starainz/cg-oamp-net)| +|2206.10685|[differentially private maximal information coefficients](https://arxiv.org/abs/2206.10685)|[dp-mic](https://github.com/jlazarsfeld/dp-mic)| +|2206.10968|[beating the sum-rate capacity of the binary adder channel with non-signaling correlations](https://arxiv.org/abs/2206.10968)|[mac_ns_lp](https://github.com/pferme/mac_ns_lp)| ## 2022-06-22 -|paper|code| -|---|---| -|[channel estimation in massive mimo under hardware non-linearities: bayesian methods versus deep learning](https://arxiv.org/abs/1911.07316)|[deep-learning-channel-estimation](https://github.com/emilbjornson/deep-learning-channel-estimation)| -|[real-time noise cancellation with deep learning](https://arxiv.org/abs/2011.03466)|[deepNeuronalFilter](https://github.com/berndporr/deepNeuronalFilter)| -|[self-supervised eeg representation learning for automatic sleep staging](https://arxiv.org/abs/2110.15278)|[contrawr](https://github.com/ycq091044/contrawr)| -|[disentangling modes with crossover instantaneous frequencies by synchrosqueezed chirplet transforms, from theory to application](https://arxiv.org/abs/2112.01857)|[synchrosqueezed-chirplet-transforms](https://github.com/ziyuchen7/synchrosqueezed-chirplet-transforms)| -|[a covariant, discrete time-frequency representation tailored for zero-based signal detection](https://arxiv.org/abs/2202.03835)|[kravchuk-transform-and-its-zeros](https://github.com/bpascal-fr/kravchuk-transform-and-its-zeros)| -|[signal decomposition using masked proximal operators](https://arxiv.org/abs/2202.09338)|[signal-decomposition](https://github.com/cvxgrp/signal-decomposition)| -|[deep neural convolutive matrix factorization for articulatory representation decomposition](https://arxiv.org/abs/2204.00465)|[ema_gesture](https://github.com/berkeley-speech-group/ema_gesture)| -|[propagation of measurement and model uncertainties through multiline trl calibration](https://arxiv.org/abs/2206.10209)|[uncertainty-multiline-trl-calibration](https://github.com/ZiadHatab/uncertainty-multiline-trl-calibration)| -|[can we trust our energy measurements? a study on the odroid-xu4](https://arxiv.org/abs/2206.10377)|[energymeasurementanalysis](https://bitbucket.org/uva-sne/energymeasurementanalysis)| -|[a learning aided gradient descent for miso beamforming](https://arxiv.org/abs/2206.10499)|[lagd](https://github.com/xiagroup/lagd)| -|[combating the instability of mutual information-based losses via regularization](https://arxiv.org/abs/2011.07932)|[deconstructing-mine](https://github.com/siyeong-lee/deconstructing-mine)| +|date|paper|code| +|---|---|---| +|2206.10209|[propagation of measurement and model uncertainties through multiline trl calibration](https://arxiv.org/abs/2206.10209)|[uncertainty-multiline-trl-calibration](https://github.com/ZiadHatab/uncertainty-multiline-trl-calibration)| +|2206.10377|[can we trust our energy measurements? a study on the odroid-xu4](https://arxiv.org/abs/2206.10377)|[energymeasurementanalysis](https://bitbucket.org/uva-sne/energymeasurementanalysis)| +|2206.10499|[a learning aided gradient descent for miso beamforming](https://arxiv.org/abs/2206.10499)|[lagd](https://github.com/xiagroup/lagd)| ## 2022-06-20 -|paper|code| -|---|---| -|[plotly-resampler: effective visual analytics for large time series](https://arxiv.org/abs/2206.08703)|[plotly-resampler](https://github.com/predict-idlab/plotly-resampler)| -|[fast lossless neural compression with integer-only discrete flows](https://arxiv.org/abs/2206.08869)|[iodf](https://github.com/thu-ml/iodf)| +|date|paper|code| +|---|---|---| +|2206.08703|[plotly-resampler: effective visual analytics for large time series](https://arxiv.org/abs/2206.08703)|[plotly-resampler](https://github.com/predict-idlab/plotly-resampler)| +|2206.08869|[fast lossless neural compression with integer-only discrete flows](https://arxiv.org/abs/2206.08869)|[iodf](https://github.com/thu-ml/iodf)| ## 2022-06-17 -|paper|code| -|---|---| -|[an accelerated expectation-maximization algorithm for multi-reference alignment](https://arxiv.org/abs/2105.07372)|[synch-em](https://github.com/noamjanco/synch-em)| -|[the portiloop: a deep learning-based open science tool for closed-loop brain stimulation](https://arxiv.org/abs/2107.13473)|[portiloop](https://github.com/mistlab/portiloop)| -|[a real-world radio frequency signal dataset based on lte system and variable channels](https://arxiv.org/abs/2205.12577)|[xsrpdataset](https://github.com/njuptzsp/xsrpdataset)| -|[evaluating short-term forecasting of multiple time series in iot environments](https://arxiv.org/abs/2206.07784)|[multiple-timeseries-forecasting](https://github.com/pcharala/multiple-timeseries-forecasting)| +|date|paper|code| +|---|---|---| +|2206.07784|[evaluating short-term forecasting of multiple time series in iot environments](https://arxiv.org/abs/2206.07784)|[multiple-timeseries-forecasting](https://github.com/pcharala/multiple-timeseries-forecasting)| ## 2022-06-16 -|paper|code| -|---|---| -|[learning the structure of large networked systems obeying conservation laws](https://arxiv.org/abs/2206.07083)|[slnscl](https://github.com/anirudhrayas/slnscl)| -|[on the relationship between ground- and satellite- based global horizontal irradiance](https://arxiv.org/abs/2206.07404)|[solarsatground](https://github.com/ydjoel/solarsatground)| -|[paramnet: a multi-layer parametric network for joint channel estimation and symbol detection](https://arxiv.org/abs/2206.07405)|[ParamNET](https://github.com/vincentchoqueuse/ParamNET)| -|[loss functions for classification using structured entropy](https://arxiv.org/abs/2206.07122)|[resources](https://github.com/numeristical/resources)| +|date|paper|code| +|---|---|---| +|2206.07083|[learning the structure of large networked systems obeying conservation laws](https://arxiv.org/abs/2206.07083)|[slnscl](https://github.com/anirudhrayas/slnscl)| +|2206.07404|[on the relationship between ground- and satellite- based global horizontal irradiance](https://arxiv.org/abs/2206.07404)|[solarsatground](https://github.com/ydjoel/solarsatground)| +|2206.07405|[paramnet: a multi-layer parametric network for joint channel estimation and symbol detection](https://arxiv.org/abs/2206.07405)|[ParamNET](https://github.com/vincentchoqueuse/ParamNET)| +|2206.07122|[loss functions for classification using structured entropy](https://arxiv.org/abs/2206.07122)|[resources](https://github.com/numeristical/resources)| ## 2022-06-15 -|paper|code| -|---|---| -|[pareto-optimal clustering with the primal deterministic information bottleneck](https://arxiv.org/abs/2204.02489)|[pareto_dib](https://github.com/andrewktan/pareto_dib)| +|date|paper|code| +|---|---|---| ## 2022-06-14 -|paper|code| -|---|---| -|[multiple hypothesis testing framework for spatial signals](https://arxiv.org/abs/2108.12314)|[lfdr-smom](https://github.com/mgoelz95/lfdr-smom)| -|[efficient approximation of jacobian matrices involving a non-uniform fast fourier transform (nufft)](https://arxiv.org/abs/2111.02912)|[Bjork](https://github.com/guanhuaw/Bjork)| -|[roadside lidar vehicle detection and tracking using range and intensity background subtraction](https://arxiv.org/abs/2201.04756)|[roadside-lidar-vehicle-detection-and-tracking-background-subtraction](https://github.com/teryzh/roadside-lidar-vehicle-detection-and-tracking-background-subtraction)| -|[integration of physics-based and data-driven models for hyperspectral image unmixing](https://arxiv.org/abs/2206.05508)|[awesome-hyperspectral-image-unmixing](https://github.com/xiuheng-wang/awesome-hyperspectral-image-unmixing)| -|[data-driven denoising of accelerometer signals](https://arxiv.org/abs/2206.05937)|[MEMS-IMU-Denoising](https://github.com/ansfl/MEMS-IMU-Denoising)| -|[reinforcement learning-based placement of charging stations in urban road networks](https://arxiv.org/abs/2206.06011)|[pcrl](https://github.com/ashusao/pcrl)| -|[ris-admm: an admm-based passive and sparse sensing method with interference removal](https://arxiv.org/abs/2206.06172)|[ris-admm](https://github.com/chenpengseu/ris-admm)| -|[ultra-marginal feature importance](https://arxiv.org/abs/2204.09938)|[umfi](https://github.com/joej1997/umfi)| +|date|paper|code| +|---|---|---| +|2206.05508|[integration of physics-based and data-driven models for hyperspectral image unmixing](https://arxiv.org/abs/2206.05508)|[awesome-hyperspectral-image-unmixing](https://github.com/xiuheng-wang/awesome-hyperspectral-image-unmixing)| +|2206.05937|[data-driven denoising of accelerometer signals](https://arxiv.org/abs/2206.05937)|[MEMS-IMU-Denoising](https://github.com/ansfl/MEMS-IMU-Denoising)| +|2206.06011|[reinforcement learning-based placement of charging stations in urban road networks](https://arxiv.org/abs/2206.06011)|[pcrl](https://github.com/ashusao/pcrl)| +|2206.06172|[ris-admm: an admm-based passive and sparse sensing method with interference removal](https://arxiv.org/abs/2206.06172)|[ris-admm](https://github.com/chenpengseu/ris-admm)| ## 2022-06-13 -|paper|code| -|---|---| -|[denoising generalized expectation-consistent approximation for mri image recovery](https://arxiv.org/abs/2206.05049)|[corr-plus-corr](https://github.com/saurav-k-shastri/corr-plus-corr)| +|date|paper|code| +|---|---|---| +|2206.05049|[denoising generalized expectation-consistent approximation for mri image recovery](https://arxiv.org/abs/2206.05049)|[corr-plus-corr](https://github.com/saurav-k-shastri/corr-plus-corr)| ## 2022-06-10 -|paper|code| -|---|---| -|[convolutional dictionary learning by end-to-end training of iterative neural networks](https://arxiv.org/abs/2206.04447)|[convsparsitynns](https://github.com/koflera/convsparsitynns)| -|[aligning random graphs with a sub-tree similarity message-passing algorithm](https://arxiv.org/abs/2112.13079)|[graph_alignment](https://github.com/giovannipiccioli/graph_alignment)| +|date|paper|code| +|---|---|---| +|2206.04447|[convolutional dictionary learning by end-to-end training of iterative neural networks](https://arxiv.org/abs/2206.04447)|[convsparsitynns](https://github.com/koflera/convsparsitynns)| ## 2022-06-09 -|paper|code| -|---|---| -|[technical report (v1.0)--pseudo-random cartesian sampling for dynamic mri](https://arxiv.org/abs/2206.03630)|[cmr-sampling](https://github.com/mihirjoe/cmr-sampling)| -|[perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising](https://arxiv.org/abs/2110.08775)|[perturbative_mean_field_matrix_factorization](https://github.com/sphinxteam/perturbative_mean_field_matrix_factorization)| +|date|paper|code| +|---|---|---| +|2206.03630|[technical report (v1.0)--pseudo-random cartesian sampling for dynamic mri](https://arxiv.org/abs/2206.03630)|[cmr-sampling](https://github.com/mihirjoe/cmr-sampling)| ## 2022-06-08 -|paper|code| -|---|---| -|[extreme compressed sensing of poisson rates from multiple measurements](https://arxiv.org/abs/2103.08711)|[SPoRe](https://github.com/pavankkota/SPoRe)| -|[energy and age pareto optimal trajectories in uav-assisted wireless data collection](https://arxiv.org/abs/2106.03822)|[aoienergyuavtraopt](https://github.com/yuanliaoo/aoienergyuavtraopt)| -|[self-supervised learning for human activity recognition using 700,000 person-days of wearable data](https://arxiv.org/abs/2206.02909)|[ssl-wearables](https://github.com/OxWearables/ssl-wearables)| -|[decomposed linear dynamical systems (dlds) for learning the latent components of neural dynamics](https://arxiv.org/abs/2206.02972)|[dLDS-Discrete-Python-Model](https://github.com/dLDS-Decomposed-Linear-Dynamics/dLDS-Discrete-Python-Model)| -|[decentralized low-latency collaborative inference via ensembles on the edge](https://arxiv.org/abs/2206.03165)|[ensembles-on-the-edge](https://github.com/maymalka10/ensembles-on-the-edge)| -|[computational doob's $h$-transforms for online filtering of discretely observed diffusions](https://arxiv.org/abs/2206.03369)|[CompDoobTransform](https://github.com/jeremyhengjm/CompDoobTransform)| +|date|paper|code| +|---|---|---| +|2206.02909|[self-supervised learning for human activity recognition using 700,000 person-days of wearable data](https://arxiv.org/abs/2206.02909)|[ssl-wearables](https://github.com/OxWearables/ssl-wearables)| +|2206.02972|[decomposed linear dynamical systems (dlds) for learning the latent components of neural dynamics](https://arxiv.org/abs/2206.02972)|[dLDS-Discrete-Python-Model](https://github.com/dLDS-Decomposed-Linear-Dynamics/dLDS-Discrete-Python-Model)| +|2206.03165|[decentralized low-latency collaborative inference via ensembles on the edge](https://arxiv.org/abs/2206.03165)|[ensembles-on-the-edge](https://github.com/maymalka10/ensembles-on-the-edge)| +|2206.03369|[computational doob's $h$-transforms for online filtering of discretely observed diffusions](https://arxiv.org/abs/2206.03369)|[CompDoobTransform](https://github.com/jeremyhengjm/CompDoobTransform)| ## 2022-06-07 -|paper|code| -|---|---| -|[mean subtraction and mode selection in dynamic mode decomposition](https://arxiv.org/abs/2105.03607)|[msub_mdselect_dmd](https://github.com/gowtham-ss-ragavan/msub_mdselect_dmd)| -|[characterizing the slope trade-off: a variational perspective and the donoho-tanner limit](https://arxiv.org/abs/2105.13302)|[SLOPE_AMP](https://github.com/woodyx218/SLOPE_AMP)| -|[dcase 2021 task 3: spectrotemporally-aligned features for polyphonic sound event localization and detection](https://arxiv.org/abs/2106.15190)|[SALSA](https://github.com/thomeou/SALSA)| -|[da-music: data-driven doa estimation via deep augmented music algorithm](https://arxiv.org/abs/2109.10581)|[tsp22](https://github.com/da-music/tsp22)| -|[mical: mutual information-based cnn-aided learned factor](https://arxiv.org/abs/2206.02298)|[cnn-aided-factor-graphs-with-estimated-mutual-information-features-for-seizure-detection-mical](https://github.com/bsalafia/cnn-aided-factor-graphs-with-estimated-mutual-information-features-for-seizure-detection-mical)| -|[on low-rank trace regression under general sampling distribution](https://arxiv.org/abs/1904.08576)|[cv-impute](https://github.com/mohsenbayati/cv-impute)| -|[blind super-resolution of point sources via projected gradient descent](https://arxiv.org/abs/2112.01077)|[pgdvhl](https://github.com/jcchen2017/pgdvhl)| -|[supervised contrastive csi representation learning for massive mimo positioning](https://arxiv.org/abs/2204.12796)|[SupConCSI](https://github.com/dengjunquan/SupConCSI)| -|[an information upper bound for probability sensitivity](https://arxiv.org/abs/2206.02274)|[ProbSensitivityInfoBound](https://github.com/longitude-jyang/ProbSensitivityInfoBound)| -|[minimizing the expected posterior entropy yields optimal summary statistics](https://arxiv.org/abs/2206.02340)|[summaries](https://github.com/tillahoffmann/summaries)| +|date|paper|code| +|---|---|---| +|2206.02298|[mical: mutual information-based cnn-aided learned factor](https://arxiv.org/abs/2206.02298)|[cnn-aided-factor-graphs-with-estimated-mutual-information-features-for-seizure-detection-mical](https://github.com/bsalafia/cnn-aided-factor-graphs-with-estimated-mutual-information-features-for-seizure-detection-mical)| +|2206.02274|[an information upper bound for probability sensitivity](https://arxiv.org/abs/2206.02274)|[ProbSensitivityInfoBound](https://github.com/longitude-jyang/ProbSensitivityInfoBound)| +|2206.02340|[minimizing the expected posterior entropy yields optimal summary statistics](https://arxiv.org/abs/2206.02340)|[summaries](https://github.com/tillahoffmann/summaries)| ## 2022-06-06 -|paper|code| -|---|---| -|[approximation of images via generalized higher order singular value decomposition over finite-dimensional commutative semisimple algebra](https://arxiv.org/abs/2202.00450)|[talgebra](https://github.com/liaoliang2020/talgebra)| -|[lossy gradient compression: how much accuracy can one bit buy?](https://arxiv.org/abs/2202.02812)|[fl_rd](https://github.com/sadafsk/fl_rd)| -|[rashomon capacity: a metric for predictive multiplicity in probabilistic classification](https://arxiv.org/abs/2206.01295)|[rashomon-capacity](https://github.com/hsianghsu/rashomon-capacity)| +|date|paper|code| +|---|---|---| +|2206.01295|[rashomon capacity: a metric for predictive multiplicity in probabilistic classification](https://arxiv.org/abs/2206.01295)|[rashomon-capacity](https://github.com/hsianghsu/rashomon-capacity)| ## 2022-06-03 -|paper|code| -|---|---| -|[design of an optimal testbed for tracking of tagged marine megafauna](https://arxiv.org/abs/2204.04155)|[receiver-deployment](https://github.com/kerentalmon/receiver-deployment)| +|date|paper|code| +|---|---|---| ## 2022-06-02 -|paper|code| -|---|---| -|[zero-shot self-supervised learning for mri reconstruction](https://arxiv.org/abs/2102.07737)|[ZS-SSL](https://github.com/byaman14/ZS-SSL)| -|[the representation jensen-r\'enyi divergence](https://arxiv.org/abs/2112.01583)|[jensen-renyi-divergence](https://github.com/uk-cliplab/jensen-renyi-divergence)| +|date|paper|code| +|---|---|---| ## 2022-06-01 -|paper|code| -|---|---| -|[metassd: meta-learned self-supervised detection](https://arxiv.org/abs/2205.15271)|[metassd](https://github.com/ml-postech/metassd)| -|[channel model mismatch analysis for xl-mimo systems from a localization perspective](https://arxiv.org/abs/2205.15417)|[radio_localization](https://github.com/chenhui07c8/radio_localization)| -|[rethinking graph neural networks for anomaly detection](https://arxiv.org/abs/2205.15508)|[rethinking-anomaly-detection](https://github.com/squareroot3/rethinking-anomaly-detection)| -|[generalised implicit neural representations](https://arxiv.org/abs/2205.15674)|[ginr](https://github.com/danielegrattarola/ginr)| -|[information fragmentation, encryption and information flow in complex biological networks](https://arxiv.org/abs/2105.13585)|[fragmentation_replication_instructions](https://github.com/cliff-bohm/fragmentation_replication_instructions)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/07.md b/archives/2022/07.md index 22835cb3..f0390bf2 100644 --- a/archives/2022/07.md +++ b/archives/2022/07.md @@ -1,149 +1,109 @@ # July 2022 Archive ## 2022-07-29 -|paper|code| -|---|---| -|[wivelo: fine-grained walking velocity estimation for wi-fi passive tracking](https://arxiv.org/abs/2207.14072)|[WiVelo_SECON22](https://github.com/liecn/WiVelo_SECON22)| -|[one-nearest-neighbor search is all you need for minimax optimal regression and classification](https://arxiv.org/abs/2202.02464)|[split-knn-rules](https://github.com/jongharyu/split-knn-rules)| -|[pareto-optimal clustering with the primal deterministic information bottleneck](https://arxiv.org/abs/2204.02489)|[pareto_dib](https://github.com/andrewktan/pareto_dib)| +|date|paper|code| +|---|---|---| +|2207.14072|[wivelo: fine-grained walking velocity estimation for wi-fi passive tracking](https://arxiv.org/abs/2207.14072)|[WiVelo_SECON22](https://github.com/liecn/WiVelo_SECON22)| ## 2022-07-28 -|paper|code| -|---|---| -|[graph neural networks for communication networks: context, use cases and opportunities](https://arxiv.org/abs/2112.14792)|[GNNPapersCommNets](https://github.com/BNN-UPC/GNNPapersCommNets)| +|date|paper|code| +|---|---|---| ## 2022-07-27 -|paper|code| -|---|---| -|[sparse signal models for data augmentation in deep learning atr](https://arxiv.org/abs/2012.09284)|[mstar_data_aug](https://github.com/SENSE-Lab-OSU/mstar_data_aug)| -|[few-shot domain adaptation for end-to-end communication](https://arxiv.org/abs/2108.00874)|[domain-adaptation-autoencoder](https://github.com/jayaram-r/domain-adaptation-autoencoder)| -|[time majority voting, a pc-based eeg classifier for non-expert users](https://arxiv.org/abs/2207.12662)|[time_majority_voting](https://github.com/guangyaodou/time_majority_voting)| -|[dynamic measurement of structural entropy for dynamic graphs](https://arxiv.org/abs/2207.12653)|[incre-se](https://github.com/yangrunze1013/incre-se)| +|date|paper|code| +|---|---|---| +|2207.12662|[time majority voting, a pc-based eeg classifier for non-expert users](https://arxiv.org/abs/2207.12662)|[time_majority_voting](https://github.com/guangyaodou/time_majority_voting)| +|2207.12653|[dynamic measurement of structural entropy for dynamic graphs](https://arxiv.org/abs/2207.12653)|[incre-se](https://github.com/yangrunze1013/incre-se)| ## 2022-07-26 -|paper|code| -|---|---| -|[task-oriented communication for multi-device cooperative edge inference](https://arxiv.org/abs/2109.00172)|[vddib-sr](https://github.com/shaojiawei07/vddib-sr)| -|[end-to-end signal classification in signed cumulative distribution transform space](https://arxiv.org/abs/2205.00348)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| -|[a learning aided flexible gradient descent approach to miso beamforming](https://arxiv.org/abs/2206.10499)|[lagd](https://github.com/xiagroup/lagd)| -|[openran gym: ai/ml development, data collection, and testing for o-ran on pawr platforms](https://arxiv.org/abs/2207.12362)|[colosseum-near-rt-ric](https://github.com/wineslab/colosseum-near-rt-ric)| -|[toward reliable signals decoding for electroencephalogram: a benchmark study to eegnex](https://arxiv.org/abs/2207.12369)|[eegnex](https://github.com/chenxiachan/eegnex)| -|[quantum advantage in learning from experiments](https://arxiv.org/abs/2112.00778)|[ReCirq](https://github.com/quantumlib/ReCirq)| -|[on confidence sequences for bounded random processes via universal gambling strategies](https://arxiv.org/abs/2207.12382)|[confidence-sequence-via-gambling](https://github.com/jongharyu/confidence-sequence-via-gambling)| +|date|paper|code| +|---|---|---| +|2207.12362|[openran gym: ai/ml development, data collection, and testing for o-ran on pawr platforms](https://arxiv.org/abs/2207.12362)|[colosseum-near-rt-ric](https://github.com/wineslab/colosseum-near-rt-ric)| +|2207.12369|[toward reliable signals decoding for electroencephalogram: a benchmark study to eegnex](https://arxiv.org/abs/2207.12369)|[eegnex](https://github.com/chenxiachan/eegnex)| +|2207.12382|[on confidence sequences for bounded random processes via universal gambling strategies](https://arxiv.org/abs/2207.12382)|[confidence-sequence-via-gambling](https://github.com/jongharyu/confidence-sequence-via-gambling)| ## 2022-07-25 -|paper|code| -|---|---| -|[explainable ai algorithms for vibration data-based fault detection: use case-adadpted methods and critical evaluation](https://arxiv.org/abs/2207.10732)|[xai-vibration-fault-detection](https://github.com/o-mey/xai-vibration-fault-detection)| +|date|paper|code| +|---|---|---| +|2207.10732|[explainable ai algorithms for vibration data-based fault detection: use case-adadpted methods and critical evaluation](https://arxiv.org/abs/2207.10732)|[xai-vibration-fault-detection](https://github.com/o-mey/xai-vibration-fault-detection)| ## 2022-07-22 -|paper|code| -|---|---| -|[neural architecture search for spiking neural networks](https://arxiv.org/abs/2201.10355)|[neural-architecture-search-for-spiking-neural-networks](https://github.com/intelligent-computing-lab-yale/neural-architecture-search-for-spiking-neural-networks)| -|[trajectory pmb filters for extended object tracking using belief propagation](https://arxiv.org/abs/2207.10164)|[trajectory-pmb-eot-bp](https://github.com/yuhsuansia/trajectory-pmb-eot-bp)| -|[multi resolution analysis (mra) for approximate self-attention](https://arxiv.org/abs/2207.10284)|[mra-attention](https://github.com/mlpen/mra-attention)| +|date|paper|code| +|---|---|---| +|2207.10164|[trajectory pmb filters for extended object tracking using belief propagation](https://arxiv.org/abs/2207.10164)|[trajectory-pmb-eot-bp](https://github.com/yuhsuansia/trajectory-pmb-eot-bp)| +|2207.10284|[multi resolution analysis (mra) for approximate self-attention](https://arxiv.org/abs/2207.10284)|[mra-attention](https://github.com/mlpen/mra-attention)| ## 2022-07-21 -|paper|code| -|---|---| -|[beats: an open-source, high-precision, multi-channel eeg acquisition tool system](https://arxiv.org/abs/2203.02102)|[beats](https://github.com/buptanteeg/beats)| +|date|paper|code| +|---|---|---| ## 2022-07-20 -|paper|code| -|---|---| -|[a large collection of real-world pediatric sleep studies](https://arxiv.org/abs/2102.13284)|[sleep_study](https://github.com/liboyue/sleep_study)| -|[do not sleep on linear models: simple and interpretable techniques outperform deep learning for sleep scoring](https://arxiv.org/abs/2207.07753)|[sleep-linear](https://github.com/predict-idlab/sleep-linear)| -|[unrolled algorithms for group synchronization](https://arxiv.org/abs/2207.09418)|[unrolling_synchronization](https://github.com/noamjanco/unrolling_synchronization)| -|[automated black-box boundary value detection](https://arxiv.org/abs/2207.09065)|[repro_autobva](https://github.com/feldob/repro_autobva)| +|date|paper|code| +|---|---|---| +|2207.07753|[do not sleep on linear models: simple and interpretable techniques outperform deep learning for sleep scoring](https://arxiv.org/abs/2207.07753)|[sleep-linear](https://github.com/predict-idlab/sleep-linear)| +|2207.09418|[unrolled algorithms for group synchronization](https://arxiv.org/abs/2207.09418)|[unrolling_synchronization](https://github.com/noamjanco/unrolling_synchronization)| +|2207.09065|[automated black-box boundary value detection](https://arxiv.org/abs/2207.09065)|[repro_autobva](https://github.com/feldob/repro_autobva)| ## 2022-07-19 -|paper|code| -|---|---| -|[music source separation with generative flow](https://arxiv.org/abs/2204.09079)|[generativesourceseparation](https://github.com/gzhu06/generativesourceseparation)| -|[plotly-resampler: effective visual analytics for large time series](https://arxiv.org/abs/2206.08703)|[plotly-resampler](https://github.com/predict-idlab/plotly-resampler)| -|[segment-level metric learning for few-shot bioacoustic event detection](https://arxiv.org/abs/2207.07773)|[dcase_2022_task_5](https://github.com/haoheliu/dcase_2022_task_5)| -|[deep learning and its applications to wifi human sensing: a benchmark and a tutorial](https://arxiv.org/abs/2207.07859)|[wifi-csi-sensing-benchmark](https://github.com/chenxinyan-sg/wifi-csi-sensing-benchmark)| -|[correlated age-of-information bandits](https://arxiv.org/abs/2011.05032)|[Correlated-AoI-Bandits](https://github.com/ishank-juneja/Correlated-AoI-Bandits)| -|[the signed cumulative distribution transform for 1-d signal analysis and classification](https://arxiv.org/abs/2106.02146)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| -|[tight concentrations and confidence sequences from the regret of universal portfolio](https://arxiv.org/abs/2110.14099)|[precise](https://github.com/bremen79/precise)| -|[ultra-marginal feature importance](https://arxiv.org/abs/2204.09938)|[umfi](https://github.com/joej1997/umfi)| -|[interpretable collective intelligence of non-rational human agents](https://arxiv.org/abs/2204.13424)|[collective-intelligence-research](https://github.com/nicknick85/collective-intelligence-research)| +|date|paper|code| +|---|---|---| +|2207.07773|[segment-level metric learning for few-shot bioacoustic event detection](https://arxiv.org/abs/2207.07773)|[dcase_2022_task_5](https://github.com/haoheliu/dcase_2022_task_5)| +|2207.07859|[deep learning and its applications to wifi human sensing: a benchmark and a tutorial](https://arxiv.org/abs/2207.07859)|[wifi-csi-sensing-benchmark](https://github.com/chenxinyan-sg/wifi-csi-sensing-benchmark)| ## 2022-07-18 -|paper|code| -|---|---| -|[correctly modeling tx and rx chain in (distributed) massive mimo -- new fundamental insights on coherency](https://arxiv.org/abs/2206.14752)|[Correctly-Modeling-TX-and-RX-Chain-in-Massive-MIMO](https://github.com/rnissel/Correctly-Modeling-TX-and-RX-Chain-in-Massive-MIMO)| -|[open-source software for electrical engineering applications requiring consideration of electrodynamics: elecode](https://arxiv.org/abs/2207.06908)|[elecode](https://gitlab.com/dmika/elecode)| -|[deepsolar tracker: towards unsupervised assessment with open-source data of the accuracy of deep learning-based distributed pv mapping](https://arxiv.org/abs/2207.07466)|[dsfrance](https://github.com/gabrielkasmi/dsfrance)| -|[outlier detection of vital sign trajectories from covid-19 patients](https://arxiv.org/abs/2207.07572)|[outlier-detection-recap-data](https://github.com/sara-es/outlier-detection-recap-data)| +|date|paper|code| +|---|---|---| +|2207.06908|[open-source software for electrical engineering applications requiring consideration of electrodynamics: elecode](https://arxiv.org/abs/2207.06908)|[elecode](https://gitlab.com/dmika/elecode)| +|2207.07466|[deepsolar tracker: towards unsupervised assessment with open-source data of the accuracy of deep learning-based distributed pv mapping](https://arxiv.org/abs/2207.07466)|[dsfrance](https://github.com/gabrielkasmi/dsfrance)| +|2207.07572|[outlier detection of vital sign trajectories from covid-19 patients](https://arxiv.org/abs/2207.07572)|[outlier-detection-recap-data](https://github.com/sara-es/outlier-detection-recap-data)| ## 2022-07-15 -|paper|code| -|---|---| -|[self-supervised speaker recognition with loss-gated learning](https://arxiv.org/abs/2110.03869)|[loss-gated-learning](https://github.com/taoruijie/loss-gated-learning)| -|[reconstruction of time-varying graph signals via sobolev smoothness](https://arxiv.org/abs/2207.06439)|[graphtrss](https://github.com/jhonygiraldo/graphtrss)| -|[few-shot specific emitter identification via deep metric ensemble learning](https://arxiv.org/abs/2207.06592)|[few-shot-specific-emitter-identification-via-deep-metric-ensemble-learning](https://github.com/beechburgpiestar/few-shot-specific-emitter-identification-via-deep-metric-ensemble-learning)| -|[a neural-network framework for the design of individualised hearing-loss compensation](https://arxiv.org/abs/2207.07091)|[connear_periphery](https://github.com/hearingtechnology/connear_periphery)| -|[analytic relations between complex networks: encoding, decoding, and causality](https://arxiv.org/abs/2207.06606)|[analytic-relations-between-complex-networks-encoding-decoding-and-causality](https://github.com/doloming/analytic-relations-between-complex-networks-encoding-decoding-and-causality)| -|[an asymmetric contrastive loss for handling imbalanced datasets](https://arxiv.org/abs/2207.07080)|[asymmetric-cl](https://github.com/valentinovito/asymmetric-cl)| +|date|paper|code| +|---|---|---| +|2207.06439|[reconstruction of time-varying graph signals via sobolev smoothness](https://arxiv.org/abs/2207.06439)|[graphtrss](https://github.com/jhonygiraldo/graphtrss)| +|2207.06592|[few-shot specific emitter identification via deep metric ensemble learning](https://arxiv.org/abs/2207.06592)|[few-shot-specific-emitter-identification-via-deep-metric-ensemble-learning](https://github.com/beechburgpiestar/few-shot-specific-emitter-identification-via-deep-metric-ensemble-learning)| +|2207.07091|[a neural-network framework for the design of individualised hearing-loss compensation](https://arxiv.org/abs/2207.07091)|[connear_periphery](https://github.com/hearingtechnology/connear_periphery)| +|2207.06606|[analytic relations between complex networks: encoding, decoding, and causality](https://arxiv.org/abs/2207.06606)|[analytic-relations-between-complex-networks-encoding-decoding-and-causality](https://github.com/doloming/analytic-relations-between-complex-networks-encoding-decoding-and-causality)| +|2207.07080|[an asymmetric contrastive loss for handling imbalanced datasets](https://arxiv.org/abs/2207.07080)|[asymmetric-cl](https://github.com/valentinovito/asymmetric-cl)| ## 2022-07-13 -|paper|code| -|---|---| -|[a covariant, discrete time-frequency representation tailored for zero-based signal detection](https://arxiv.org/abs/2202.03835)|[kravchuk-transform-and-its-zeros](https://github.com/bpascal-fr/kravchuk-transform-and-its-zeros)| -|[an automated theorem proving framework for information-theoretic results](https://arxiv.org/abs/2101.12370)|[psitip](https://github.com/cheuktingli/psitip)| -|[on the distribution of the information density of gaussian random vectors: explicit formulas and tight approximations](https://arxiv.org/abs/2105.03925)|[information-density](https://gitlab.com/infth/information-density)| -|[quantum advantage in learning from experiments](https://arxiv.org/abs/2112.00778)|[ReCirq](https://github.com/quantumlib/ReCirq)| +|date|paper|code| +|---|---|---| ## 2022-07-12 -|paper|code| -|---|---| -|[towards off-the-grid algorithms for total variation regularized inverse problems](https://arxiv.org/abs/2104.06706)|[tvsfw](https://github.com/rpetit/tvsfw)| -|[frame-type sensitive rdo control for content-adaptive-encoding](https://arxiv.org/abs/2206.11976)|[icip2022](https://gitlab.com/mindfreeze/icip2022)| -|[multi-channel deep networks for block-based image compressive sensing](https://arxiv.org/abs/1908.11221)|[deepbcs](https://github.com/siwangzhou/deepbcs)| -|[an information upper bound for probability sensitivity](https://arxiv.org/abs/2206.02274)|[ProbSensitivityInfoBound](https://github.com/longitude-jyang/ProbSensitivityInfoBound)| -|[l$_0$onie: compressing coins with l$_0$-constraints](https://arxiv.org/abs/2207.04144)|[l0onie](https://github.com/juan43ramirez/l0onie)| +|date|paper|code| +|---|---|---| +|2207.04144|[l$_0$onie: compressing coins with l$_0$-constraints](https://arxiv.org/abs/2207.04144)|[l0onie](https://github.com/juan43ramirez/l0onie)| ## 2022-07-11 -|paper|code| -|---|---| -|[mutual-information based optimal experimental design for hyperpolarized $^{13}$c-pyruvate mri](https://arxiv.org/abs/2206.12509)|[hyperpolarizedmri](https://github.com/prashjha/hyperpolarizedmri)| +|date|paper|code| +|---|---|---| ## 2022-07-08 -|paper|code| -|---|---| -|[visual sensor network stimulation model identification via gaussian mixture model and deep embedded features](https://arxiv.org/abs/2201.06804)|[vsn-with-ae](https://github.com/luca-varotto/vsn-with-ae)| -|[variance in classifying affective state via electrocardiogram and photoplethysmography](https://arxiv.org/abs/2207.02916)|[emo_phys_eval](https://github.com/zacdair/emo_phys_eval)| -|[morpi: mobile robot pure inertial navigation](https://arxiv.org/abs/2207.02982)|[morpi](https://github.com/ansfl/morpi)| -|[topologically driven methods for construction of multi-edge type (multigraph with nodes puncturing) quasi-cyclic low-density parity-check codes for wireless channel, wdm long-haul and archival holographic memory](https://arxiv.org/abs/2011.14753)|[trapping-sets-enumeration](https://github.com/Lcrypto/trapping-sets-enumeration)| +|date|paper|code| +|---|---|---| +|2207.02916|[variance in classifying affective state via electrocardiogram and photoplethysmography](https://arxiv.org/abs/2207.02916)|[emo_phys_eval](https://github.com/zacdair/emo_phys_eval)| +|2207.02982|[morpi: mobile robot pure inertial navigation](https://arxiv.org/abs/2207.02982)|[morpi](https://github.com/ansfl/morpi)| ## 2022-07-07 -|paper|code| -|---|---| -|[state-augmented learnable algorithms for resource management in wireless networks](https://arxiv.org/abs/2207.02242)|[stateaugmented_rrm_gnn](https://github.com/navid-naderi/stateaugmented_rrm_gnn)| +|date|paper|code| +|---|---|---| +|2207.02242|[state-augmented learnable algorithms for resource management in wireless networks](https://arxiv.org/abs/2207.02242)|[stateaugmented_rrm_gnn](https://github.com/navid-naderi/stateaugmented_rrm_gnn)| ## 2022-07-06 -|paper|code| -|---|---| -|[near out-of-distribution detection for low-resolution radar micro-doppler signatures](https://arxiv.org/abs/2205.07869)|[near-ood-doppler-signatures](https://github.com/blupblupblup/near-ood-doppler-signatures)| -|[identification of distorted rf components via deep multi-task learning](https://arxiv.org/abs/2207.01707)|[hardware-problem-identification](https://github.com/mehmetaaygul/hardware-problem-identification)| -|[content addressable memory without catastrophic forgetting by heteroassociation with a fixed scaffold](https://arxiv.org/abs/2202.00159)|[mesh](https://github.com/fietelab/mesh)| -|[modeling and correcting bias in sequential evaluation](https://arxiv.org/abs/2205.01607)|[sequential-bias](https://github.com/jingyanw/sequential-bias)| +|date|paper|code| +|---|---|---| +|2207.01707|[identification of distorted rf components via deep multi-task learning](https://arxiv.org/abs/2207.01707)|[hardware-problem-identification](https://github.com/mehmetaaygul/hardware-problem-identification)| ## 2022-07-05 -|paper|code| -|---|---| -|[hardware architecture for high throughput event visual data filtering with matrix of iir filters algorithm](https://arxiv.org/abs/2207.00860)|[dvs_filtermatrixiir](https://github.com/vision-agh/dvs_filtermatrixiir)| -|[learning noise with generative adversarial networks: explorations with classical random process models](https://arxiv.org/abs/2207.01110)|[noisegan](https://github.com/usnistgov/noisegan)| -|[task-oriented self-supervised learning for anomaly detection in electroencephalography](https://arxiv.org/abs/2207.01391)|[eeg-ad](https://github.com/ironing/eeg-ad)| -|[semi-blind source separation using convolutive transfer function for nonlinear acoustic echo cancellation](https://arxiv.org/abs/2207.01556)|[audio-samples2](https://github.com/chengguoliang0/audio-samples2)| -|[encoding of probability distributions for asymmetric numeral systems](https://arxiv.org/abs/2106.06438)|[AsymmetricNumeralSystemsToolkit](https://github.com/JarekDuda/AsymmetricNumeralSystemsToolkit)| +|date|paper|code| +|---|---|---| +|2207.00860|[hardware architecture for high throughput event visual data filtering with matrix of iir filters algorithm](https://arxiv.org/abs/2207.00860)|[dvs_filtermatrixiir](https://github.com/vision-agh/dvs_filtermatrixiir)| +|2207.01110|[learning noise with generative adversarial networks: explorations with classical random process models](https://arxiv.org/abs/2207.01110)|[noisegan](https://github.com/usnistgov/noisegan)| +|2207.01391|[task-oriented self-supervised learning for anomaly detection in electroencephalography](https://arxiv.org/abs/2207.01391)|[eeg-ad](https://github.com/ironing/eeg-ad)| +|2207.01556|[semi-blind source separation using convolutive transfer function for nonlinear acoustic echo cancellation](https://arxiv.org/abs/2207.01556)|[audio-samples2](https://github.com/chengguoliang0/audio-samples2)| ## 2022-07-01 -|paper|code| -|---|---| -|[stride: a flexible platform for high-performance ultrasound computed tomography](https://arxiv.org/abs/2110.03345)|[stride](https://github.com/trustimaging/stride)| -|[leveraging joint-diagonalization in transform-learning nmf](https://arxiv.org/abs/2112.05664)|[tlnmf-tsp](https://github.com/sixin-zh/tlnmf-tsp)| -|[propagation of measurement and model uncertainties through multiline trl calibration](https://arxiv.org/abs/2206.10209)|[uncertainty-multiline-trl-calibration](https://github.com/ZiadHatab/uncertainty-multiline-trl-calibration)| -|[federated over-air subspace tracking from incomplete and corrupted data](https://arxiv.org/abs/2002.12873)|[distributed-pca](https://github.com/praneethmurthy/distributed-pca)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/08.md b/archives/2022/08.md index 47a67dfd..2bf10537 100644 --- a/archives/2022/08.md +++ b/archives/2022/08.md @@ -1,164 +1,126 @@ # August 2022 Archive ## 2022-08-31 -|paper|code| -|---|---| -|[gridless 3d recovery of image sources from room impulse responses](https://arxiv.org/abs/2208.14017)|[acoustic-sfw](https://github.com/sprunckt/acoustic-sfw)| +|date|paper|code| +|---|---|---| +|2208.14017|[gridless 3d recovery of image sources from room impulse responses](https://arxiv.org/abs/2208.14017)|[acoustic-sfw](https://github.com/sprunckt/acoustic-sfw)| ## 2022-08-30 -|paper|code| -|---|---| -|[openfwi: large-scale multi-structural benchmark datasets for seismic full waveform inversion](https://arxiv.org/abs/2111.02926)|[openfwi](https://github.com/lanl/openfwi)| -|[robust distributed bayesian learning with stragglers via consensus monte carlo](https://arxiv.org/abs/2112.09794)|[straggler-resilient-cmc](https://github.com/kclip/straggler-resilient-cmc)| -|[integration of physics-based and data-driven models for hyperspectral image unmixing](https://arxiv.org/abs/2206.05508)|[awesome-hyperspectral-image-unmixing](https://github.com/xiuheng-wang/awesome-hyperspectral-image-unmixing)| -|[cast: a toolchain for creating and characterizing realistic wireless network emulation scenarios](https://arxiv.org/abs/2208.03993)|[cast](https://github.com/wineslab/cast)| -|[latent signal models: learning compact representations of signal evolution for improved time-resolved, multi-contrast mri](https://arxiv.org/abs/2208.13003)|[latent_signal_models_mrm_2022](https://github.com/yaminarefeen/latent_signal_models_mrm_2022)| -|[adjacent-bits-swapped polar codes: a new code construction to speed up polarization](https://arxiv.org/abs/2202.04454)|[abs-polar](https://github.com/plumjelly/abs-polar)| +|date|paper|code| +|---|---|---| +|2208.03993|[cast: a toolchain for creating and characterizing realistic wireless network emulation scenarios](https://arxiv.org/abs/2208.03993)|[cast](https://github.com/wineslab/cast)| +|2208.13003|[latent signal models: learning compact representations of signal evolution for improved time-resolved, multi-contrast mri](https://arxiv.org/abs/2208.13003)|[latent_signal_models_mrm_2022](https://github.com/yaminarefeen/latent_signal_models_mrm_2022)| ## 2022-08-29 -|paper|code| -|---|---| -|[gcns-net: a graph convolutional neural network approach for decoding time-resolved eeg motor imagery signals](https://arxiv.org/abs/2006.08924)|[EEG-DL](https://github.com/SuperBruceJia/EEG-DL)| +|date|paper|code| +|---|---|---| ## 2022-08-26 -|paper|code| -|---|---| -|[ecg-atk-gan: robustness against adversarial attacks on ecgs using conditional generative adversarial networks](https://arxiv.org/abs/2110.09983)|[ecg-atk-gan](https://github.com/farihahossain/ecg-atk-gan)| -|[ensemble learning using individual neonatal data for seizure detection](https://arxiv.org/abs/2204.07043)|[distributed-nsda](https://github.com/anaborovac/distributed-nsda)| -|[eeg4students: an experimental design for eeg data collection and machine learning analysis](https://arxiv.org/abs/2208.11743)|[eeg4students](https://github.com/guangyaodou/eeg4students)| -|[approximation of images via generalized higher order singular value decomposition over finite-dimensional commutative semisimple algebra](https://arxiv.org/abs/2202.00450)|[talgebra](https://github.com/liaoliang2020/talgebra)| +|date|paper|code| +|---|---|---| +|2208.11743|[eeg4students: an experimental design for eeg data collection and machine learning analysis](https://arxiv.org/abs/2208.11743)|[eeg4students](https://github.com/guangyaodou/eeg4students)| ## 2022-08-25 -|paper|code| -|---|---| -|[trajectory pmb filters for extended object tracking using belief propagation](https://arxiv.org/abs/2207.10164)|[trajectory-pmb-eot-bp](https://github.com/yuhsuansia/trajectory-pmb-eot-bp)| -|[enhancing deep learning performance of massive mimo csi feedback](https://arxiv.org/abs/2208.11333)|[jpts](https://github.com/sijieji/jpts)| +|date|paper|code| +|---|---|---| +|2208.11333|[enhancing deep learning performance of massive mimo csi feedback](https://arxiv.org/abs/2208.11333)|[jpts](https://github.com/sijieji/jpts)| ## 2022-08-24 -|paper|code| -|---|---| -|[leveraging joint-diagonalization in transform-learning nmf](https://arxiv.org/abs/2112.05664)|[tlnmf-tsp](https://github.com/sixin-zh/tlnmf-tsp)| -|[arrhythmia classification using cgan-augmented ecg signals](https://arxiv.org/abs/2202.00569)|[augmentation-of-ecg-training-dataset-with-cgan](https://github.com/mah533/augmentation-of-ecg-training-dataset-with-cgan)| -|[quantum message-passing algorithm for optimal and efficient decoding](https://arxiv.org/abs/2109.08170)|[quantum-message-passing-paper](https://github.com/chripiv/quantum-message-passing-paper)| +|date|paper|code| +|---|---|---| ## 2022-08-23 -|paper|code| -|---|---| -|[exploiting temporal structures of cyclostationary signals for data-driven single-channel source separation](https://arxiv.org/abs/2208.10325)|[scss_csgaussian](https://github.com/rfchallenge/scss_csgaussian)| -|[survey of machine learning techniques to predict heartbeat arrhythmias](https://arxiv.org/abs/2208.10463)|[ECG_Predictor](https://github.com/innovationcore/ECG_Predictor)| -|[universal caching](https://arxiv.org/abs/2205.04860)|[universalcaching](https://github.com/ativjoshi/universalcaching)| +|date|paper|code| +|---|---|---| +|2208.10325|[exploiting temporal structures of cyclostationary signals for data-driven single-channel source separation](https://arxiv.org/abs/2208.10325)|[scss_csgaussian](https://github.com/rfchallenge/scss_csgaussian)| +|2208.10463|[survey of machine learning techniques to predict heartbeat arrhythmias](https://arxiv.org/abs/2208.10463)|[ECG_Predictor](https://github.com/innovationcore/ECG_Predictor)| ## 2022-08-22 -|paper|code| -|---|---| -|[echofilter: a deep learning segmentation model improves the automation, standardization, and timeliness for post-processing echosounder data in tidal energy streams](https://arxiv.org/abs/2202.09648)|[echofilter](https://github.com/deepsenseca/echofilter)| -|[a unified algorithmic framework for distributed adaptive signal and feature fusion problems -- part ii: convergence properties](https://arxiv.org/abs/2208.09088)|[DASF_toolbox](https://github.com/AlexanderBertrandLab/DASF_toolbox)| +|date|paper|code| +|---|---|---| +|2208.09088|[a unified algorithmic framework for distributed adaptive signal and feature fusion problems -- part ii: convergence properties](https://arxiv.org/abs/2208.09088)|[DASF_toolbox](https://github.com/AlexanderBertrandLab/DASF_toolbox)| ## 2022-08-19 -|paper|code| -|---|---| -|[fast off-the-grid sparse recovery with over-parametrized projected gradient descent](https://arxiv.org/abs/2202.13757)|[opcomp_sparse_recovery](https://github.com/pjbenard/opcomp_sparse_recovery)| -|[ensemble learning using individual neonatal data for seizure detection](https://arxiv.org/abs/2204.07043)|[distributed-nsda](https://github.com/anaborovac/distributed-nsda)| -|[psychophysiological arousal in young children who stutter: an interpretable ai approach](https://arxiv.org/abs/2208.08859)|[modality-wise-multple-instance-learning](https://github.com/asalekin-ubiquitouslab/modality-wise-multple-instance-learning)| -|[a unified algorithmic framework for distributed adaptive signal and feature fusion problems -- part i: algorithm derivation](https://arxiv.org/abs/2208.08867)|[DASF_toolbox](https://github.com/AlexanderBertrandLab/DASF_toolbox)| +|date|paper|code| +|---|---|---| +|2208.08859|[psychophysiological arousal in young children who stutter: an interpretable ai approach](https://arxiv.org/abs/2208.08859)|[modality-wise-multple-instance-learning](https://github.com/asalekin-ubiquitouslab/modality-wise-multple-instance-learning)| +|2208.08867|[a unified algorithmic framework for distributed adaptive signal and feature fusion problems -- part i: algorithm derivation](https://arxiv.org/abs/2208.08867)|[DASF_toolbox](https://github.com/AlexanderBertrandLab/DASF_toolbox)| ## 2022-08-18 -|paper|code| -|---|---| -|[towards a better understanding human reading comprehension with brain signals](https://arxiv.org/abs/2108.01360)|[uercm](https://github.com/yeziyi1998/uercm)| -|[quantum message-passing algorithm for optimal and efficient decoding](https://arxiv.org/abs/2109.08170)|[quantum-message-passing-paper](https://github.com/chripiv/quantum-message-passing-paper)| +|date|paper|code| +|---|---|---| ## 2022-08-17 -|paper|code| -|---|---| -|[parametric scattering networks](https://arxiv.org/abs/2107.09539)|[ParametricScatteringNetworks](https://github.com/bentherien/ParametricScatteringNetworks)| -|[self-supervised learning for anomalous channel detection in eeg graphs: application to seizure analysis](https://arxiv.org/abs/2208.07448)|[EEG-CGS](https://github.com/Armanfard-Lab/EEG-CGS)| -|[signal detection with dynamic programming](https://arxiv.org/abs/2208.07830)|[Signal-detection-with-dynamic-programming](https://github.com/MordechaiRoth1/Signal-detection-with-dynamic-programming)| -|[efficient randomized subspace embeddings for distributed optimization under a communication budget](https://arxiv.org/abs/2103.07578)|[distoptconstrcomm](https://github.com/rajarshisaha95/distoptconstrcomm)| +|date|paper|code| +|---|---|---| +|2208.07448|[self-supervised learning for anomalous channel detection in eeg graphs: application to seizure analysis](https://arxiv.org/abs/2208.07448)|[EEG-CGS](https://github.com/Armanfard-Lab/EEG-CGS)| +|2208.07830|[signal detection with dynamic programming](https://arxiv.org/abs/2208.07830)|[Signal-detection-with-dynamic-programming](https://github.com/MordechaiRoth1/Signal-detection-with-dynamic-programming)| ## 2022-08-16 -|paper|code| -|---|---| -|[a robust adversarial network-based end-to-end communications system with strong generalization ability against adversarial attacks](https://arxiv.org/abs/2103.02654)|[GAN-based-E2E-communications-system-for-defense-against-adversarial-attack](https://github.com/YudiDong/GAN-based-E2E-communications-system-for-defense-against-adversarial-attack)| -|[towards interpretable sleep stage classification using cross-modal transformers](https://arxiv.org/abs/2208.06991)|[cross-modal-transformer](https://github.com/jathurshan0330/cross-modal-transformer)| -|[dynamic task software caching-assisted computation offloading for multi-access edge computing](https://arxiv.org/abs/2208.07151)|[drl-mec](https://github.com/chfocus/drl-mec)| -|[wifi based distance estimation using supervised machine learning](https://arxiv.org/abs/2208.07190)|[wifi-fingerprint](https://github.com/kahramankostas/wifi-fingerprint)| -|[how does data freshness affect real-time supervised learning?](https://arxiv.org/abs/2208.06948)|[impact-of-data-freshness-in-learning](https://github.com/kamran0153/impact-of-data-freshness-in-learning)| +|date|paper|code| +|---|---|---| +|2208.06991|[towards interpretable sleep stage classification using cross-modal transformers](https://arxiv.org/abs/2208.06991)|[cross-modal-transformer](https://github.com/jathurshan0330/cross-modal-transformer)| +|2208.07151|[dynamic task software caching-assisted computation offloading for multi-access edge computing](https://arxiv.org/abs/2208.07151)|[drl-mec](https://github.com/chfocus/drl-mec)| +|2208.07190|[wifi based distance estimation using supervised machine learning](https://arxiv.org/abs/2208.07190)|[wifi-fingerprint](https://github.com/kahramankostas/wifi-fingerprint)| +|2208.06948|[how does data freshness affect real-time supervised learning?](https://arxiv.org/abs/2208.06948)|[impact-of-data-freshness-in-learning](https://github.com/kamran0153/impact-of-data-freshness-in-learning)| ## 2022-08-15 -|paper|code| -|---|---| -|[lrh-net: a multi-level knowledge distillation approach for low-resource heart network](https://arxiv.org/abs/2204.08000)|[lrh-net](https://github.com/ekansh09/lrh-net)| -|[a hybrid method for condition monitoring and fault diagnosis of rolling bearings with low system delay](https://arxiv.org/abs/2208.06051)|[vibration-based-fault-diagnosis-with-low-delay](https://github.com/western-oc2-lab/vibration-based-fault-diagnosis-with-low-delay)| -|[a unified spatially coupled code design: threshold, cycles, and locality](https://arxiv.org/abs/2203.02052)|[unified_sc_ldpcl](https://github.com/hesfahanizadeh/unified_sc_ldpcl)| -|[communication network model of the immune system identifies the impact of interactions with sars-cov-2 proteins](https://arxiv.org/abs/2208.06355)|[core](https://github.com/sarkar-s/core)| +|date|paper|code| +|---|---|---| +|2208.06051|[a hybrid method for condition monitoring and fault diagnosis of rolling bearings with low system delay](https://arxiv.org/abs/2208.06051)|[vibration-based-fault-diagnosis-with-low-delay](https://github.com/western-oc2-lab/vibration-based-fault-diagnosis-with-low-delay)| +|2208.06355|[communication network model of the immune system identifies the impact of interactions with sars-cov-2 proteins](https://arxiv.org/abs/2208.06355)|[core](https://github.com/sarkar-s/core)| ## 2022-08-12 -|paper|code| -|---|---| -|[echofilter: a deep learning segmentation model improves the automation, standardization, and timeliness for post-processing echosounder data in tidal energy streams](https://arxiv.org/abs/2202.09648)|[echofilter](https://github.com/deepsenseca/echofilter)| -|[an modified cole's importance sampling method for low error floor qc-ldpc codes construction](https://arxiv.org/abs/2208.05795)|[trapping-sets-enumeration](https://github.com/Lcrypto/trapping-sets-enumeration)| +|date|paper|code| +|---|---|---| +|2208.05795|[an modified cole's importance sampling method for low error floor qc-ldpc codes construction](https://arxiv.org/abs/2208.05795)|[trapping-sets-enumeration](https://github.com/Lcrypto/trapping-sets-enumeration)| ## 2022-08-11 -|paper|code| -|---|---| -|[perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising](https://arxiv.org/abs/2110.08775)|[perturbative_mean_field_matrix_factorization](https://github.com/sphinxteam/perturbative_mean_field_matrix_factorization)| +|date|paper|code| +|---|---|---| ## 2022-08-10 -|paper|code| -|---|---| -|[efficient waveform covariance matrix design and antenna selection for mimo radar](https://arxiv.org/abs/2002.06025)|[evolutionary-antenna-design-in-mimo](https://github.com/arindam-bose/evolutionary-antenna-design-in-mimo)| -|[expression might be enough: representing pressure and demand for reinforcement learning based traffic signal control](https://arxiv.org/abs/2112.10107)|[Advanced_XLight](https://github.com/LiangZhang1996/Advanced_XLight)| -|[ultra lite convolutional neural network for automatic modulation classification](https://arxiv.org/abs/2208.04659)|[ultra-lite-convolutional-neural-network-for-automatic-modulation-classification](https://github.com/beechburgpiestar/ultra-lite-convolutional-neural-network-for-automatic-modulation-classification)| +|date|paper|code| +|---|---|---| +|2208.04659|[ultra lite convolutional neural network for automatic modulation classification](https://arxiv.org/abs/2208.04659)|[ultra-lite-convolutional-neural-network-for-automatic-modulation-classification](https://github.com/beechburgpiestar/ultra-lite-convolutional-neural-network-for-automatic-modulation-classification)| ## 2022-08-09 -|paper|code| -|---|---| -|[beats: an open-source, high-precision, multi-channel eeg acquisition tool system](https://arxiv.org/abs/2203.02102)|[beats](https://github.com/buptanteeg/beats)| -|[a spatially separable attention mechanism for massive mimo csi feedback](https://arxiv.org/abs/2208.03369)|[pytorch_stnet](https://github.com/sharanmourya/pytorch_stnet)| -|[fra-rir: fast random approximation of the image-source method](https://arxiv.org/abs/2208.04101)|[fra-rir](https://github.com/yluo42/fra-rir)| -|[oversquashing in gnns through the lens of information contraction and graph expansion](https://arxiv.org/abs/2208.03471)|[oversquashing](https://github.com/kedar2/oversquashing)| +|date|paper|code| +|---|---|---| +|2208.03369|[a spatially separable attention mechanism for massive mimo csi feedback](https://arxiv.org/abs/2208.03369)|[pytorch_stnet](https://github.com/sharanmourya/pytorch_stnet)| +|2208.04101|[fra-rir: fast random approximation of the image-source method](https://arxiv.org/abs/2208.04101)|[fra-rir](https://github.com/yluo42/fra-rir)| +|2208.03471|[oversquashing in gnns through the lens of information contraction and graph expansion](https://arxiv.org/abs/2208.03471)|[oversquashing](https://github.com/kedar2/oversquashing)| ## 2022-08-08 -|paper|code| -|---|---| -|[disentangled representation learning for rf fingerprint extraction under unknown channel statistics](https://arxiv.org/abs/2208.02724)|[dr-rff](https://github.com/xrj-com/dr-rff)| -|[a design of low-projection scma codebooks for downlink satellite internet of things](https://arxiv.org/abs/2208.03118)|[scma-codebook](https://github.com/ethanlq/scma-codebook)| +|date|paper|code| +|---|---|---| +|2208.02724|[disentangled representation learning for rf fingerprint extraction under unknown channel statistics](https://arxiv.org/abs/2208.02724)|[dr-rff](https://github.com/xrj-com/dr-rff)| +|2208.03118|[a design of low-projection scma codebooks for downlink satellite internet of things](https://arxiv.org/abs/2208.03118)|[scma-codebook](https://github.com/ethanlq/scma-codebook)| ## 2022-08-05 -|paper|code| -|---|---| -|[visually evaluating generative adversarial networks using itself under multivariate time series](https://arxiv.org/abs/2208.02649)|[GaussianGANs](https://github.com/jack-pan-ai/GaussianGANs)| +|date|paper|code| +|---|---|---| +|2208.02649|[visually evaluating generative adversarial networks using itself under multivariate time series](https://arxiv.org/abs/2208.02649)|[GaussianGANs](https://github.com/jack-pan-ai/GaussianGANs)| ## 2022-08-04 -|paper|code| -|---|---| -|[stable and interpretable unrolled dictionary learning](https://arxiv.org/abs/2106.00058)|[stable-interpretable-unrolled-dl](https://github.com/btolooshams/stable-interpretable-unrolled-dl)| -|[the wqn algorithm to adaptively correct artifacts in the eeg signal](https://arxiv.org/abs/2207.11696)|[wavelet-wqn-acha](https://github.com/mattbit/wavelet-wqn-acha)| -|[segmented learning for class-of-service network traffic classification](https://arxiv.org/abs/2208.01793)|[s2mc-for-cos](https://github.com/yoga-suhas-km/s2mc-for-cos)| -|[recovery of future data via convolution nuclear norm minimization](https://arxiv.org/abs/1909.03889)|[CNNM](https://github.com/gcliu1982/CNNM)| -|[deep learning-enabled semantic communication systems with task-unaware transmitter and dynamic data](https://arxiv.org/abs/2205.00271)|[semantic-communication-systems](https://github.com/sjtu-mxtao/semantic-communication-systems)| +|date|paper|code| +|---|---|---| +|2208.01793|[segmented learning for class-of-service network traffic classification](https://arxiv.org/abs/2208.01793)|[s2mc-for-cos](https://github.com/yoga-suhas-km/s2mc-for-cos)| ## 2022-08-03 -|paper|code| -|---|---| -|[self-supervised group meiosis contrastive learning for eeg-based emotion recognition](https://arxiv.org/abs/2208.00877)|[Self-supervised-group-meiosis-contrastive-learning-for-EEG-based-emotion-recognition](https://github.com/kanhaoning/Self-supervised-group-meiosis-contrastive-learning-for-EEG-based-emotion-recognition)| -|[towards v2i age-aware fairness access: a dqn based intelligent vehicular node training and test method](https://arxiv.org/abs/2208.01283)|[age-fairness](https://github.com/qiongwu86/age-fairness)| +|date|paper|code| +|---|---|---| +|2208.00877|[self-supervised group meiosis contrastive learning for eeg-based emotion recognition](https://arxiv.org/abs/2208.00877)|[Self-supervised-group-meiosis-contrastive-learning-for-EEG-based-emotion-recognition](https://github.com/kanhaoning/Self-supervised-group-meiosis-contrastive-learning-for-EEG-based-emotion-recognition)| +|2208.01283|[towards v2i age-aware fairness access: a dqn based intelligent vehicular node training and test method](https://arxiv.org/abs/2208.01283)|[age-fairness](https://github.com/qiongwu86/age-fairness)| ## 2022-08-02 -|paper|code| -|---|---| -|[untargeted region of interest selection for gc-ms data using a pseudo f-ratio moving window ($\psi$frmv)](https://arxiv.org/abs/2208.00313)|[regionofinterest](https://github.com/ryland-chem/regionofinterest)| -|[vector-based data improves left-right eye-tracking classifier performance after a covariate distributional shift](https://arxiv.org/abs/2208.00465)|[eegetcovariatedistributionalshift](https://github.com/brianxiang123/eegetcovariatedistributionalshift)| -|[descod-ecg: deep score-based diffusion model for ecg baseline wander and noise removal](https://arxiv.org/abs/2208.00542)|[score-based-ecg-denoising](https://github.com/huayuliarizona/score-based-ecg-denoising)| -|[tcmi: a non-parametric mutual-dependence estimator for multivariate continuous distributions](https://arxiv.org/abs/2001.11212)|[tcmi](https://github.com/BenjaminRegler/tcmi)| -|[tight concentrations and confidence sequences from the regret of universal portfolio](https://arxiv.org/abs/2110.14099)|[precise](https://github.com/bremen79/precise)| -|[better lattice quantizers constructed from complex integers](https://arxiv.org/abs/2204.01105)|[latticequantizer](https://github.com/shx-lyu/latticequantizer)| +|date|paper|code| +|---|---|---| +|2208.00313|[untargeted region of interest selection for gc-ms data using a pseudo f-ratio moving window ($\psi$frmv)](https://arxiv.org/abs/2208.00313)|[regionofinterest](https://github.com/ryland-chem/regionofinterest)| +|2208.00465|[vector-based data improves left-right eye-tracking classifier performance after a covariate distributional shift](https://arxiv.org/abs/2208.00465)|[eegetcovariatedistributionalshift](https://github.com/brianxiang123/eegetcovariatedistributionalshift)| +|2208.00542|[descod-ecg: deep score-based diffusion model for ecg baseline wander and noise removal](https://arxiv.org/abs/2208.00542)|[score-based-ecg-denoising](https://github.com/huayuliarizona/score-based-ecg-denoising)| ## 2022-08-01 -|paper|code| -|---|---| -|[deep learning based successive interference cancellation for the non-orthogonal downlink](https://arxiv.org/abs/2207.14468)|[sicnet](https://github.com/thienvanluong/sicnet)| -|[deep learning-based synchronization for uplink nb-iot](https://arxiv.org/abs/2205.10805)|[nprach_synch](https://github.com/nvlabs/nprach_synch)| -|[analytic relations between networks: encoding, decoding, and causality](https://arxiv.org/abs/2207.06606)|[analytic-relations-between-complex-networks-encoding-decoding-and-causality](https://github.com/doloming/analytic-relations-between-complex-networks-encoding-decoding-and-causality)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/09.md b/archives/2022/09.md index 698d0343..40583bdd 100644 --- a/archives/2022/09.md +++ b/archives/2022/09.md @@ -1,164 +1,111 @@ # September 2022 Archive ## 2022-09-30 -|paper|code| -|---|---| -|[frequency-dependent $f$-number increases the contrast and the spatial resolution in fast pulse-echo ultrasound imaging](https://arxiv.org/abs/2111.04593)|[f_number](https://github.com/mschiffn/f_number)| +|date|paper|code| +|---|---|---| ## 2022-09-29 -|paper|code| -|---|---| -|[a parameter-free nonconvex low-rank tensor completion model for spatiotemporal traffic data recovery](https://arxiv.org/abs/2209.13786)|[T-ITS-PFNC](https://github.com/YoungHe49/T-ITS-PFNC)| +|date|paper|code| +|---|---|---| +|2209.13786|[a parameter-free nonconvex low-rank tensor completion model for spatiotemporal traffic data recovery](https://arxiv.org/abs/2209.13786)|[T-ITS-PFNC](https://github.com/YoungHe49/T-ITS-PFNC)| ## 2022-09-28 -|paper|code| -|---|---| -|[biologically-plausible determinant maximization neural networks for blind separation of correlated sources](https://arxiv.org/abs/2209.12894)|[biologically-plausible-detmaxnns-for-blind-source-separation](https://github.com/bariscanbozkurt/biologically-plausible-detmaxnns-for-blind-source-separation)| -|[source detection via multi-label classification](https://arxiv.org/abs/2209.13553)|[Signal_detector](https://github.com/jkrishnan95v/Signal_detector)| -|[semi-blind source separation with learned constraints](https://arxiv.org/abs/2209.13585)|[sgmca](https://github.com/rcarlonigertosio/sgmca)| -|[provably efficient machine learning for quantum many-body problems](https://arxiv.org/abs/2106.12627)|[PastaQ.jl](https://github.com/GTorlai/PastaQ.jl)| -|[cell-free massive mimo meets otfs modulation](https://arxiv.org/abs/2112.10869)|[cell-free-otfs](https://github.com/mohammadalimohammadi/cell-free-otfs)| -|[an asymmetric contrastive loss for handling imbalanced datasets](https://arxiv.org/abs/2207.07080)|[asymmetric-cl](https://github.com/valentinovito/asymmetric-cl)| +|date|paper|code| +|---|---|---| +|2209.12894|[biologically-plausible determinant maximization neural networks for blind separation of correlated sources](https://arxiv.org/abs/2209.12894)|[biologically-plausible-detmaxnns-for-blind-source-separation](https://github.com/bariscanbozkurt/biologically-plausible-detmaxnns-for-blind-source-separation)| +|2209.13553|[source detection via multi-label classification](https://arxiv.org/abs/2209.13553)|[Signal_detector](https://github.com/jkrishnan95v/Signal_detector)| +|2209.13585|[semi-blind source separation with learned constraints](https://arxiv.org/abs/2209.13585)|[sgmca](https://github.com/rcarlonigertosio/sgmca)| ## 2022-09-27 -|paper|code| -|---|---| -|[ddp-gcn: multi-graph convolutional network for spatiotemporal traffic forecasting](https://arxiv.org/abs/1905.12256)|[DDP-GCN](https://github.com/snu-adsl/DDP-GCN)| -|[ppg2abp: translating photoplethysmogram (ppg) signals to arterial blood pressure (abp) waveforms using fully convolutional neural networks](https://arxiv.org/abs/2005.01669)|[PPG2ABP](https://github.com/nibtehaz/PPG2ABP)| -|[real-time noise cancellation with deep learning](https://arxiv.org/abs/2011.03466)|[deepNeuronalFilter](https://github.com/berndporr/deepNeuronalFilter)| -|[under the sand: navigation and localization of a micro aerial vehicle for landmine detection with ground penetrating synthetic aperture radar](https://arxiv.org/abs/2106.10108)|[mav_findmine](https://github.com/ethz-asl/mav_findmine)| -|[pyffs: a python library for fast fourier series computation and interpolation with gpu acceleration](https://arxiv.org/abs/2110.00262)|[pyFFS](https://github.com/imagingofthings/pyFFS)| -|[bounded simplex-structured matrix factorization](https://arxiv.org/abs/2209.12638)|[bssmf.jl](https://gitlab.com/vuthanho/bssmf.jl)| -|[poisson phase retrieval in very low-count regimes](https://arxiv.org/abs/2104.00861)|[ppr-low-count](https://github.com/zongyuli-umich/ppr-low-count)| -|[how does data freshness affect real-time supervised learning?](https://arxiv.org/abs/2208.06948)|[impact-of-data-freshness-in-learning](https://github.com/kamran0153/impact-of-data-freshness-in-learning)| +|date|paper|code| +|---|---|---| +|2209.12638|[bounded simplex-structured matrix factorization](https://arxiv.org/abs/2209.12638)|[bssmf.jl](https://gitlab.com/vuthanho/bssmf.jl)| ## 2022-09-26 -|paper|code| -|---|---| -|[deep, deep learning with bart](https://arxiv.org/abs/2202.14005)|[deep-deep-learning-with-bart](https://github.com/mrirecon/deep-deep-learning-with-bart)| -|[activity detection in distributed mimo: distributed amp via likelihood ratio fusion](https://arxiv.org/abs/2208.03070)|[distributed-AMP](https://github.com/jiananbai/distributed-AMP)| -|[autoencoder based iterative modeling and multivariate time-series subsequence clustering algorithm](https://arxiv.org/abs/2209.04213)|[abimca](https://github.com/jokonu/abimca)| +|date|paper|code| +|---|---|---| +|2209.04213|[autoencoder based iterative modeling and multivariate time-series subsequence clustering algorithm](https://arxiv.org/abs/2209.04213)|[abimca](https://github.com/jokonu/abimca)| ## 2022-09-23 -|paper|code| -|---|---| -|[leveraging joint-diagonalization in transform-learning nmf](https://arxiv.org/abs/2112.05664)|[tlnmf-tsp](https://github.com/sixin-zh/tlnmf-tsp)| -|[eventnet: detecting events in eeg](https://arxiv.org/abs/2209.11007)|[eventnet](https://github.com/n1xu5/eventnet)| -|[dynamic response recovery using ambient synchrophasor data: a synthetic texas interconnection case study](https://arxiv.org/abs/2209.11105)|[dy_resp_pkg_new](https://github.com/ShaohuiLiu/dy_resp_pkg_new)| -|[compressing sign information in dct-based image coding via deep sign retrieval](https://arxiv.org/abs/2209.10712)|[dsr](https://github.com/ctsutake/dsr)| +|date|paper|code| +|---|---|---| +|2209.11007|[eventnet: detecting events in eeg](https://arxiv.org/abs/2209.11007)|[eventnet](https://github.com/n1xu5/eventnet)| +|2209.11105|[dynamic response recovery using ambient synchrophasor data: a synthetic texas interconnection case study](https://arxiv.org/abs/2209.11105)|[dy_resp_pkg_new](https://github.com/ShaohuiLiu/dy_resp_pkg_new)| +|2209.10712|[compressing sign information in dct-based image coding via deep sign retrieval](https://arxiv.org/abs/2209.10712)|[dsr](https://github.com/ctsutake/dsr)| ## 2022-09-22 -|paper|code| -|---|---| -|[learning bilinear models of actuated koopman generators from partially-observed trajectories](https://arxiv.org/abs/2209.09977)|[koopmangeneratorem](https://github.com/samotto1/koopmangeneratorem)| -|[inferring network properties from time series using transfer entropy and mutual information: validation of multivariate versus bivariate approaches](https://arxiv.org/abs/2007.07500)|[infonet](https://github.com/LNov/infonet)| -|[decoding reed-muller codes with successive codeword permutations](https://arxiv.org/abs/2109.02122)|[sprld](https://github.com/nghiadt05/sprld)| +|date|paper|code| +|---|---|---| +|2209.09977|[learning bilinear models of actuated koopman generators from partially-observed trajectories](https://arxiv.org/abs/2209.09977)|[koopmangeneratorem](https://github.com/samotto1/koopmangeneratorem)| ## 2022-09-21 -|paper|code| -|---|---| -|[an inertial block majorization minimization framework for nonsmooth nonconvex optimization](https://arxiv.org/abs/2010.12133)|[TITAN](https://github.com/nhatpd/TITAN)| -|[signal decomposition using masked proximal operators](https://arxiv.org/abs/2202.09338)|[signal-decomposition](https://github.com/cvxgrp/signal-decomposition)| -|[massive mimo with dual-polarized antennas](https://arxiv.org/abs/2202.10084)|[dual-polarization](https://github.com/emilbjornson/dual-polarization)| +|date|paper|code| +|---|---|---| ## 2022-09-20 -|paper|code| -|---|---| -|[temporal feedback convolutional recurrent neural networks for speech command recognition](https://arxiv.org/abs/1911.01803)|[temporal-feedback-crnn](https://github.com/tae-jun/temporal-feedback-crnn)| -|[real-time outdoor localization using radio maps: a deep learning approach](https://arxiv.org/abs/2106.12556)|[LocUNet](https://github.com/CagkanYapar/LocUNet)| -|[efficient approximation of jacobian matrices involving a non-uniform fast fourier transform (nufft)](https://arxiv.org/abs/2111.02912)|[Bjork](https://github.com/guanhuaw/Bjork)| -|[data-driven estimation of capacity upper bounds](https://arxiv.org/abs/2205.06471)|[upper_capacity_bounds](https://github.com/chaeger/upper_capacity_bounds)| -|[bolt: fused window transformers for fmri time series analysis](https://arxiv.org/abs/2205.11578)|[bolt](https://github.com/icon-lab/bolt)| -|[an impedance transition method to verify the reference impedance of multiline trl calibration](https://arxiv.org/abs/2209.09163)|[verification-multiline-trl-calibration](https://github.com/ZiadHatab/verification-multiline-trl-calibration)| -|[information-theoretic characterization of the generalization error for iterative semi-supervised learning](https://arxiv.org/abs/2110.00926)|[generrorssl_2022](https://github.com/herianhe/generrorssl_2022)| +|date|paper|code| +|---|---|---| +|2209.09163|[an impedance transition method to verify the reference impedance of multiline trl calibration](https://arxiv.org/abs/2209.09163)|[verification-multiline-trl-calibration](https://github.com/ZiadHatab/verification-multiline-trl-calibration)| ## 2022-09-19 -|paper|code| -|---|---| -|[gcns-net: a graph convolutional neural network approach for decoding time-resolved eeg motor imagery signals](https://arxiv.org/abs/2006.08924)|[EEG-DL](https://github.com/SuperBruceJia/EEG-DL)| -|[bayesbeat: reliable atrial fibrillation detection from noisy photoplethysmography data](https://arxiv.org/abs/2011.00753)|[bayesbeat](https://github.com/sarathismg/bayesbeat)| -|[parallel faceted imaging in radio interferometry via proximal splitting (faceted hypersara): ii. code and real data proof of concept](https://arxiv.org/abs/2209.07604)|[faceted-hypersara](https://github.com/basp-group/faceted-hypersara)| -|[multiscale adaptive scheduling and path-planning for power-constrained uav-relays via smdps](https://arxiv.org/abs/2209.07655)|[MAESTRO-X](https://github.com/bharathkeshavamurthy/MAESTRO-X)| -|[self-supervised learning with an information maximization criterion](https://arxiv.org/abs/2209.07999)|[corinfomax-ssl](https://github.com/serdarozsoy/corinfomax-ssl)| +|date|paper|code| +|---|---|---| +|2209.07604|[parallel faceted imaging in radio interferometry via proximal splitting (faceted hypersara): ii. code and real data proof of concept](https://arxiv.org/abs/2209.07604)|[faceted-hypersara](https://github.com/basp-group/faceted-hypersara)| +|2209.07655|[multiscale adaptive scheduling and path-planning for power-constrained uav-relays via smdps](https://arxiv.org/abs/2209.07655)|[MAESTRO-X](https://github.com/bharathkeshavamurthy/MAESTRO-X)| +|2209.07999|[self-supervised learning with an information maximization criterion](https://arxiv.org/abs/2209.07999)|[corinfomax-ssl](https://github.com/serdarozsoy/corinfomax-ssl)| ## 2022-09-16 -|paper|code| -|---|---| -|[blind equalization and channel estimation in coherent optical communications using variational autoencoders](https://arxiv.org/abs/2204.11776)|[vae-equalizer](https://github.com/kit-cel/vae-equalizer)| -|[particle gradient descent model for point process generation](https://arxiv.org/abs/2010.14928)|[pp_syn](https://github.com/abrochar/pp_syn)| -|[a stochastic optimization framework for fair risk minimization](https://arxiv.org/abs/2102.12586)|[FERMI](https://github.com/optimization-for-data-driven-science/FERMI)| +|date|paper|code| +|---|---|---| ## 2022-09-15 -|paper|code| -|---|---| -|[learning-based downlink power allocation in cell-free massive mimo systems](https://arxiv.org/abs/2109.03128)|[power-allocation-cell-free](https://github.com/emilbjornson/power-allocation-cell-free)| -|[untargeted region of interest selection for gc-ms data using a pseudo f-ratio moving window ($\psi$frmv)](https://arxiv.org/abs/2208.00313)|[regionofinterest](https://github.com/ryland-chem/regionofinterest)| -|[personalized emotion detection using iot and machine learning](https://arxiv.org/abs/2209.06464)|[MLEmotionDetection](https://github.com/fionavictoria/MLEmotionDetection)| +|date|paper|code| +|---|---|---| +|2209.06464|[personalized emotion detection using iot and machine learning](https://arxiv.org/abs/2209.06464)|[MLEmotionDetection](https://github.com/fionavictoria/MLEmotionDetection)| ## 2022-09-14 -|paper|code| -|---|---| -|[multi-event-camera depth estimation and outlier rejection by refocused events fusion](https://arxiv.org/abs/2207.10494)|[dvs_mcemvs](https://github.com/tub-rip/dvs_mcemvs)| -|[decorrelate irrelevant, purify relevant: overcome textual spurious correlations from a feature perspective](https://arxiv.org/abs/2202.08048)|[depro](https://github.com/coling2022-depro/depro)| +|date|paper|code| +|---|---|---| ## 2022-09-13 -|paper|code| -|---|---| -|[adaptive r-peak detection on wearable ecg sensors for high-intensity exercise](https://arxiv.org/abs/2112.04369)|[adaptive_rpeak_det_public](https://c4science.ch/source/adaptive_rpeak_det_public)| -|[a design of low-projection scma codebooks for ultra-low decoding complexity in downlink iot networks](https://arxiv.org/abs/2208.03118)|[scma-codebook](https://github.com/ethanlq/scma-codebook)| -|[data-driven blind synchronization and interference rejection for digital communication signals](https://arxiv.org/abs/2209.04871)|[scss_sync](https://github.com/rfchallenge/scss_sync)| +|date|paper|code| +|---|---|---| +|2209.04871|[data-driven blind synchronization and interference rejection for digital communication signals](https://arxiv.org/abs/2209.04871)|[scss_sync](https://github.com/rfchallenge/scss_sync)| ## 2022-09-12 -|paper|code| -|---|---| -|[autoencoder based iterative modeling and multivariate time-series subsequence clustering algorithm](https://arxiv.org/abs/2209.04213)|[mt3scm](https://github.com/jokonu/mt3scm)| -|[the optimality of word lengths. theoretical foundations and an empirical study](https://arxiv.org/abs/2208.10384)|[iql-research-project-21-22](https://github.com/iql-course/iql-research-project-21-22)| +|date|paper|code| +|---|---|---| +|2209.04213|[autoencoder based iterative modeling and multivariate time-series subsequence clustering algorithm](https://arxiv.org/abs/2209.04213)|[mt3scm](https://github.com/jokonu/mt3scm)| ## 2022-09-09 -|paper|code| -|---|---| -|[two beams are better than one: enabling reliable and high throughput mmwave links](https://arxiv.org/abs/2101.04249)|[mmreliable](https://github.com/ucsdwcsng/mmreliable)| -|[position aided beam prediction in the real world: how useful gps locations actually are?](https://arxiv.org/abs/2205.09054)|[position-beam-prediction](https://github.com/jmoraispk/position-beam-prediction)| -|[too fine or too coarse? the goldilocks composition of data complexity for robust left-right eye-tracking classifiers](https://arxiv.org/abs/2209.03761)|[kdd-ml](https://github.com/ayahia1/kdd-ml)| -|[non-adaptive and two-stage coding over the z-channel](https://arxiv.org/abs/2202.00136)|[Z-channel_with_1_error](https://github.com/VorobyevIlya/Z-channel_with_1_error)| +|date|paper|code| +|---|---|---| +|2209.03761|[too fine or too coarse? the goldilocks composition of data complexity for robust left-right eye-tracking classifiers](https://arxiv.org/abs/2209.03761)|[kdd-ml](https://github.com/ayahia1/kdd-ml)| ## 2022-09-08 -|paper|code| -|---|---| -|[a time-domain real-valued generalized wiener filter for multi-channel neural separation systems](https://arxiv.org/abs/2112.03533)|[TAC](https://github.com/yluo42/TAC)| -|[generative principal component analysis](https://arxiv.org/abs/2203.09693)|[GenerativePCA](https://github.com/liuzq09/GenerativePCA)| -|[denoising generalized expectation-consistent approximation for mr image recovery](https://arxiv.org/abs/2206.05049)|[corr-plus-corr](https://github.com/saurav-k-shastri/corr-plus-corr)| +|date|paper|code| +|---|---|---| ## 2022-09-07 -|paper|code| -|---|---| -|[bottlefit: learning compressed representations in deep neural networks for effective and efficient split computing](https://arxiv.org/abs/2201.02693)|[bottlefit-split_computing](https://github.com/yoshitomo-matsubara/bottlefit-split_computing)| -|[semantic communications with discrete-time analog transmission: a papr perspective](https://arxiv.org/abs/2208.08342)|[semanticpapr](https://github.com/lynshao/semanticpapr)| -|[transfer learning of an ensemble of dnns for ssvep bci spellers without user-specific training](https://arxiv.org/abs/2209.01511)|[ensemble-of-dnns](https://github.com/osmanberke/ensemble-of-dnns)| -|[tfn: an interpretable neural network with time-frequency transform embedded for intelligent fault diagnosis](https://arxiv.org/abs/2209.01992)|[tfn](https://github.com/chenqian0618/tfn)| -|[large graph signal denoising with application to differential privacy](https://arxiv.org/abs/2209.02043)|[dp-graph-denoising](https://gitlab.com/elie-chedemail/dp-graph-denoising)| -|[data augmentation for deep receivers](https://arxiv.org/abs/2209.01362)|[data-augmentations-for-receivers](https://github.com/tomerraviv95/data-augmentations-for-receivers)| -|[learning to predict requires integrated information](https://arxiv.org/abs/2209.01418)|[learningrequiresintinf](https://github.com/carlottalanger/learningrequiresintinf)| -|[abs+ polar codes: exploiting more linear transforms on adjacent bits](https://arxiv.org/abs/2209.02461)|[abs-polar](https://github.com/plumjelly/abs-polar)| +|date|paper|code| +|---|---|---| +|2209.01511|[transfer learning of an ensemble of dnns for ssvep bci spellers without user-specific training](https://arxiv.org/abs/2209.01511)|[ensemble-of-dnns](https://github.com/osmanberke/ensemble-of-dnns)| +|2209.01992|[tfn: an interpretable neural network with time-frequency transform embedded for intelligent fault diagnosis](https://arxiv.org/abs/2209.01992)|[tfn](https://github.com/chenqian0618/tfn)| +|2209.02043|[large graph signal denoising with application to differential privacy](https://arxiv.org/abs/2209.02043)|[dp-graph-denoising](https://gitlab.com/elie-chedemail/dp-graph-denoising)| +|2209.01362|[data augmentation for deep receivers](https://arxiv.org/abs/2209.01362)|[data-augmentations-for-receivers](https://github.com/tomerraviv95/data-augmentations-for-receivers)| +|2209.01418|[learning to predict requires integrated information](https://arxiv.org/abs/2209.01418)|[learningrequiresintinf](https://github.com/carlottalanger/learningrequiresintinf)| +|2209.02461|[abs+ polar codes: exploiting more linear transforms on adjacent bits](https://arxiv.org/abs/2209.02461)|[abs-polar](https://github.com/plumjelly/abs-polar)| ## 2022-09-05 -|paper|code| -|---|---| -|[artificial intelligence enabled noma towards next generation multiple access](https://arxiv.org/abs/2206.04992)|[ai_noma](https://github.com/xiaoxiaxusummer/ai_noma)| -|[evaluating short-term forecasting of multiple time series in iot environments](https://arxiv.org/abs/2206.07784)|[multiple-timeseries-forecasting](https://github.com/pcharala/multiple-timeseries-forecasting)| -|[towards unsupervised assessment with open-source data of the accuracy of deep learning-based distributed pv mapping](https://arxiv.org/abs/2207.07466)|[dsfrance](https://github.com/gabrielkasmi/dsfrance)| -|[software tools for decoding quantum low-density parity check codes](https://arxiv.org/abs/2209.01180)|[qecc](https://github.com/lucasberent/qecc)| +|date|paper|code| +|---|---|---| +|2209.01180|[software tools for decoding quantum low-density parity check codes](https://arxiv.org/abs/2209.01180)|[qecc](https://github.com/lucasberent/qecc)| ## 2022-09-02 -|paper|code| -|---|---| -|[variational sparse coding with learned thresholding](https://arxiv.org/abs/2205.03665)|[variational-sparse-coding](https://github.com/kfallah/variational-sparse-coding)| -|[a unified spatially coupled code design: threshold, cycles, and locality](https://arxiv.org/abs/2203.02052)|[unified_sc_ldpcl](https://github.com/hesfahanizadeh/unified_sc_ldpcl)| -|[mind: maximum mutual information based neural decoder](https://arxiv.org/abs/2205.07061)|[mind-neural-decoder](https://github.com/tonellolab/mind-neural-decoder)| +|date|paper|code| +|---|---|---| ## 2022-09-01 -|paper|code| -|---|---| -|[fast robust subspace tracking via pca in sparse data-dependent noise](https://arxiv.org/abs/2006.08030)|[NORST](https://github.com/praneethmurthy/NORST)| -|[do language models make human-like predictions about the coreferents of italian anaphoric zero pronouns?](https://arxiv.org/abs/2208.14554)|[italian-zero-anaphora-prediction](https://github.com/jmichaelov/italian-zero-anaphora-prediction)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/10.md b/archives/2022/10.md index b0687f82..018e5131 100644 --- a/archives/2022/10.md +++ b/archives/2022/10.md @@ -1,188 +1,135 @@ # October 2022 Archive ## 2022-10-31 -|paper|code| -|---|---| -|[deep convolutional neural networks for multi-target tracking: a transfer learning approach](https://arxiv.org/abs/2210.15539)|[mtt](https://github.com/damowerko/mtt)| -|[conditioning and sampling in variational diffusion models for speech super-resolution](https://arxiv.org/abs/2210.15793)|[diffwave-sr](https://github.com/yoyololicon/diffwave-sr)| -|[multimodal estimation of change points of physiological arousal in drivers](https://arxiv.org/abs/2210.15826)|[ggs_driving](https://github.com/usc-sail/ggs_driving)| -|[speaker recognition with two-step multi-modal deep cleansing](https://arxiv.org/abs/2210.15903)|[avcleanse](https://github.com/taoruijie/avcleanse)| -|[lightweight and high-fidelity end-to-end text-to-speech with multi-band generation and inverse short-time fourier transform](https://arxiv.org/abs/2210.15975)|[mb-istft-vits](https://github.com/masayakawamura/mb-istft-vits)| -|[nnsvs: a neural network-based singing voice synthesis toolkit](https://arxiv.org/abs/2210.15987)|[nnsvs](https://github.com/nnsvs/nnsvs)| -|[imitation learning-based implicit semantic-aware communication networks: multi-layer representation and collaborative reasoning](https://arxiv.org/abs/2210.16118)|[irml](https://github.com/zjs919/irml)| +|date|paper|code| +|---|---|---| +|2210.15539|[deep convolutional neural networks for multi-target tracking: a transfer learning approach](https://arxiv.org/abs/2210.15539)|[mtt](https://github.com/damowerko/mtt)| +|2210.15793|[conditioning and sampling in variational diffusion models for speech super-resolution](https://arxiv.org/abs/2210.15793)|[diffwave-sr](https://github.com/yoyololicon/diffwave-sr)| +|2210.15826|[multimodal estimation of change points of physiological arousal in drivers](https://arxiv.org/abs/2210.15826)|[ggs_driving](https://github.com/usc-sail/ggs_driving)| +|2210.15903|[speaker recognition with two-step multi-modal deep cleansing](https://arxiv.org/abs/2210.15903)|[avcleanse](https://github.com/taoruijie/avcleanse)| +|2210.15975|[lightweight and high-fidelity end-to-end text-to-speech with multi-band generation and inverse short-time fourier transform](https://arxiv.org/abs/2210.15975)|[mb-istft-vits](https://github.com/masayakawamura/mb-istft-vits)| +|2210.15987|[nnsvs: a neural network-based singing voice synthesis toolkit](https://arxiv.org/abs/2210.15987)|[nnsvs](https://github.com/nnsvs/nnsvs)| +|2210.16118|[imitation learning-based implicit semantic-aware communication networks: multi-layer representation and collaborative reasoning](https://arxiv.org/abs/2210.16118)|[irml](https://github.com/zjs919/irml)| ## 2022-10-28 -|paper|code| -|---|---| -|[vqf: highly accurate imu orientation estimation with bias estimation and magnetic disturbance rejection](https://arxiv.org/abs/2203.17024)|[vqf](https://github.com/dlaidig/vqf)| -|[accelerated massive mimo detector based on annealed underdamped langevin dynamics](https://arxiv.org/abs/2210.15071)|[langevin-mimo-detector](https://github.com/nzilberstein/langevin-mimo-detector)| -|[kalmanbot: kalmannet-aided bollinger bands for pairs trading](https://arxiv.org/abs/2210.15448)|[kalmanbot_icassp23](https://github.com/kalmannet/kalmanbot_icassp23)| -|[infoshape: task-based neural data shaping via mutual information](https://arxiv.org/abs/2210.15034)|[mine-pytorch](https://github.com/billywu1029/mine-pytorch)| +|date|paper|code| +|---|---|---| +|2210.15071|[accelerated massive mimo detector based on annealed underdamped langevin dynamics](https://arxiv.org/abs/2210.15071)|[langevin-mimo-detector](https://github.com/nzilberstein/langevin-mimo-detector)| +|2210.15448|[kalmanbot: kalmannet-aided bollinger bands for pairs trading](https://arxiv.org/abs/2210.15448)|[kalmanbot_icassp23](https://github.com/kalmannet/kalmanbot_icassp23)| +|2210.15034|[infoshape: task-based neural data shaping via mutual information](https://arxiv.org/abs/2210.15034)|[mine-pytorch](https://github.com/billywu1029/mine-pytorch)| ## 2022-10-27 -|paper|code| -|---|---| -|[multimodal sensor data fusion for in-situ classification of animal behavior using accelerometry and gnss data](https://arxiv.org/abs/2206.12078)|[animal_behavior_classification_acc_gnss](https://github.com/reza219/animal_behavior_classification_acc_gnss)| -|[topological slepians: maximally localized representations of signals over simplicial complexes](https://arxiv.org/abs/2210.14758)|[topological-slepians](https://github.com/clabat9/topological-slepians)| -|[a nonlinear sum of squares search for cazac sequences](https://arxiv.org/abs/2210.14827)|[ieee-sos-cazac](https://github.com/magsino-usna/ieee-sos-cazac)| -|[hybrid hmm decoder for convolutional codes by joint trellis-like structure and channel prior](https://arxiv.org/abs/2210.14749)|[hmm-decoder](https://github.com/haoyyli/hmm-decoder)| +|date|paper|code| +|---|---|---| +|2210.14758|[topological slepians: maximally localized representations of signals over simplicial complexes](https://arxiv.org/abs/2210.14758)|[topological-slepians](https://github.com/clabat9/topological-slepians)| +|2210.14827|[a nonlinear sum of squares search for cazac sequences](https://arxiv.org/abs/2210.14827)|[ieee-sos-cazac](https://github.com/magsino-usna/ieee-sos-cazac)| +|2210.14749|[hybrid hmm decoder for convolutional codes by joint trellis-like structure and channel prior](https://arxiv.org/abs/2210.14749)|[hmm-decoder](https://github.com/haoyyli/hmm-decoder)| ## 2022-10-26 -|paper|code| -|---|---| -|[label-aware ranked loss for robust people counting using automotive in-cabin radar](https://arxiv.org/abs/2110.05876)|[labelawareranked-loss](https://github.com/2geeks2/labelawareranked-loss)| +|date|paper|code| +|---|---|---| ## 2022-10-25 -|paper|code| -|---|---| -|[hierarchical filtering with online learned priors for ecg denoising](https://arxiv.org/abs/2210.12807)|[hkf_icassp23](https://github.com/kalmannet/hkf_icassp23)| -|[unsupervised particle sorting for cryo-em using probabilistic pca](https://arxiv.org/abs/2210.12811)|[particle_sorting](https://github.com/giliw/particle_sorting)| -|[ecg artifact removal from single-channel surface emg using fully convolutional networks](https://arxiv.org/abs/2210.13271)|[ecg-removal-from-semg-by-fcn](https://github.com/eric-wang135/ecg-removal-from-semg-by-fcn)| -|[stimulus-informed generalized canonical correlation analysis of stimulus-following brain responses](https://arxiv.org/abs/2210.13297)|[si-gcca](https://github.com/alexanderbertrandlab/si-gcca)| -|[tight mutual information estimation with contrastive fenchel-legendre optimization](https://arxiv.org/abs/2107.01131)|[FLO](https://github.com/qingguo666/FLO)| -|[fast beam alignment via pure exploration in multi-armed bandits](https://arxiv.org/abs/2210.12625)|[fast-beam-alignment](https://github.com/yiwei0129/fast-beam-alignment)| +|date|paper|code| +|---|---|---| +|2210.12807|[hierarchical filtering with online learned priors for ecg denoising](https://arxiv.org/abs/2210.12807)|[hkf_icassp23](https://github.com/kalmannet/hkf_icassp23)| +|2210.12811|[unsupervised particle sorting for cryo-em using probabilistic pca](https://arxiv.org/abs/2210.12811)|[particle_sorting](https://github.com/giliw/particle_sorting)| +|2210.13271|[ecg artifact removal from single-channel surface emg using fully convolutional networks](https://arxiv.org/abs/2210.13271)|[ecg-removal-from-semg-by-fcn](https://github.com/eric-wang135/ecg-removal-from-semg-by-fcn)| +|2210.13297|[stimulus-informed generalized canonical correlation analysis of stimulus-following brain responses](https://arxiv.org/abs/2210.13297)|[si-gcca](https://github.com/alexanderbertrandlab/si-gcca)| +|2210.12625|[fast beam alignment via pure exploration in multi-armed bandits](https://arxiv.org/abs/2210.12625)|[fast-beam-alignment](https://github.com/yiwei0129/fast-beam-alignment)| ## 2022-10-24 -|paper|code| -|---|---| -|[noisy neonatal chest sound separation for high-quality heart and lung sounds](https://arxiv.org/abs/2201.03211)|[heart-and-lung-sound-separation](https://github.com/egrooby-monash/heart-and-lung-sound-separation)| -|[deep, deep learning with bart](https://arxiv.org/abs/2202.14005)|[deep-deep-learning-with-bart](https://github.com/mrirecon/deep-deep-learning-with-bart)| -|[nestanets: stable, accurate and efficient neural networks for analysis-sparse inverse problems](https://arxiv.org/abs/2203.00804)|[as-nesta-net](https://github.com/mneyrane/as-nesta-net)| +|date|paper|code| +|---|---|---| ## 2022-10-21 -|paper|code| -|---|---| -|[recovery of missing sensor data by reconstructing time-varying graph signals](https://arxiv.org/abs/2203.00418)|[EUSIPCO_22_Sobolev](https://github.com/anindya2001/EUSIPCO_22_Sobolev)| -|[prosky: neat meets noma-mmwave in the sky of 6g](https://arxiv.org/abs/2210.11406)|[prosky](https://github.com/fouzibenfaid/prosky)| -|[a hybrid millimeter-wave channel simulator for joint communication and localization](https://arxiv.org/abs/2210.11422)|[omnisim](https://github.com/dengjunquan/omnisim)| -|[on tilted losses in machine learning: theory and applications](https://arxiv.org/abs/2109.06141)|[TERM](https://github.com/litian96/TERM)| -|[rashomon capacity: a metric for predictive multiplicity in classification](https://arxiv.org/abs/2206.01295)|[rashomon-capacity](https://github.com/hsianghsu/rashomon-capacity)| +|date|paper|code| +|---|---|---| +|2210.11406|[prosky: neat meets noma-mmwave in the sky of 6g](https://arxiv.org/abs/2210.11406)|[prosky](https://github.com/fouzibenfaid/prosky)| +|2210.11422|[a hybrid millimeter-wave channel simulator for joint communication and localization](https://arxiv.org/abs/2210.11422)|[omnisim](https://github.com/dengjunquan/omnisim)| ## 2022-10-20 -|paper|code| -|---|---| -|[a spatially separable attention mechanism for massive mimo csi feedback](https://arxiv.org/abs/2208.03369)|[pytorch_stnet](https://github.com/sharanmourya/pytorch_stnet)| -|[generative adversarial user privacy in lossy single-server information retrieval](https://arxiv.org/abs/2012.03902)|[GAUP_TIFS22](https://github.com/Simula-UiB/GAUP_TIFS22)| +|date|paper|code| +|---|---|---| ## 2022-10-19 -|paper|code| -|---|---| -|[non-stationary transformers: exploring the stationarity in time series forecasting](https://arxiv.org/abs/2205.14415)|[Nonstationary_Transformers](https://github.com/thuml/Nonstationary_Transformers)| -|[deep learning-enabled semantic communication systems with task-unaware transmitter and dynamic data](https://arxiv.org/abs/2205.00271)|[semantic-communication-systems](https://github.com/sjtu-mxtao/semantic-communication-systems)| -|[distributed inference over linear models using alternating gaussian belief propagation](https://arxiv.org/abs/2210.09808)|[FactorGraph.jl](https://github.com/mcosovic/FactorGraph.jl)| +|date|paper|code| +|---|---|---| +|2210.09808|[distributed inference over linear models using alternating gaussian belief propagation](https://arxiv.org/abs/2210.09808)|[FactorGraph.jl](https://github.com/mcosovic/FactorGraph.jl)| ## 2022-10-18 -|paper|code| -|---|---| -|[a robust alternative for graph convolutional neural networks via graph neighborhood filters](https://arxiv.org/abs/2110.00844)|[neighborhoodgf](https://github.com/vmtenorio/neighborhoodgf)| -|[music source separation with generative flow](https://arxiv.org/abs/2204.09079)|[generativesourceseparation](https://github.com/gzhu06/generativesourceseparation)| -|[sinr: deconvolving circular sas images using implicit neural representations](https://arxiv.org/abs/2204.10428)|[csas_deconvolution_inr](https://github.com/awreed/csas_deconvolution_inr)| -|[transfer learning of wav2vec 2.0 for automatic lyric transcription](https://arxiv.org/abs/2207.09747)|[alt_speechbrain](https://github.com/guxm2021/alt_speechbrain)| -|[toward reliable signals decoding for electroencephalogram: a benchmark study to eegnex](https://arxiv.org/abs/2207.12369)|[eegnex](https://github.com/chenxiachan/eegnex)| -|[disentangled representation learning for rf fingerprint extraction under unknown channel statistics](https://arxiv.org/abs/2208.02724)|[dr-rff](https://github.com/xrj-com/dr-rff)| -|[multiscale adaptive scheduling and path-planning for power-constrained uav-relays via smdps](https://arxiv.org/abs/2209.07655)|[MAESTRO-X](https://github.com/bharathkeshavamurthy/MAESTRO-X)| -|[evaluating latent space robustness and uncertainty of eeg-ml models under realistic distribution shifts](https://arxiv.org/abs/2209.11233)|[evaluating-eeg-representations](https://github.com/neerajwagh/evaluating-eeg-representations)| -|[a framework to evaluate independent component analysis applied to eeg signal: testing on the picard algorithm](https://arxiv.org/abs/2210.08409)|[testica](https://github.com/sccn/testica)| -|[robust graph filter identification and graph denoising from signal observations](https://arxiv.org/abs/2210.08488)|[graph_denoising](https://github.com/reysam93/graph_denoising)| -|[principled pruning of bayesian neural networks through variational free energy minimization](https://arxiv.org/abs/2210.09134)|[principledpruningbnn](https://github.com/biaslab/principledpruningbnn)| -|[a unitary transform based generalized approximate message passing](https://arxiv.org/abs/2210.08861)|[guamp](https://github.com/riverzhu/guamp)| +|date|paper|code| +|---|---|---| +|2210.08409|[a framework to evaluate independent component analysis applied to eeg signal: testing on the picard algorithm](https://arxiv.org/abs/2210.08409)|[testica](https://github.com/sccn/testica)| +|2210.08488|[robust graph filter identification and graph denoising from signal observations](https://arxiv.org/abs/2210.08488)|[graph_denoising](https://github.com/reysam93/graph_denoising)| +|2210.09134|[principled pruning of bayesian neural networks through variational free energy minimization](https://arxiv.org/abs/2210.09134)|[principledpruningbnn](https://github.com/biaslab/principledpruningbnn)| +|2210.08861|[a unitary transform based generalized approximate message passing](https://arxiv.org/abs/2210.08861)|[guamp](https://github.com/riverzhu/guamp)| ## 2022-10-17 -|paper|code| -|---|---| -|[calibration and uncertainty characterization for ultra-wideband two-way-ranging measurements](https://arxiv.org/abs/2210.05888)|[uwb_calibration](https://github.com/decarsg/uwb_calibration)| -|[i13dr: a real-time demand response infrastructure for integrating renewable energy resources](https://arxiv.org/abs/2210.07789)|[demand-manager-app](https://github.com/i13DR/demand-manager-app)| +|date|paper|code| +|---|---|---| +|2210.05888|[calibration and uncertainty characterization for ultra-wideband two-way-ranging measurements](https://arxiv.org/abs/2210.05888)|[uwb_calibration](https://github.com/decarsg/uwb_calibration)| +|2210.07789|[i13dr: a real-time demand response infrastructure for integrating renewable energy resources](https://arxiv.org/abs/2210.07789)|[demand-manager-app](https://github.com/i13DR/demand-manager-app)| ## 2022-10-14 -|paper|code| -|---|---| -|[ecg-atk-gan: robustness against adversarial attacks on ecgs using conditional generative adversarial networks](https://arxiv.org/abs/2110.09983)|[ecg-atk-gan](https://github.com/farihahossain/ecg-atk-gan)| -|[spd domain-specific batch normalization to crack interpretable unsupervised domain adaptation in eeg](https://arxiv.org/abs/2206.01323)|[TSMNet](https://github.com/rkobler/TSMNet)| -|[partial identifiability for nonnegative matrix factorization](https://arxiv.org/abs/2206.08022)|[nmf-partial-identifiability](https://gitlab.com/ngillis/nmf-partial-identifiability)| -|[a monotonicity constrained attention module for emotion classification with limited eeg data](https://arxiv.org/abs/2208.08155)|[bci-attention](https://github.com/dykuang/bci-attention)| -|[self-supervised learning for label-efficient sleep stage classification: a comprehensive evaluation](https://arxiv.org/abs/2210.06286)|[eval_ssl_ssc](https://github.com/emadeldeen24/eval_ssl_ssc)| -|[decentralized state estimation in a dimension-reduced linear regression](https://arxiv.org/abs/2210.06947)|[dtt](https://gitlab.com/robinforsling/dtt)| -|[better lattice quantizers constructed from complex integers](https://arxiv.org/abs/2204.01105)|[latticequantizer](https://github.com/shx-lyu/latticequantizer)| -|[decision-oriented two-parameter fisher information sensitivity using symplectic decomposition](https://arxiv.org/abs/2207.12077)|[symplecticfishersensitivity](https://github.com/longitude-jyang/symplecticfishersensitivity)| -|[rigorous dynamical mean field theory for stochastic gradient descent methods](https://arxiv.org/abs/2210.06591)|[rigorous-dynamical-mean-field-theory](https://github.com/spoc-group/rigorous-dynamical-mean-field-theory)| +|date|paper|code| +|---|---|---| +|2210.06286|[self-supervised learning for label-efficient sleep stage classification: a comprehensive evaluation](https://arxiv.org/abs/2210.06286)|[eval_ssl_ssc](https://github.com/emadeldeen24/eval_ssl_ssc)| +|2210.06947|[decentralized state estimation in a dimension-reduced linear regression](https://arxiv.org/abs/2210.06947)|[dtt](https://gitlab.com/robinforsling/dtt)| +|2210.06591|[rigorous dynamical mean field theory for stochastic gradient descent methods](https://arxiv.org/abs/2210.06591)|[rigorous-dynamical-mean-field-theory](https://github.com/spoc-group/rigorous-dynamical-mean-field-theory)| ## 2022-10-13 -|paper|code| -|---|---| -|[a spatially separable attention mechanism for massive mimo csi feedback](https://arxiv.org/abs/2208.03369)|[pytorch_stnet](https://github.com/sharanmourya/pytorch_stnet)| -|[outlier-insensitive kalman filtering using nuv priors](https://arxiv.org/abs/2210.06083)|[oikf_icassp23](https://github.com/kalmannet/oikf_icassp23)| -|[an energy-efficient spiking neural network for finger velocity decoding for implantable brain-machine interface](https://arxiv.org/abs/2210.06287)|[snn-for-finger-velocity-ibmi](https://github.com/liaorichard/snn-for-finger-velocity-ibmi)| -|[multimodality multi-lead ecg arrhythmia classification using self-supervised learning](https://arxiv.org/abs/2210.06297)|[ecg_ssl_12lead](https://github.com/uark-aicv/ecg_ssl_12lead)| -|[cross task neural architecture search for eeg signal classifications](https://arxiv.org/abs/2210.06298)|[ctnas-eeg](https://github.com/duanyiqun/ctnas-eeg)| -|[multi-layer state evolution under random convolutional design](https://arxiv.org/abs/2205.13503)|[conv-ml-amp](https://github.com/mdnls/conv-ml-amp)| -|[graph neural networks for channel decoding](https://arxiv.org/abs/2207.14742)|[gnn-decoder](https://github.com/nvlabs/gnn-decoder)| +|date|paper|code| +|---|---|---| +|2210.06083|[outlier-insensitive kalman filtering using nuv priors](https://arxiv.org/abs/2210.06083)|[oikf_icassp23](https://github.com/kalmannet/oikf_icassp23)| +|2210.06287|[an energy-efficient spiking neural network for finger velocity decoding for implantable brain-machine interface](https://arxiv.org/abs/2210.06287)|[snn-for-finger-velocity-ibmi](https://github.com/liaorichard/snn-for-finger-velocity-ibmi)| +|2210.06297|[multimodality multi-lead ecg arrhythmia classification using self-supervised learning](https://arxiv.org/abs/2210.06297)|[ecg_ssl_12lead](https://github.com/uark-aicv/ecg_ssl_12lead)| +|2210.06298|[cross task neural architecture search for eeg signal classifications](https://arxiv.org/abs/2210.06298)|[ctnas-eeg](https://github.com/duanyiqun/ctnas-eeg)| ## 2022-10-12 -|paper|code| -|---|---| -|[the portiloop: a deep learning-based open science tool for closed-loop brain stimulation](https://arxiv.org/abs/2107.13473)|[portiloop](https://github.com/mistlab/portiloop)| -|[transfer learning-based channel estimation in orthogonal frequency division multiplexing systems using data-nulling superimposed pilots](https://arxiv.org/abs/2205.14308)|[transferlearningbasedcebydnsp](https://github.com/leiunnn/transferlearningbasedcebydnsp)| -|[slurp! spectroscopy of liquids using robot pre-touch sensing](https://arxiv.org/abs/2210.04941)|[slurp_grasping](https://github.com/river-lab/slurp_grasping)| -|[multi-site diagnostic classification of schizophrenia using 3d cnn on aggregated task-based fmri data](https://arxiv.org/abs/2210.05240)|[Schizophrenia-Classification-from-multi-site-fMRI-data](https://github.com/s-vigneshwaran/Schizophrenia-Classification-from-multi-site-fMRI-data)| -|[misspecified phase retrieval with generative priors](https://arxiv.org/abs/2210.05571)|[MPRG](https://github.com/jiulongliu/MPRG)| +|date|paper|code| +|---|---|---| +|2210.04941|[slurp! spectroscopy of liquids using robot pre-touch sensing](https://arxiv.org/abs/2210.04941)|[slurp_grasping](https://github.com/river-lab/slurp_grasping)| +|2210.05240|[multi-site diagnostic classification of schizophrenia using 3d cnn on aggregated task-based fmri data](https://arxiv.org/abs/2210.05240)|[Schizophrenia-Classification-from-multi-site-fMRI-data](https://github.com/s-vigneshwaran/Schizophrenia-Classification-from-multi-site-fMRI-data)| +|2210.05571|[misspecified phase retrieval with generative priors](https://arxiv.org/abs/2210.05571)|[MPRG](https://github.com/jiulongliu/MPRG)| ## 2022-10-11 -|paper|code| -|---|---| -|[towards real-world bci: ccspnet, a compact subject-independent motor imagery framework](https://arxiv.org/abs/2012.13567)|[CCSPNet](https://github.com/Singular-Brain/CCSPNet)| -|[performance analysis of multi-user noma wireless-powered mmtc networks: a stochastic geometry approach](https://arxiv.org/abs/2201.04784)|[mmtc-noma](https://github.com/thanhluannguyen/mmtc-noma)| -|[communication-efficient stochastic zeroth-order optimization for federated learning](https://arxiv.org/abs/2201.09531)|[FedZO](https://github.com/noobyzy/FedZO)| -|[urglq: an efficient covariance matrix reconstruction method for robust adaptive beamforming](https://arxiv.org/abs/2210.02214)|[robust-adaptive-beamforming-2022](https://github.com/chenpengseu/robust-adaptive-beamforming-2022)| -|[online learning of the transfer matrix of dynamic scattering media: wavefront shaping meets multidimensional time series](https://arxiv.org/abs/2210.04033)|[online_learning_tm](https://github.com/labogigan/online_learning_tm)| -|[correlative information maximization based biologically plausible neural networks for correlated source separation](https://arxiv.org/abs/2210.04222)|[Biologically-Plausible-Correlative-Information-Maximization-for-Blind-Source-Separation](https://github.com/BariscanBozkurt/Biologically-Plausible-Correlative-Information-Maximization-for-Blind-Source-Separation)| -|[rhombic grids reduce the number of voxels in fast pulse-echo ultrasound imaging](https://arxiv.org/abs/2210.04818)|[rhombic_grids](https://github.com/mschiffn/rhombic_grids)| -|[coinpress: practical private mean and covariance estimation](https://arxiv.org/abs/2006.06618)|[coin-press](https://github.com/twistedcubic/coin-press)| -|[constrained optimal querying: huffman coding and beyond](https://arxiv.org/abs/2210.04013)|[constrained-optimal-querying-huffman-coding-and-beyond](https://github.com/madcreeper/constrained-optimal-querying-huffman-coding-and-beyond)| +|date|paper|code| +|---|---|---| +|2210.02214|[urglq: an efficient covariance matrix reconstruction method for robust adaptive beamforming](https://arxiv.org/abs/2210.02214)|[robust-adaptive-beamforming-2022](https://github.com/chenpengseu/robust-adaptive-beamforming-2022)| +|2210.04033|[online learning of the transfer matrix of dynamic scattering media: wavefront shaping meets multidimensional time series](https://arxiv.org/abs/2210.04033)|[online_learning_tm](https://github.com/labogigan/online_learning_tm)| +|2210.04222|[correlative information maximization based biologically plausible neural networks for correlated source separation](https://arxiv.org/abs/2210.04222)|[Biologically-Plausible-Correlative-Information-Maximization-for-Blind-Source-Separation](https://github.com/BariscanBozkurt/Biologically-Plausible-Correlative-Information-Maximization-for-Blind-Source-Separation)| +|2210.04818|[rhombic grids reduce the number of voxels in fast pulse-echo ultrasound imaging](https://arxiv.org/abs/2210.04818)|[rhombic_grids](https://github.com/mschiffn/rhombic_grids)| +|2210.04013|[constrained optimal querying: huffman coding and beyond](https://arxiv.org/abs/2210.04013)|[constrained-optimal-querying-huffman-coding-and-beyond](https://github.com/madcreeper/constrained-optimal-querying-huffman-coding-and-beyond)| ## 2022-10-10 -|paper|code| -|---|---| -|[experiments with mmwave automotive radar test-bed](https://arxiv.org/abs/1912.12566)|[mmWave-radar-signal-processing-and-microDoppler-classification](https://github.com/Xiangyu-Gao/mmWave-radar-signal-processing-and-microDoppler-classification)| +|date|paper|code| +|---|---|---| ## 2022-10-07 -|paper|code| -|---|---| -|[role of deep learning in wireless communications](https://arxiv.org/abs/2210.02596)|[DL-DSC-FDD-Massive-MIMO](https://github.com/foadsohrabi/DL-DSC-FDD-Massive-MIMO)| -|[few-shot calibration of set predictors via meta-learned cross-validation-based conformal prediction](https://arxiv.org/abs/2210.03067)|[meta-xb](https://github.com/kclip/meta-xb)| -|[efficient sequence packing without cross-contamination: accelerating large language models without impacting performance](https://arxiv.org/abs/2107.02027)|[packedBERT](https://github.com/graphcore/tutorials/tree/sdk-release-2.1/blogs_code/packedBERT)| -|[grassmannian packings: trust-region stochastic tuning for matrix incoherence](https://arxiv.org/abs/2207.06374)|[trstmi](https://github.com/josiahpark/trstmi)| -|[orthogonal non-negative matrix factorization: a maximum-entropy-principle approach](https://arxiv.org/abs/2210.02672)|[mep-orthogonal-nmf](https://github.com/salar96/mep-orthogonal-nmf)| +|date|paper|code| +|---|---|---| +|2210.02596|[role of deep learning in wireless communications](https://arxiv.org/abs/2210.02596)|[DL-DSC-FDD-Massive-MIMO](https://github.com/foadsohrabi/DL-DSC-FDD-Massive-MIMO)| +|2210.03067|[few-shot calibration of set predictors via meta-learned cross-validation-based conformal prediction](https://arxiv.org/abs/2210.03067)|[meta-xb](https://github.com/kclip/meta-xb)| +|2210.02672|[orthogonal non-negative matrix factorization: a maximum-entropy-principle approach](https://arxiv.org/abs/2210.02672)|[mep-orthogonal-nmf](https://github.com/salar96/mep-orthogonal-nmf)| ## 2022-10-06 -|paper|code| -|---|---| -|[generalised implicit neural representations](https://arxiv.org/abs/2205.15674)|[ginr](https://github.com/danielegrattarola/ginr)| -|[learning the spectrogram temporal resolution for audio classification](https://arxiv.org/abs/2210.01719)|[diffres-python](https://github.com/haoheliu/diffres-python)| -|[matt: a manifold attention network for eeg decoding](https://arxiv.org/abs/2210.01986)|[matt](https://github.com/cecnl/matt)| +|date|paper|code| +|---|---|---| +|2210.01719|[learning the spectrogram temporal resolution for audio classification](https://arxiv.org/abs/2210.01719)|[diffres-python](https://github.com/haoheliu/diffres-python)| +|2210.01986|[matt: a manifold attention network for eeg decoding](https://arxiv.org/abs/2210.01986)|[matt](https://github.com/cecnl/matt)| ## 2022-10-05 -|paper|code| -|---|---| -|[diagnosis of parkinson's disease based on voice signals using shap and hard voting ensemble method](https://arxiv.org/abs/2210.01205)|[classification_of_parkinson_disease](https://github.com/pariaghaheri/classification_of_parkinson_disease)| -|[do language models make human-like predictions about the coreferents of italian anaphoric zero pronouns?](https://arxiv.org/abs/2208.14554)|[italian-zero-anaphora-prediction](https://github.com/jmichaelov/italian-zero-anaphora-prediction)| -|[overparameterized relu neural networks learn the simplest models: neural isometry and exact recovery](https://arxiv.org/abs/2209.15265)|[neural-recovery](https://github.com/pilancilab/neural-recovery)| +|date|paper|code| +|---|---|---| +|2210.01205|[diagnosis of parkinson's disease based on voice signals using shap and hard voting ensemble method](https://arxiv.org/abs/2210.01205)|[classification_of_parkinson_disease](https://github.com/pariaghaheri/classification_of_parkinson_disease)| ## 2022-10-04 -|paper|code| -|---|---| -|[uncertainty detection and reduction in neural decoding of eeg signals](https://arxiv.org/abs/2201.00627)|[ue-eeg](https://github.com/tiehangd/ue-eeg)| -|[unsupervised multimodal change detection based on structural relationship graph representation learning](https://arxiv.org/abs/2210.00941)|[srgcae](https://github.com/chenhongruixuan/srgcae)| +|date|paper|code| +|---|---|---| +|2210.00941|[unsupervised multimodal change detection based on structural relationship graph representation learning](https://arxiv.org/abs/2210.00941)|[srgcae](https://github.com/chenhongruixuan/srgcae)| ## 2022-10-03 -|paper|code| -|---|---| -|[end-to-end p300 bci using bayesian accumulation of riemannian probabilities](https://arxiv.org/abs/2203.07807)|[demos](https://github.com/timeflux/demos)| -|[near lossless time series data compression methods using statistics and deviation](https://arxiv.org/abs/2209.14162)|[data-compression](https://github.com/vidhi0206/data-compression)| -|[ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices](https://arxiv.org/abs/2209.15146)|[stress](https://github.com/xalentis/stress)| -|[rf-transformer: a unified backscatter radio hardware abstraction](https://arxiv.org/abs/2209.15195)|[rf-transformer](https://github.com/lefscc/rf-transformer)| -|[astf: visual abstractions of time-varying patterns in radio signals](https://arxiv.org/abs/2209.15223)|[astf](https://github.com/csuvis/astf)| -|[tinyturbo: efficient turbo decoders on edge](https://arxiv.org/abs/2209.15614)|[tinyturbo](https://github.com/hebbarashwin/tinyturbo)| -|[construction of optimal spectral methods in phase retrieval](https://arxiv.org/abs/2012.04524)|[Optimal_Spectral_Methods_PR](https://github.com/AnMaillard/Optimal_Spectral_Methods_PR)| -|[optimal denoising of rotationally invariant rectangular matrices](https://arxiv.org/abs/2203.07752)|[rectangular_rie](https://github.com/penombraet/rectangular_rie)| -|[self-stabilization: the implicit bias of gradient descent at the edge of stability](https://arxiv.org/abs/2209.15594)|[eos](https://github.com/adamian98/eos)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/11.md b/archives/2022/11.md index d959f8c2..55a2a288 100644 --- a/archives/2022/11.md +++ b/archives/2022/11.md @@ -1,196 +1,139 @@ # November 2022 Archive ## 2022-11-30 -|paper|code| -|---|---| -|[music source separation with generative flow](https://arxiv.org/abs/2204.09079)|[generativesourceseparation](https://github.com/gzhu06/generativesourceseparation)| -|[parallel faceted imaging in radio interferometry via proximal splitting (faceted hypersara): ii. code and real data proof of concept](https://arxiv.org/abs/2209.07604)|[faceted-hypersara](https://github.com/basp-group/faceted-hypersara)| -|[defending adversarial attacks on deep learning based power allocation in massive mimo using denoising autoencoders](https://arxiv.org/abs/2211.15365)|[dae_for_adv_attacks_in_mimo](https://github.com/jess-jpg-txt/dae_for_adv_attacks_in_mimo)| -|[medalcare-xl: 16,900 healthy and pathological 12 lead ecgs obtained through electrophysiological simulations](https://arxiv.org/abs/2211.15997)|[fim_eikonal](https://github.com/kit-ibt/fim_eikonal)| -|[sketch-and-solve approaches to k-means clustering by semidefinite programming](https://arxiv.org/abs/2211.15744)|[sketch-and-solve_kmeans](https://github.com/kkylie/sketch-and-solve_kmeans)| +|date|paper|code| +|---|---|---| +|2211.15365|[defending adversarial attacks on deep learning based power allocation in massive mimo using denoising autoencoders](https://arxiv.org/abs/2211.15365)|[dae_for_adv_attacks_in_mimo](https://github.com/jess-jpg-txt/dae_for_adv_attacks_in_mimo)| +|2211.15997|[medalcare-xl: 16,900 healthy and pathological 12 lead ecgs obtained through electrophysiological simulations](https://arxiv.org/abs/2211.15997)|[fim_eikonal](https://github.com/kit-ibt/fim_eikonal)| +|2211.15744|[sketch-and-solve approaches to k-means clustering by semidefinite programming](https://arxiv.org/abs/2211.15744)|[sketch-and-solve_kmeans](https://github.com/kkylie/sketch-and-solve_kmeans)| ## 2022-11-29 -|paper|code| -|---|---| -|[deformable radar polygon: a lightweight and predictable occupancy representation for short-range collision avoidance](https://arxiv.org/abs/2203.01442)|[deformable_radar_polygon_occupancy_representation](https://github.com/xiangyu-gao/deformable_radar_polygon_occupancy_representation)| -|[surimi: supervised radio map augmentation with deep learning and a generative adversarial network for fingerprint-based indoor positioning](https://arxiv.org/abs/2207.06120)|[surimi](https://github.com/darwinquezada/surimi)| -|[semi-supervised specific emitter identification method using metric-adversarial training](https://arxiv.org/abs/2211.15379)|[mat-based-ss-sei](https://github.com/lovelymimola/mat-based-ss-sei)| -|[discovering dynamic patterns from spatiotemporal data with time-varying low-rank autoregression](https://arxiv.org/abs/2211.15482)|[vars](https://github.com/xinychen/vars)| +|date|paper|code| +|---|---|---| +|2211.15379|[semi-supervised specific emitter identification method using metric-adversarial training](https://arxiv.org/abs/2211.15379)|[mat-based-ss-sei](https://github.com/lovelymimola/mat-based-ss-sei)| +|2211.15482|[discovering dynamic patterns from spatiotemporal data with time-varying low-rank autoregression](https://arxiv.org/abs/2211.15482)|[vars](https://github.com/xinychen/vars)| ## 2022-11-28 -|paper|code| -|---|---| -|[low-complexity near-optimum symbol detection based on neural enhancement of factor graphs](https://arxiv.org/abs/2203.16417)|[gap](https://github.com/kit-cel/gap)| -|[biologically-plausible determinant maximization neural networks for blind separation of correlated sources](https://arxiv.org/abs/2209.12894)|[biologically-plausible-detmaxnns-for-blind-source-separation](https://github.com/bariscanbozkurt/biologically-plausible-detmaxnns-for-blind-source-separation)| -|[conditioning and sampling in variational diffusion models for speech super-resolution](https://arxiv.org/abs/2210.15793)|[diffwave-sr](https://github.com/yoyololicon/diffwave-sr)| -|[quantized compressed sensing with score-based generative models](https://arxiv.org/abs/2211.13006)|[qcs-sgm](https://github.com/mengxiangming/qcs-sgm)| -|[structured gradient descent for fast robust low-rank hankel matrix completion](https://arxiv.org/abs/2204.03316)|[hsgd](https://github.com/caesarcai/hsgd)| +|date|paper|code| +|---|---|---| +|2211.13006|[quantized compressed sensing with score-based generative models](https://arxiv.org/abs/2211.13006)|[qcs-sgm](https://github.com/mengxiangming/qcs-sgm)| ## 2022-11-24 -|paper|code| -|---|---| -|[evaluation of interpretability for deep learning algorithms in eeg emotion recognition: a case study in autism](https://arxiv.org/abs/2111.13208)|[deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals](https://github.com/meiyor/deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals)| -|[pan-tompkins++: a robust approach to detect r-peaks in ecg signals](https://arxiv.org/abs/2211.03171)|[Pan-Tompkins-Plus-Plus](https://github.com/Niaz-Imtiaz/Pan-Tompkins-Plus-Plus)| -|[evaluating feature attribution methods for electrocardiogram](https://arxiv.org/abs/2211.12702)|[attribution-ecg](https://github.com/snu-drl/attribution-ecg)| -|[challenges in gaussian processes for non intrusive load monitoring](https://arxiv.org/abs/2211.13018)|[nilm_gp](https://github.com/aadesh-1404/nilm_gp)| -|[eeg aided boosting of single-lead ecg based sleep staging with deep knowledge distillation](https://arxiv.org/abs/2211.13125)|[sleep_staging_kd](https://github.com/acrophase/sleep_staging_kd)| -|[imitation learning-based implicit semantic-aware communication networks: multi-layer representation and collaborative reasoning](https://arxiv.org/abs/2210.16118)|[irml](https://github.com/zjs919/irml)| -|[verified reversible programming for verified lossless compression](https://arxiv.org/abs/2211.09676)|[flipper](https://github.com/j-towns/flipper)| -|[diffusion model based posterior sampling for noisy linear inverse problems](https://arxiv.org/abs/2211.12343)|[dmps](https://github.com/mengxiangming/dmps)| +|date|paper|code| +|---|---|---| +|2211.03171|[pan-tompkins++: a robust approach to detect r-peaks in ecg signals](https://arxiv.org/abs/2211.03171)|[Pan-Tompkins-Plus-Plus](https://github.com/Niaz-Imtiaz/Pan-Tompkins-Plus-Plus)| +|2211.12702|[evaluating feature attribution methods for electrocardiogram](https://arxiv.org/abs/2211.12702)|[attribution-ecg](https://github.com/snu-drl/attribution-ecg)| +|2211.13018|[challenges in gaussian processes for non intrusive load monitoring](https://arxiv.org/abs/2211.13018)|[nilm_gp](https://github.com/aadesh-1404/nilm_gp)| +|2211.13125|[eeg aided boosting of single-lead ecg based sleep staging with deep knowledge distillation](https://arxiv.org/abs/2211.13125)|[sleep_staging_kd](https://github.com/acrophase/sleep_staging_kd)| +|2211.09676|[verified reversible programming for verified lossless compression](https://arxiv.org/abs/2211.09676)|[flipper](https://github.com/j-towns/flipper)| +|2211.12343|[diffusion model based posterior sampling for noisy linear inverse problems](https://arxiv.org/abs/2211.12343)|[dmps](https://github.com/mengxiangming/dmps)| ## 2022-11-23 -|paper|code| -|---|---| -|[graph neural networks with parallel neighborhood aggregations for graph classification](https://arxiv.org/abs/2111.11482)|[spin](https://github.com/siddhant-doshi/spin)| -|[communication-efficient stochastic zeroth-order optimization for federated learning](https://arxiv.org/abs/2201.09531)|[FedZO](https://github.com/noobyzy/FedZO)| -|[meta-af: meta-learning for adaptive filters](https://arxiv.org/abs/2204.11942)|[metaaf](https://github.com/adobe-research/metaaf)| -|[transforming ris-assisted passive beamforming from tedious to simple: a relaxation algorithm for rician channel](https://arxiv.org/abs/2211.06555)|[relaxation-algorithm-on-ris-miso](https://github.com/dwyanedong/relaxation-algorithm-on-ris-miso)| -|[olia: an open-source digital lock-in amplifier](https://arxiv.org/abs/2211.08889)|[olia](https://github.com/openlockin/olia)| -|[ontology-aware learning and evaluation for audio tagging](https://arxiv.org/abs/2211.12195)|[ontology-aware-audio-tagging](https://github.com/haoheliu/ontology-aware-audio-tagging)| -|[quasifibrations of graphs to find symmetries in biological networks](https://arxiv.org/abs/2111.06999)|[qf](https://github.com/boldip/qf)| -|[blind super-resolution of point sources via projected gradient descent](https://arxiv.org/abs/2112.01077)|[pgdvhl](https://github.com/jcchen2017/pgdvhl)| -|[rate-distortion theoretic bounds on generalization error for distributed learning](https://arxiv.org/abs/2206.02604)|[datascience](https://github.com/romainchor/datascience)| +|date|paper|code| +|---|---|---| +|2211.06555|[transforming ris-assisted passive beamforming from tedious to simple: a relaxation algorithm for rician channel](https://arxiv.org/abs/2211.06555)|[relaxation-algorithm-on-ris-miso](https://github.com/dwyanedong/relaxation-algorithm-on-ris-miso)| +|2211.08889|[olia: an open-source digital lock-in amplifier](https://arxiv.org/abs/2211.08889)|[olia](https://github.com/openlockin/olia)| +|2211.12195|[ontology-aware learning and evaluation for audio tagging](https://arxiv.org/abs/2211.12195)|[ontology-aware-audio-tagging](https://github.com/haoheliu/ontology-aware-audio-tagging)| ## 2022-11-22 -|paper|code| -|---|---| -|[openfwi: large-scale multi-structural benchmark datasets for seismic full waveform inversion](https://arxiv.org/abs/2111.02926)|[openfwi](https://github.com/lanl/openfwi)| -|[pmnet: robust pathloss map prediction via supervised learning](https://arxiv.org/abs/2211.10527)|[pmnet](https://github.com/abman23/pmnet)| -|[spatiotemporal modeling of multivariate signals with graph neural networks and structured state space models](https://arxiv.org/abs/2211.11176)|[graphs4mer](https://github.com/tsy935/graphs4mer)| -|[motor imagery decoding using ensemble curriculum learning and collaborative training](https://arxiv.org/abs/2211.11460)|[ensemble-mi](https://github.com/gzoumpourlis/ensemble-mi)| -|[neural network based generation of 1-dimensional stochastic fields with turbulent velocity statistics](https://arxiv.org/abs/2211.11580)|[nn-turb](https://github.com/cgranerob/nn-turb)| -|[nonlinear information bottleneck](https://arxiv.org/abs/1705.02436)|[nonlinear-IB-PyTorch](https://github.com/burklight/nonlinear-IB-PyTorch)| -|[a novel approach to the partial information decomposition](https://arxiv.org/abs/1908.08642)|[redundancy](https://github.com/artemyk/redundancy)| -|[diffeomorphic information neural estimation](https://arxiv.org/abs/2211.10856)|[dine](https://github.com/baosws/dine)| +|date|paper|code| +|---|---|---| +|2211.10527|[pmnet: robust pathloss map prediction via supervised learning](https://arxiv.org/abs/2211.10527)|[pmnet](https://github.com/abman23/pmnet)| +|2211.11176|[spatiotemporal modeling of multivariate signals with graph neural networks and structured state space models](https://arxiv.org/abs/2211.11176)|[graphs4mer](https://github.com/tsy935/graphs4mer)| +|2211.11460|[motor imagery decoding using ensemble curriculum learning and collaborative training](https://arxiv.org/abs/2211.11460)|[ensemble-mi](https://github.com/gzoumpourlis/ensemble-mi)| +|2211.11580|[neural network based generation of 1-dimensional stochastic fields with turbulent velocity statistics](https://arxiv.org/abs/2211.11580)|[nn-turb](https://github.com/cgranerob/nn-turb)| +|2211.10856|[diffeomorphic information neural estimation](https://arxiv.org/abs/2211.10856)|[dine](https://github.com/baosws/dine)| ## 2022-11-21 -|paper|code| -|---|---| -|[arrhythmia classification using cgan-augmented ecg signals](https://arxiv.org/abs/2202.00569)|[augmentation-of-ecg-training-dataset-with-cgan](https://github.com/mah533/augmentation-of-ecg-training-dataset-with-cgan)| -|[sinusoidal frequency estimation by gradient descent](https://arxiv.org/abs/2210.14476)|[sinusoidal-gradient-descent](https://github.com/ben-hayes/sinusoidal-gradient-descent)| -|[sar-based landslide classification pretraining leads to better segmentation](https://arxiv.org/abs/2211.09927)|[sar-landslide-detection-pretraining](https://github.com/vmboehm/sar-landslide-detection-pretraining)| -|[astrometric calibration and source characterisation of the latest generation neuromorphic event-based cameras for space imaging](https://arxiv.org/abs/2211.09939)|[icns_noralph_event_based-space_imaging-speed_dataset](https://github.com/nicralph213/icns_noralph_event_based-space_imaging-speed_dataset)| -|[towards fast single-trial online erp based brain-computer interface using dry eeg electrodes and neural networks: a pilot study](https://arxiv.org/abs/2211.10352)|[stimusto](https://github.com/okbalefthanded/stimusto)| +|date|paper|code| +|---|---|---| +|2211.09927|[sar-based landslide classification pretraining leads to better segmentation](https://arxiv.org/abs/2211.09927)|[sar-landslide-detection-pretraining](https://github.com/vmboehm/sar-landslide-detection-pretraining)| +|2211.09939|[astrometric calibration and source characterisation of the latest generation neuromorphic event-based cameras for space imaging](https://arxiv.org/abs/2211.09939)|[icns_noralph_event_based-space_imaging-speed_dataset](https://github.com/nicralph213/icns_noralph_event_based-space_imaging-speed_dataset)| +|2211.10352|[towards fast single-trial online erp based brain-computer interface using dry eeg electrodes and neural networks: a pilot study](https://arxiv.org/abs/2211.10352)|[stimusto](https://github.com/okbalefthanded/stimusto)| ## 2022-11-18 -|paper|code| -|---|---| -|[deep reinforcement learning based joint downlink beamforming and ris configuration in ris-aided mu-miso systems under hardware impairments and imperfect csi](https://arxiv.org/abs/2211.09702)|[ris-miso-pda-deep-reinforcement-learning](https://github.com/baturaysaglam/ris-miso-pda-deep-reinforcement-learning)| -|[sigt: an efficient end-to-end mimo-ofdm receiver framework based on transformer](https://arxiv.org/abs/2211.09712)|[sigt](https://github.com/sigtransformer/sigt)| -|[efficient urllc with a reconfigurable intelligent surface and imperfect device tracking](https://arxiv.org/abs/2211.09171)|[efficient-ris-aided-urllc](https://github.com/aau-cnt/efficient-ris-aided-urllc)| +|date|paper|code| +|---|---|---| +|2211.09702|[deep reinforcement learning based joint downlink beamforming and ris configuration in ris-aided mu-miso systems under hardware impairments and imperfect csi](https://arxiv.org/abs/2211.09702)|[ris-miso-pda-deep-reinforcement-learning](https://github.com/baturaysaglam/ris-miso-pda-deep-reinforcement-learning)| +|2211.09712|[sigt: an efficient end-to-end mimo-ofdm receiver framework based on transformer](https://arxiv.org/abs/2211.09712)|[sigt](https://github.com/sigtransformer/sigt)| +|2211.09171|[efficient urllc with a reconfigurable intelligent surface and imperfect device tracking](https://arxiv.org/abs/2211.09171)|[efficient-ris-aided-urllc](https://github.com/aau-cnt/efficient-ris-aided-urllc)| ## 2022-11-17 -|paper|code| -|---|---| -|[one-bit mmwave mimo channel estimation using deep generative networks](https://arxiv.org/abs/2211.08635)|[obq-gan-mimo-ce](https://github.com/akashsdoshi96/obq-gan-mimo-ce)| -|[mcnet: fuse multiple cues for multichannel speech enhancement](https://arxiv.org/abs/2211.08872)|[mcnet](https://github.com/audio-westlakeu/mcnet)| -|[olia: an open-source digital lock-in amplifier](https://arxiv.org/abs/2211.08889)|[olia](https://github.com/openlockin/olia)| -|[detecting train driveshaft damages using accelerometer signals and differential convolutional neural networks](https://arxiv.org/abs/2211.09011)|[crack-detection-railway-axles-deep-learning](https://github.com/antialopezg/crack-detection-railway-axles-deep-learning)| -|[what has been enhanced in my knowledge-enhanced language model?](https://arxiv.org/abs/2202.00964)|[gcs_ki](https://github.com/yifan-h/gcs_ki)| +|date|paper|code| +|---|---|---| +|2211.08635|[one-bit mmwave mimo channel estimation using deep generative networks](https://arxiv.org/abs/2211.08635)|[obq-gan-mimo-ce](https://github.com/akashsdoshi96/obq-gan-mimo-ce)| +|2211.08872|[mcnet: fuse multiple cues for multichannel speech enhancement](https://arxiv.org/abs/2211.08872)|[mcnet](https://github.com/audio-westlakeu/mcnet)| +|2211.08889|[olia: an open-source digital lock-in amplifier](https://arxiv.org/abs/2211.08889)|[olia](https://github.com/openlockin/olia)| +|2211.09011|[detecting train driveshaft damages using accelerometer signals and differential convolutional neural networks](https://arxiv.org/abs/2211.09011)|[crack-detection-railway-axles-deep-learning](https://github.com/antialopezg/crack-detection-railway-axles-deep-learning)| ## 2022-11-16 -|paper|code| -|---|---| -|[link scheduling using graph neural networks](https://arxiv.org/abs/2109.05536)|[distgcn](https://github.com/zhongyuanzhao/distgcn)| -|[a tutorial on terahertz-band localization for 6g communication systems](https://arxiv.org/abs/2110.08581)|[radio_localization](https://github.com/chenhui07c8/radio_localization)| -|[end-to-end p300 bci using bayesian accumulation of riemannian probabilities](https://arxiv.org/abs/2203.07807)|[demos](https://github.com/timeflux/demos)| -|[data augmentation for learning predictive models on eeg: a systematic comparison](https://arxiv.org/abs/2206.14483)|[eeg-augmentation-benchmark-2022](https://github.com/eeg-augmentation-benchmark/eeg-augmentation-benchmark-2022)| -|[towards v2i age-aware fairness access: a dqn based intelligent vehicular node training and test method](https://arxiv.org/abs/2208.01283)|[age-fairness](https://github.com/qiongwu86/age-fairness)| -|[motif-topology improved spiking neural network for the cocktail party effect and mcgurk effect](https://arxiv.org/abs/2211.07641)|[motif-snn](https://github.com/thomasaimondy/motif-snn)| -|[machine learning methods applied to cortico-cortical evoked potentials aid in localizing seizure onset zones](https://arxiv.org/abs/2211.07867)|[ml4hsoz](https://github.com/iangmalone/ml4hsoz)| -|[cardiacgen: a hierarchical deep generative model for cardiac signals](https://arxiv.org/abs/2211.08385)|[cardiac_gen_model](https://github.com/SENSE-Lab-OSU/cardiac_gen_model)| -|[almost optimal variance-constrained best arm identification](https://arxiv.org/abs/2201.10142)|[va-bai](https://github.com/y-hou/va-bai)| +|date|paper|code| +|---|---|---| +|2211.07641|[motif-topology improved spiking neural network for the cocktail party effect and mcgurk effect](https://arxiv.org/abs/2211.07641)|[motif-snn](https://github.com/thomasaimondy/motif-snn)| +|2211.07867|[machine learning methods applied to cortico-cortical evoked potentials aid in localizing seizure onset zones](https://arxiv.org/abs/2211.07867)|[ml4hsoz](https://github.com/iangmalone/ml4hsoz)| +|2211.08385|[cardiacgen: a hierarchical deep generative model for cardiac signals](https://arxiv.org/abs/2211.08385)|[cardiac_gen_model](https://github.com/SENSE-Lab-OSU/cardiac_gen_model)| ## 2022-11-15 -|paper|code| -|---|---| -|[universal adversarial perturbations for cnn classifiers in eeg-based bcis](https://arxiv.org/abs/1912.01171)|[UAP_EEG](https://github.com/ZihanLiu95/UAP_EEG)| -|[tiny noise, big mistakes: adversarial perturbations induce errors in brain-computer interface spellers](https://arxiv.org/abs/2001.11569)|[Speller-Attacks](https://github.com/ZhangXiao96/Speller-Attacks)| -|[reconfigurable intelligent surface phase hopping for ultra-reliable communications](https://arxiv.org/abs/2107.11852)|[ris-phase-hopping](https://github.com/klb2/ris-phase-hopping)| -|[a dataset and baseline approach for identifying usage states from non-intrusive power sensing with midas iot-based sensors](https://arxiv.org/abs/2209.00987)|[poweriot-state-identification](https://github.com/ai4society/poweriot-state-identification)| -|[transforming ris-assisted passive beamforming from tedious to simple: a relaxation algorithm for rician channel](https://arxiv.org/abs/2211.06555)|[relaxation-algorithm-on-ris-miso](https://github.com/dwyanedong/relaxation-algorithm-on-ris-miso)| -|[advancing the state-of-the-art for ecg analysis through structured state space models](https://arxiv.org/abs/2211.07579)|[ssm_ecg](https://github.com/tmehari/ssm_ecg)| -|[wyner-ziv estimators for distributed mean estimation with side information and optimization](https://arxiv.org/abs/2011.12160)|[wz_estimators](https://github.com/shubhamjha-46/wz_estimators)| -|[hybrid hmm decoder for convolutional codes by joint trellis-like structure and channel prior](https://arxiv.org/abs/2210.14749)|[hmm-decoder](https://github.com/haoyyli/hmm-decoder)| -|[multi-user frequency assignment for ultra-reliable mmwave two-ray channels](https://arxiv.org/abs/2211.07204)|[frequency-assignment-qmkp](https://github.com/klb2/frequency-assignment-qmkp)| +|date|paper|code| +|---|---|---| +|2211.06555|[transforming ris-assisted passive beamforming from tedious to simple: a relaxation algorithm for rician channel](https://arxiv.org/abs/2211.06555)|[relaxation-algorithm-on-ris-miso](https://github.com/dwyanedong/relaxation-algorithm-on-ris-miso)| +|2211.07579|[advancing the state-of-the-art for ecg analysis through structured state space models](https://arxiv.org/abs/2211.07579)|[ssm_ecg](https://github.com/tmehari/ssm_ecg)| +|2211.07204|[multi-user frequency assignment for ultra-reliable mmwave two-ray channels](https://arxiv.org/abs/2211.07204)|[frequency-assignment-qmkp](https://github.com/klb2/frequency-assignment-qmkp)| ## 2022-11-14 -|paper|code| -|---|---| -|[learning sparse analytic filters for piano transcription](https://arxiv.org/abs/2108.10382)|[sparse-analytic-filters](https://github.com/cwitkowitz/sparse-analytic-filters)| -|[on low-rank trace regression under general sampling distribution](https://arxiv.org/abs/1904.08576)|[cv-impute](https://github.com/mohsenbayati/cv-impute)| +|date|paper|code| +|---|---|---| ## 2022-11-11 -|paper|code| -|---|---| -|[gradient-based learning of discrete structured measurement operators for signal recovery](https://arxiv.org/abs/2202.03391)|[glodismo](https://github.com/josauder/glodismo)| -|[graph neural networks for community detection on sparse graphs](https://arxiv.org/abs/2211.03231)|[gnn_community_detection](https://github.com/nhuang37/gnn_community_detection)| -|[the entropy rate of linear additive markov processes](https://arxiv.org/abs/2211.05350)|[LAMPEntropyEstimates](https://github.com/bridget-smart/LAMPEntropyEstimates)| +|date|paper|code| +|---|---|---| +|2211.03231|[graph neural networks for community detection on sparse graphs](https://arxiv.org/abs/2211.03231)|[gnn_community_detection](https://github.com/nhuang37/gnn_community_detection)| +|2211.05350|[the entropy rate of linear additive markov processes](https://arxiv.org/abs/2211.05350)|[LAMPEntropyEstimates](https://github.com/bridget-smart/LAMPEntropyEstimates)| ## 2022-11-10 -|paper|code| -|---|---| -|[toward reliable signals decoding for electroencephalogram: a benchmark study to eegnex](https://arxiv.org/abs/2207.12369)|[eegnex](https://github.com/chenxiachan/eegnex)| -|[optimal discrete beamforming of reconfigurable intelligent surface](https://arxiv.org/abs/2211.04167)|[RIS_Optimization](https://github.com/RujingXiong/RIS_Optimization)| -|[phaseaug: a differentiable augmentation for speech synthesis to simulate one-to-many mapping](https://arxiv.org/abs/2211.04610)|[phaseaug](https://github.com/mindslab-ai/phaseaug)| -|[estimation of signal parameters using deep convolutional neural networks](https://arxiv.org/abs/2211.04846)|[deepest-demo](https://huggingface.co/spaces/EMS-TU-Ilmenau/deepest-demo)| -|[quantization adaptor for bit-level deep learning-based massive mimo csi feedback](https://arxiv.org/abs/2211.02937)|[qcrnet](https://github.com/zhang-xd18/qcrnet)| +|date|paper|code| +|---|---|---| +|2211.04167|[optimal discrete beamforming of reconfigurable intelligent surface](https://arxiv.org/abs/2211.04167)|[RIS_Optimization](https://github.com/RujingXiong/RIS_Optimization)| +|2211.04610|[phaseaug: a differentiable augmentation for speech synthesis to simulate one-to-many mapping](https://arxiv.org/abs/2211.04610)|[phaseaug](https://github.com/mindslab-ai/phaseaug)| +|2211.04846|[estimation of signal parameters using deep convolutional neural networks](https://arxiv.org/abs/2211.04846)|[deepest-demo](https://huggingface.co/spaces/EMS-TU-Ilmenau/deepest-demo)| +|2211.02937|[quantization adaptor for bit-level deep learning-based massive mimo csi feedback](https://arxiv.org/abs/2211.02937)|[qcrnet](https://github.com/zhang-xd18/qcrnet)| ## 2022-11-09 -|paper|code| -|---|---| -|[mimo channel estimation using score-based generative models](https://arxiv.org/abs/2204.07122)|[score-based-channels](https://github.com/utcsilab/score-based-channels)| -|[causal discovery in linear structural causal models with deterministic relations](https://arxiv.org/abs/2111.00341)|[propagation-scm](https://github.com/yuqin-yang/propagation-scm)| -|[causal discovery in linear latent variable models subject to measurement error](https://arxiv.org/abs/2211.03984)|[sem-me-ur](https://github.com/yuqin-yang/sem-me-ur)| -|[bounded guaranteed algorithms for concave impurity minimization via maximum likelihood](https://arxiv.org/abs/2211.04430)|[linear_clustering](https://github.com/hoangle96/linear_clustering)| +|date|paper|code| +|---|---|---| +|2211.03984|[causal discovery in linear latent variable models subject to measurement error](https://arxiv.org/abs/2211.03984)|[sem-me-ur](https://github.com/yuqin-yang/sem-me-ur)| +|2211.04430|[bounded guaranteed algorithms for concave impurity minimization via maximum likelihood](https://arxiv.org/abs/2211.04430)|[linear_clustering](https://github.com/hoangle96/linear_clustering)| ## 2022-11-08 -|paper|code| -|---|---| -|[sharp: environment and person independent activity recognition with commodity ieee 802.11 access points](https://arxiv.org/abs/2103.09924)|[sharp](https://github.com/signetlabdei/sharp)| -|[efficient deep learning-based estimation of the vital signs on smartphones](https://arxiv.org/abs/2204.08989)|[mtvital](https://github.com/mahdifarvardin/mtvital)| -|[towards efficient ecg-based atrial fibrillation detection via parameterised hypercomplex neural networks](https://arxiv.org/abs/2211.02678)|[hypercomplexecg](https://github.com/leibniz-future-lab/hypercomplexecg)| -|[malgrid: visualization of binary features in large malware corpora](https://arxiv.org/abs/2211.02696)|[MalGrid](https://github.com/Mayachitra-Inc/MalGrid)| -|[samo: speaker attractor multi-center one-class learning for voice anti-spoofing](https://arxiv.org/abs/2211.02718)|[samo](https://github.com/sivannavis/samo)| -|[deep learning for rapid landslide detection using synthetic aperture radar (sar) datacubes](https://arxiv.org/abs/2211.02869)|[landslide-sar-unet](https://github.com/iprapas/landslide-sar-unet)| -|[neural multi-event forecasting on spatio-temporal point processes using probabilistically enriched transformers](https://arxiv.org/abs/2211.02922)|[neural-spatio-temporal-probabilistic-transformers](https://github.com/negar-erfanian/neural-spatio-temporal-probabilistic-transformers)| -|[pan-tompkins++: a robust approach to detect r-peaks in ecg signals](https://arxiv.org/abs/2211.03171)|[Pan-Tompkins-Plus-Plus](https://github.com/Niaz-Imtiaz/Pan-Tompkins-Plus-Plus)| -|[pygsl: a graph structure learning toolkit](https://arxiv.org/abs/2211.03583)|[pygsl](https://github.com/maxwass/pygsl)| -|[unifying approaches in active learning and active sampling via fisher information and information-theoretic quantities](https://arxiv.org/abs/2208.00549)|[2208.00549](https://github.com/blackhc/2208.00549)| -|[hybrid hmm decoder for convolutional codes by joint trellis-like structure and channel prior](https://arxiv.org/abs/2210.14749)|[hmm-decoder](https://github.com/haoyyli/hmm-decoder)| -|[fas-unet: a novel fas-driven unet to learn variational image segmentation](https://arxiv.org/abs/2210.15164)|[fasunet](https://github.com/zhuhui100/fasunet)| -|[inductive graph transformer for delivery time estimation](https://arxiv.org/abs/2211.02863)|[igt-wsdm23](https://github.com/enoche/igt-wsdm23)| +|date|paper|code| +|---|---|---| +|2211.02678|[towards efficient ecg-based atrial fibrillation detection via parameterised hypercomplex neural networks](https://arxiv.org/abs/2211.02678)|[hypercomplexecg](https://github.com/leibniz-future-lab/hypercomplexecg)| +|2211.02696|[malgrid: visualization of binary features in large malware corpora](https://arxiv.org/abs/2211.02696)|[MalGrid](https://github.com/Mayachitra-Inc/MalGrid)| +|2211.02718|[samo: speaker attractor multi-center one-class learning for voice anti-spoofing](https://arxiv.org/abs/2211.02718)|[samo](https://github.com/sivannavis/samo)| +|2211.02869|[deep learning for rapid landslide detection using synthetic aperture radar (sar) datacubes](https://arxiv.org/abs/2211.02869)|[landslide-sar-unet](https://github.com/iprapas/landslide-sar-unet)| +|2211.02922|[neural multi-event forecasting on spatio-temporal point processes using probabilistically enriched transformers](https://arxiv.org/abs/2211.02922)|[neural-spatio-temporal-probabilistic-transformers](https://github.com/negar-erfanian/neural-spatio-temporal-probabilistic-transformers)| +|2211.03171|[pan-tompkins++: a robust approach to detect r-peaks in ecg signals](https://arxiv.org/abs/2211.03171)|[Pan-Tompkins-Plus-Plus](https://github.com/Niaz-Imtiaz/Pan-Tompkins-Plus-Plus)| +|2211.03583|[pygsl: a graph structure learning toolkit](https://arxiv.org/abs/2211.03583)|[pygsl](https://github.com/maxwass/pygsl)| +|2211.02863|[inductive graph transformer for delivery time estimation](https://arxiv.org/abs/2211.02863)|[igt-wsdm23](https://github.com/enoche/igt-wsdm23)| ## 2022-11-07 -|paper|code| -|---|---| -|[graph neural networks for wireless communications: from theory to practice](https://arxiv.org/abs/2203.10800)|[gnn4com](https://github.com/yshenaw/gnn4com)| -|[rate-splitting for intelligent reflecting surface-aided multiuser vr streaming](https://arxiv.org/abs/2210.12191)|[Deep-GRAIL](https://github.com/ruihuang1967/Deep-GRAIL)| -|[multi-view multi-label fine-grained emotion decoding from human brain activity](https://arxiv.org/abs/2211.02629)|[ml-bvae](https://github.com/kaichengfu1997/ml-bvae)| -|[recursive estimation of user intent from noninvasive electroencephalography using discriminative models](https://arxiv.org/abs/2211.02630)|[bci-disc-models](https://github.com/nik-sm/bci-disc-models)| -|[a knowledge distillation framework for enhancing ear-eeg based sleep staging with scalp-eeg data](https://arxiv.org/abs/2211.02638)|[EarEEG_KnowledgeDistillation](https://github.com/Mithunjha/EarEEG_KnowledgeDistillation)| +|date|paper|code| +|---|---|---| +|2211.02629|[multi-view multi-label fine-grained emotion decoding from human brain activity](https://arxiv.org/abs/2211.02629)|[ml-bvae](https://github.com/kaichengfu1997/ml-bvae)| +|2211.02630|[recursive estimation of user intent from noninvasive electroencephalography using discriminative models](https://arxiv.org/abs/2211.02630)|[bci-disc-models](https://github.com/nik-sm/bci-disc-models)| +|2211.02638|[a knowledge distillation framework for enhancing ear-eeg based sleep staging with scalp-eeg data](https://arxiv.org/abs/2211.02638)|[EarEEG_KnowledgeDistillation](https://github.com/Mithunjha/EarEEG_KnowledgeDistillation)| ## 2022-11-04 -|paper|code| -|---|---| -|[an open platform for simulating the physical layer of 6g communication systems with multiple intelligent surfaces](https://arxiv.org/abs/2211.01659)|[6g-simulation-platform](https://github.com/alexpapad95/6g-simulation-platform)| -|[a space of goals: the cognitive geometry of informationally bounded agents](https://arxiv.org/abs/2111.03699)|[cognitive-geometry](https://gitlab.com/uh-adapsys/cognitive-geometry)| +|date|paper|code| +|---|---|---| +|2211.01659|[an open platform for simulating the physical layer of 6g communication systems with multiple intelligent surfaces](https://arxiv.org/abs/2211.01659)|[6g-simulation-platform](https://github.com/alexpapad95/6g-simulation-platform)| ## 2022-11-03 -|paper|code| -|---|---| -|[topology-aware graph neural networks for learning feasible and adaptive ac-opf solutions](https://arxiv.org/abs/2205.10129)|[GNN_OPF_electricity_market](https://github.com/ShaohuiLiu/GNN_OPF_electricity_market)| -|[parallel faceted imaging in radio interferometry via proximal splitting (faceted hypersara): ii. code and real data proof of concept](https://arxiv.org/abs/2209.07604)|[faceted-hypersara](https://github.com/basp-group/faceted-hypersara)| -|[a nonlinear sum of squares search for cazac sequences](https://arxiv.org/abs/2210.14827)|[ieee-sos-cazac](https://github.com/magsino-usna/ieee-sos-cazac)| -|[witt: a wireless image transmission transformer for semantic communications](https://arxiv.org/abs/2211.00937)|[witt](https://github.com/keyang8/witt)| +|date|paper|code| +|---|---|---| +|2211.00937|[witt: a wireless image transmission transformer for semantic communications](https://arxiv.org/abs/2211.00937)|[witt](https://github.com/keyang8/witt)| ## 2022-11-01 -|paper|code| -|---|---| -|[i13dr: a real-time demand response infrastructure for integrating renewable energy resources](https://arxiv.org/abs/2210.07789)|[demand-manager-app](https://github.com/i13DR/demand-manager-app)| -|[fast-convergent federated learning via cyclic aggregation](https://arxiv.org/abs/2210.16520)|[cyclicaggregation](https://github.com/yjlee22/cyclicaggregation)| -|[better lightweight network for free: codeword mimic learning for massive mimo csi feedback](https://arxiv.org/abs/2210.16544)|[codewordmimicfeedback](https://github.com/kylin9511/codewordmimicfeedback)| -|[space-time design for deep joint source channel coding of images over mimo channels](https://arxiv.org/abs/2210.16985)|[st_jscc](https://github.com/aprilbian/st_jscc)| -|[what has been enhanced in my knowledge-enhanced language model?](https://arxiv.org/abs/2202.00964)|[gcs_ki](https://github.com/yifan-h/gcs_ki)| -|[page: prototype-based model-level explanations for graph neural networks](https://arxiv.org/abs/2210.17159)|[page](https://github.com/jordan7186/page)| +|date|paper|code| +|---|---|---| diff --git a/archives/2022/12.md b/archives/2022/12.md index 39e8b654..b9105656 100644 --- a/archives/2022/12.md +++ b/archives/2022/12.md @@ -1,147 +1,108 @@ # December 2022 Archive ## 2022-12-29 -|paper|code| -|---|---| -|[clock and orientation-robust simultaneous radio localization and mapping at millimeter wave bands](https://arxiv.org/abs/2212.13477)|[castro-5g](https://github.com/gomezcuba/castro-5g)| -|[ecg-based electrolyte prediction: evaluating regression and probabilistic methods](https://arxiv.org/abs/2212.13890)|[ecg-electrolyte-regression](https://github.com/philippvb/ecg-electrolyte-regression)| -|[a low multiplicative complexity fast recursive dct-2 algorithm](https://arxiv.org/abs/1203.3442)|[Fast_recursive_DCT](https://github.com/Mak-Sim/Fast_recursive_DCT)| +|date|paper|code| +|---|---|---| +|2212.13477|[clock and orientation-robust simultaneous radio localization and mapping at millimeter wave bands](https://arxiv.org/abs/2212.13477)|[castro-5g](https://github.com/gomezcuba/castro-5g)| +|2212.13890|[ecg-based electrolyte prediction: evaluating regression and probabilistic methods](https://arxiv.org/abs/2212.13890)|[ecg-electrolyte-regression](https://github.com/philippvb/ecg-electrolyte-regression)| ## 2022-12-27 -|paper|code| -|---|---| -|[permutation matrix modulation](https://arxiv.org/abs/2112.13630)|[permutation-matrix-modulation](https://github.com/faddlis/permutation-matrix-modulation)| -|[recovery of missing sensor data by reconstructing time-varying graph signals](https://arxiv.org/abs/2203.00418)|[EUSIPCO_22_Sobolev](https://github.com/anindya2001/EUSIPCO_22_Sobolev)| -|[link-level simulator for 5g localization](https://arxiv.org/abs/2212.12998)|[5G_Positioning_Link_Level_Simulator%20v1.0.rar](https://github.com/Group85GP/Group85GP/blob/main/5G_Positioning_Link_Level_Simulator%20v1.0.rar)| -|[doubly transitive lines ii: almost simple symmetries](https://arxiv.org/abs/1905.06859)|[2-tran-II](https://github.com/jwiverson/2-tran-II)| +|date|paper|code| +|---|---|---| +|2212.12998|[link-level simulator for 5g localization](https://arxiv.org/abs/2212.12998)|[5G_Positioning_Link_Level_Simulator%20v1.0.rar](https://github.com/Group85GP/Group85GP/blob/main/5G_Positioning_Link_Level_Simulator%20v1.0.rar)| ## 2022-12-26 -|paper|code| -|---|---| -|[neonatal eeg graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy](https://arxiv.org/abs/2206.04420)|[downsample_open_eeg](https://github.com/otoolej/downsample_open_eeg)| -|[spectral subspace dictionary learning](https://arxiv.org/abs/2210.10855)|[spectral_dict_learn](https://github.com/sew347/spectral_dict_learn)| -|[deep unfolding-based weighted averaging for federated learning under heterogeneous environments](https://arxiv.org/abs/2212.12191)|[deepunfolding-based-fl](https://github.com/a-nakai-k/deepunfolding-based-fl)| +|date|paper|code| +|---|---|---| +|2212.12191|[deep unfolding-based weighted averaging for federated learning under heterogeneous environments](https://arxiv.org/abs/2212.12191)|[deepunfolding-based-fl](https://github.com/a-nakai-k/deepunfolding-based-fl)| ## 2022-12-23 -|paper|code| -|---|---| -|[electromagnetic based communication model for dynamic metasurface antennas](https://arxiv.org/abs/2212.11594)|[dma_model](https://github.com/robinjw/dma_model)| +|date|paper|code| +|---|---|---| +|2212.11594|[electromagnetic based communication model for dynamic metasurface antennas](https://arxiv.org/abs/2212.11594)|[dma_model](https://github.com/robinjw/dma_model)| ## 2022-12-22 -|paper|code| -|---|---| -|[rhombic grids reduce the number of voxels in fast pulse-echo ultrasound imaging](https://arxiv.org/abs/2210.04818)|[rhombic_grids](https://github.com/mschiffn/rhombic_grids)| -|[anticancer peptides classification using kernel sparse representation classifier](https://arxiv.org/abs/2212.10567)|[acp-kernel-src](https://github.com/ehtisham-fazal/acp-kernel-src)| -|[nestanets: stable, accurate and efficient neural networks for analysis-sparse inverse problems](https://arxiv.org/abs/2203.00804)|[as-nesta-net](https://github.com/mneyrane/as-nesta-net)| +|date|paper|code| +|---|---|---| +|2212.10567|[anticancer peptides classification using kernel sparse representation classifier](https://arxiv.org/abs/2212.10567)|[acp-kernel-src](https://github.com/ehtisham-fazal/acp-kernel-src)| ## 2022-12-21 -|paper|code| -|---|---| -|[beats: an open-source, high-precision, multi-channel eeg acquisition tool system](https://arxiv.org/abs/2203.02102)|[beats](https://github.com/buptanteeg/beats)| -|[joint network topology inference via a shared graphon model](https://arxiv.org/abs/2209.08223)|[jointinf_graphs_graphon](https://github.com/mn51/jointinf_graphs_graphon)| +|date|paper|code| +|---|---|---| ## 2022-12-20 -|paper|code| -|---|---| -|[enhancement of a state-of-the-art rl-based detection algorithm for massive mimo radars](https://arxiv.org/abs/2112.02628)|[improved_rl_algorithm_mmimo_radar](https://github.com/lisifra96/improved_rl_algorithm_mmimo_radar)| -|[openran gym: ai/ml development, data collection, and testing for o-ran on pawr platforms](https://arxiv.org/abs/2207.12362)|[colosseum-near-rt-ric](https://github.com/wineslab/colosseum-near-rt-ric)| -|[fast fullsubnet: accelerate full-band and sub-band fusion model for single-channel speech enhancement](https://arxiv.org/abs/2212.09019)|[FullSubNet](https://github.com/haoxiangsnr/FullSubNet)| +|date|paper|code| +|---|---|---| +|2212.09019|[fast fullsubnet: accelerate full-band and sub-band fusion model for single-channel speech enhancement](https://arxiv.org/abs/2212.09019)|[FullSubNet](https://github.com/haoxiangsnr/FullSubNet)| ## 2022-12-19 -|paper|code| -|---|---| -|[deep learning and its applications to wifi human sensing: a benchmark and a tutorial](https://arxiv.org/abs/2207.07859)|[wifi-csi-sensing-benchmark](https://github.com/chenxinyan-sg/wifi-csi-sensing-benchmark)| -|[simulating road spray effects in automotive lidar sensor models](https://arxiv.org/abs/2212.08558)|[reflection_based_lidar_object_model](https://github.com/openmsl/reflection_based_lidar_object_model)| +|date|paper|code| +|---|---|---| +|2212.08558|[simulating road spray effects in automotive lidar sensor models](https://arxiv.org/abs/2212.08558)|[reflection_based_lidar_object_model](https://github.com/openmsl/reflection_based_lidar_object_model)| ## 2022-12-16 -|paper|code| -|---|---| -|[a quaternion-valued variational autoencoder](https://arxiv.org/abs/2010.11647)|[QVAE](https://github.com/eleGAN23/QVAE)| -|[l3das21 challenge: machine learning for 3d audio signal processing](https://arxiv.org/abs/2104.05499)|[L3DAS21](https://github.com/l3das/L3DAS21)| -|[l3das22 challenge: learning 3d audio sources in a real office environment](https://arxiv.org/abs/2202.10372)|[l3das22](https://github.com/l3das/l3das22)| -|[state-augmented learnable algorithms for resource management in wireless networks](https://arxiv.org/abs/2207.02242)|[stateaugmented_rrm_gnn](https://github.com/navid-naderi/stateaugmented_rrm_gnn)| -|[duidd: deep-unfolded interleaved detection and decoding for mimo wireless systems](https://arxiv.org/abs/2212.07816)|[duidd](https://github.com/iip-group/duidd)| +|date|paper|code| +|---|---|---| +|2212.07816|[duidd: deep-unfolded interleaved detection and decoding for mimo wireless systems](https://arxiv.org/abs/2212.07816)|[duidd](https://github.com/iip-group/duidd)| ## 2022-12-15 -|paper|code| -|---|---| -|[do not sleep on traditional machine learning: simple and interpretable techniques are competitive to deep learning for sleep scoring](https://arxiv.org/abs/2207.07753)|[sleep-linear](https://github.com/predict-idlab/sleep-linear)| -|[self-supervised learning for anomalous channel detection in eeg graphs: application to seizure analysis](https://arxiv.org/abs/2208.07448)|[EEG-CGS](https://github.com/Armanfard-Lab/EEG-CGS)| -|[network coding: an optimization approach](https://arxiv.org/abs/2212.07230)|[network_codes](https://github.com/christopherhojny/network_codes)| +|date|paper|code| +|---|---|---| +|2212.07230|[network coding: an optimization approach](https://arxiv.org/abs/2212.07230)|[network_codes](https://github.com/christopherhojny/network_codes)| ## 2022-12-14 -|paper|code| -|---|---| -|[learning representations for new sound classes with continual self-supervised learning](https://arxiv.org/abs/2205.07390)|[cssl_sound](https://github.com/zhepeiw/cssl_sound)| -|[artificial intelligence enabled noma towards next generation multiple access](https://arxiv.org/abs/2206.04992)|[ai_noma](https://github.com/xiaoxiaxusummer/ai_noma)| +|date|paper|code| +|---|---|---| ## 2022-12-13 -|paper|code| -|---|---| -|[federated learning via plurality vote](https://arxiv.org/abs/2110.02998)|[fedvote](https://github.com/kai-yue/fedvote)| -|[deep, deep learning with bart](https://arxiv.org/abs/2202.14005)|[deep-deep-learning-with-bart](https://github.com/mrirecon/deep-deep-learning-with-bart)| -|[autofi: towards automatic wifi human sensing via geometric self-supervised learning](https://arxiv.org/abs/2205.01629)|[wifi-csi-sensing-benchmark](https://github.com/xyanchen/wifi-csi-sensing-benchmark)| -|[spectral efficiency analysis of uplink-downlink decoupled access in c-v2x networks](https://arxiv.org/abs/2212.02164)|[Spectral-Efficiency-Analysis-of-Uplink-Downlink-Decoupled-Access-in-C-V2X-Networks](https://github.com/shiwensuoluo/Spectral-Efficiency-Analysis-of-Uplink-Downlink-Decoupled-Access-in-C-V2X-Networks)| -|[max filtering with reflection groups](https://arxiv.org/abs/2212.05104)|[reflection-groups](https://github.com/daniel-packer/reflection-groups)| +|date|paper|code| +|---|---|---| +|2212.02164|[spectral efficiency analysis of uplink-downlink decoupled access in c-v2x networks](https://arxiv.org/abs/2212.02164)|[Spectral-Efficiency-Analysis-of-Uplink-Downlink-Decoupled-Access-in-C-V2X-Networks](https://github.com/shiwensuoluo/Spectral-Efficiency-Analysis-of-Uplink-Downlink-Decoupled-Access-in-C-V2X-Networks)| +|2212.05104|[max filtering with reflection groups](https://arxiv.org/abs/2212.05104)|[reflection-groups](https://github.com/daniel-packer/reflection-groups)| ## 2022-12-12 -|paper|code| -|---|---| -|[model-based and graph-based priors for group testing](https://arxiv.org/abs/2205.11838)|[priors_group_testing](https://github.com/ethangela/priors_group_testing)| -|[deep conv-attention model for diagnosing left bundle branch block from 12-lead electrocardiograms](https://arxiv.org/abs/2212.04936)|[dilated_conv_attention.ipynb](https://github.com/alrzsdgh/LBBB-deep-learning/blob/main/dilated_conv_attention.ipynb)| -|[symbol-level grand for high-order modulation over flat fading channels](https://arxiv.org/abs/2207.07748)|[sGRAND](https://github.com/IoannisChatzigeorgiou/sGRAND)| -|[a lego-brick approach to coding for network communication](https://arxiv.org/abs/2211.07208)|[lego-brick](https://github.com/nadimgh/lego-brick)| +|date|paper|code| +|---|---|---| +|2212.04936|[deep conv-attention model for diagnosing left bundle branch block from 12-lead electrocardiograms](https://arxiv.org/abs/2212.04936)|[dilated_conv_attention.ipynb](https://github.com/alrzsdgh/LBBB-deep-learning/blob/main/dilated_conv_attention.ipynb)| ## 2022-12-09 -|paper|code| -|---|---| -|[dynamic shimming in the cervical spinal cord for multi-echo gradient-echo imaging at 3 t](https://arxiv.org/abs/2107.10331)|[realtime-dynamic-shimming](https://github.com/neuropoly/realtime-dynamic-shimming)| -|[unrolled algorithms for group synchronization](https://arxiv.org/abs/2207.09418)|[unrolling_synchronization](https://github.com/noamjanco/unrolling_synchronization)| -|[greeneyes: an air quality evaluating model based on wavenet](https://arxiv.org/abs/2212.04175)|[AirEvaluation](https://github.com/AI-Huang/AirEvaluation)| -|[vicious classifiers: data reconstruction attack at inference time](https://arxiv.org/abs/2212.04223)|[vicious-classifiers](https://github.com/mmalekzadeh/vicious-classifiers)| +|date|paper|code| +|---|---|---| +|2212.04175|[greeneyes: an air quality evaluating model based on wavenet](https://arxiv.org/abs/2212.04175)|[AirEvaluation](https://github.com/AI-Huang/AirEvaluation)| +|2212.04223|[vicious classifiers: data reconstruction attack at inference time](https://arxiv.org/abs/2212.04223)|[vicious-classifiers](https://github.com/mmalekzadeh/vicious-classifiers)| ## 2022-12-08 -|paper|code| -|---|---| -|[unique sparse decomposition of low rank matrices](https://arxiv.org/abs/2106.07736)|[Unique_Fac_of_Low_Rank](https://github.com/Jindiande/Unique_Fac_of_Low_Rank)| -|[gridless 3d recovery of image sources from room impulse responses](https://arxiv.org/abs/2208.14017)|[acoustic-sfw](https://github.com/sprunckt/acoustic-sfw)| -|[enhancing low-density eeg-based brain-computer interfaces with similarity-keeping knowledge distillation](https://arxiv.org/abs/2212.03329)|[eeg-kd](https://github.com/cecnl/eeg-kd)| +|date|paper|code| +|---|---|---| +|2212.03329|[enhancing low-density eeg-based brain-computer interfaces with similarity-keeping knowledge distillation](https://arxiv.org/abs/2212.03329)|[eeg-kd](https://github.com/cecnl/eeg-kd)| ## 2022-12-07 -|paper|code| -|---|---| -|[direction of arrival estimation of sound sources using icosahedral cnns](https://arxiv.org/abs/2203.16940)|[icodoa](https://github.com/daviddiazguerra/icodoa)| -|[storseismic: a new paradigm in deep learning for seismic processing](https://arxiv.org/abs/2205.00222)|[storseismic](https://github.com/swag-kaust/storseismic)| +|date|paper|code| +|---|---|---| ## 2022-12-06 -|paper|code| -|---|---| -|[lggnet: learning from local-global-graph representations for brain-computer interface](https://arxiv.org/abs/2105.02786)|[LGG](https://github.com/yi-ding-cs/LGG)| -|[bayesian active meta-learning for few pilot demodulation and equalization](https://arxiv.org/abs/2108.00785)|[bayesian_active_meta_learning](https://github.com/kclip/bayesian_active_meta_learning)| -|[signal enhancement for two-dimensional cryo-em data processing](https://arxiv.org/abs/2212.01421)|[cryoemsignalenhancement](https://github.com/tamirbendory/cryoemsignalenhancement)| -|[joint graph learning from gaussian observations in the presence of hidden nodes](https://arxiv.org/abs/2212.01816)|[hidden_joint_gaussian_inf](https://github.com/reysam93/hidden_joint_gaussian_inf)| -|[spectral efficiency analysis of uplink-downlink decoupled access in c-v2x networks](https://arxiv.org/abs/2212.02164)|[Spectral-Efficiency-Analysis-of-Uplink-Downlink-Decoupled-Access-in-C-V2X-Networks](https://github.com/shiwensuoluo/Spectral-Efficiency-Analysis-of-Uplink-Downlink-Decoupled-Access-in-C-V2X-Networks)| -|[node-wise domain adaptation based on transferable attention for recognizing road rage via eeg](https://arxiv.org/abs/2212.02417)|[dataandcode](https://github.com/1cec0ffee/dataandcode)| -|[approximate message passing for multi-layer estimation in rotationally invariant models](https://arxiv.org/abs/2212.01572)|[ML-RI-GAMP](https://github.com/sparc-lab/ML-RI-GAMP)| +|date|paper|code| +|---|---|---| +|2212.01421|[signal enhancement for two-dimensional cryo-em data processing](https://arxiv.org/abs/2212.01421)|[cryoemsignalenhancement](https://github.com/tamirbendory/cryoemsignalenhancement)| +|2212.01816|[joint graph learning from gaussian observations in the presence of hidden nodes](https://arxiv.org/abs/2212.01816)|[hidden_joint_gaussian_inf](https://github.com/reysam93/hidden_joint_gaussian_inf)| +|2212.02164|[spectral efficiency analysis of uplink-downlink decoupled access in c-v2x networks](https://arxiv.org/abs/2212.02164)|[Spectral-Efficiency-Analysis-of-Uplink-Downlink-Decoupled-Access-in-C-V2X-Networks](https://github.com/shiwensuoluo/Spectral-Efficiency-Analysis-of-Uplink-Downlink-Decoupled-Access-in-C-V2X-Networks)| +|2212.02417|[node-wise domain adaptation based on transferable attention for recognizing road rage via eeg](https://arxiv.org/abs/2212.02417)|[dataandcode](https://github.com/1cec0ffee/dataandcode)| +|2212.01572|[approximate message passing for multi-layer estimation in rotationally invariant models](https://arxiv.org/abs/2212.01572)|[ML-RI-GAMP](https://github.com/sparc-lab/ML-RI-GAMP)| ## 2022-12-05 -|paper|code| -|---|---| -|[optimal discrete beamforming of reconfigurable intelligent surfaces](https://arxiv.org/abs/2211.04167)|[RIS_Optimization](https://github.com/RujingXiong/RIS_Optimization)| -|[a domain-knowledge-inspired music embedding space and a novel attention mechanism for symbolic music modeling](https://arxiv.org/abs/2212.00973)|[fundamentalmusicembedding](https://github.com/guozixunnicolas/fundamentalmusicembedding)| -|[fecam: frequency enhanced channel attention mechanism for time series forecasting](https://arxiv.org/abs/2212.01209)|[fecam](https://github.com/zero-coder/fecam)| -|[wigner distribution deconvolution adaptation for live ptychography reconstruction](https://arxiv.org/abs/2212.01309)|[livewdd](https://github.com/ptychography-4-0/livewdd)| +|date|paper|code| +|---|---|---| +|2212.00973|[a domain-knowledge-inspired music embedding space and a novel attention mechanism for symbolic music modeling](https://arxiv.org/abs/2212.00973)|[fundamentalmusicembedding](https://github.com/guozixunnicolas/fundamentalmusicembedding)| +|2212.01209|[fecam: frequency enhanced channel attention mechanism for time series forecasting](https://arxiv.org/abs/2212.01209)|[fecam](https://github.com/zero-coder/fecam)| +|2212.01309|[wigner distribution deconvolution adaptation for live ptychography reconstruction](https://arxiv.org/abs/2212.01309)|[livewdd](https://github.com/ptychography-4-0/livewdd)| ## 2022-12-02 -|paper|code| -|---|---| -|[fully on-board low-power localization with multizone time-of-flight sensors on nano-uavs](https://arxiv.org/abs/2212.00710)|[Matrix_ToF_Drones](https://github.com/ETH-PBL/Matrix_ToF_Drones)| -|[swl-adapt: an unsupervised domain adaptation model with sample weight learning for cross-user wearable human activity recognition](https://arxiv.org/abs/2212.00724)|[SWL-Adapt](https://github.com/Rxannro/SWL-Adapt)| +|date|paper|code| +|---|---|---| +|2212.00710|[fully on-board low-power localization with multizone time-of-flight sensors on nano-uavs](https://arxiv.org/abs/2212.00710)|[Matrix_ToF_Drones](https://github.com/ETH-PBL/Matrix_ToF_Drones)| +|2212.00724|[swl-adapt: an unsupervised domain adaptation model with sample weight learning for cross-user wearable human activity recognition](https://arxiv.org/abs/2212.00724)|[SWL-Adapt](https://github.com/Rxannro/SWL-Adapt)| ## 2022-12-01 -|paper|code| -|---|---| -|[openran gym: ai/ml development, data collection, and testing for o-ran on pawr platforms](https://arxiv.org/abs/2207.12362)|[colosseum-near-rt-ric](https://github.com/wineslab/colosseum-near-rt-ric)| -|[self-supervised learning for anomalous channel detection in eeg graphs: application to seizure analysis](https://arxiv.org/abs/2208.07448)|[EEG-CGS](https://github.com/Armanfard-Lab/EEG-CGS)| -|[robust and fast measure of information via low-rank representation](https://arxiv.org/abs/2211.16784)|[lrmi](https://github.com/gamepiaynmo/lrmi)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/01.md b/archives/2023/01.md index 28bba066..df118342 100644 --- a/archives/2023/01.md +++ b/archives/2023/01.md @@ -1,157 +1,114 @@ # January 2023 Archive ## 2023-01-31 -|paper|code| -|---|---| -|[chaos as an interpretable benchmark for forecasting and data-driven modelling](https://arxiv.org/abs/2110.05266)|[dysts](https://github.com/williamgilpin/dysts)| -|[beyond hawkes: neural multi-event forecasting on spatio-temporal point processes](https://arxiv.org/abs/2211.02922)|[neural-spatio-temporal-probabilistic-transformers](https://github.com/negar-erfanian/neural-spatio-temporal-probabilistic-transformers)| -|[versatile neural processes for learning implicit neural representations](https://arxiv.org/abs/2301.08883)|[versatile-np](https://github.com/zongyuguo/versatile-np)| -|[audioldm: text-to-audio generation with latent diffusion models](https://arxiv.org/abs/2301.12503)|[audioldm_eval](https://github.com/haoheliu/audioldm_eval)| -|[kernelized cumulants: beyond kernel mean embeddings](https://arxiv.org/abs/2301.12466)|[kernelized-cumulants](https://github.com/patricbonnier/kernelized-cumulants)| +|date|paper|code| +|---|---|---| +|2301.08883|[versatile neural processes for learning implicit neural representations](https://arxiv.org/abs/2301.08883)|[versatile-np](https://github.com/zongyuguo/versatile-np)| +|2301.12503|[audioldm: text-to-audio generation with latent diffusion models](https://arxiv.org/abs/2301.12503)|[audioldm_eval](https://github.com/haoheliu/audioldm_eval)| +|2301.12466|[kernelized cumulants: beyond kernel mean embeddings](https://arxiv.org/abs/2301.12466)|[kernelized-cumulants](https://github.com/patricbonnier/kernelized-cumulants)| ## 2023-01-30 -|paper|code| -|---|---| -|[digital twin-based multiple access optimization and monitoring via model-driven bayesian learning](https://arxiv.org/abs/2210.05582)|[bayesian-dt](https://github.com/kclip/bayesian-dt)| -|[smile: robust network localization via sparse and low-rank matrix decomposition](https://arxiv.org/abs/2301.11450)|[smile-network-localization](https://github.com/anrgusc/smile-network-localization)| +|date|paper|code| +|---|---|---| +|2301.11450|[smile: robust network localization via sparse and low-rank matrix decomposition](https://arxiv.org/abs/2301.11450)|[smile-network-localization](https://github.com/anrgusc/smile-network-localization)| ## 2023-01-27 -|paper|code| -|---|---| -|[flex-net: a graph neural network approach to resource management in flexible duplex networks](https://arxiv.org/abs/2301.11166)|[flex-net](https://github.com/tharaka-perera/flex-net)| +|date|paper|code| +|---|---|---| +|2301.11166|[flex-net: a graph neural network approach to resource management in flexible duplex networks](https://arxiv.org/abs/2301.11166)|[flex-net](https://github.com/tharaka-perera/flex-net)| ## 2023-01-26 -|paper|code| -|---|---| -|[an inertial block majorization minimization framework for nonsmooth nonconvex optimization](https://arxiv.org/abs/2010.12133)|[TITAN](https://github.com/nhatpd/TITAN)| -|[a framework of inertial alternating direction method of multipliers for non-convex non-smooth optimization](https://arxiv.org/abs/2102.05433)|[iADMM](https://github.com/nhatpd/iADMM)| -|[partial identifiability for nonnegative matrix factorization](https://arxiv.org/abs/2206.08022)|[nmf-partial-identifiability](https://gitlab.com/ngillis/nmf-partial-identifiability)| -|[high-throughput rate-flexible combinational decoders for multi-kernel polar codes](https://arxiv.org/abs/2301.10445)|[polar-compiler](https://github.com/hosseinrezaeii91/polar-compiler)| +|date|paper|code| +|---|---|---| +|2301.10445|[high-throughput rate-flexible combinational decoders for multi-kernel polar codes](https://arxiv.org/abs/2301.10445)|[polar-compiler](https://github.com/hosseinrezaeii91/polar-compiler)| ## 2023-01-25 -|paper|code| -|---|---| -|[deep task-based analog-to-digital conversion](https://arxiv.org/abs/2201.12634)|[adc-learning-hyperopt](https://github.com/arielamar123/adc-learning-hyperopt)| -|[autoencoder-based joint communication and sensing of multiple targets](https://arxiv.org/abs/2301.09439)|[JCAS_multitarg](https://github.com/frozenhairdryer/JCAS_multitarg)| -|[spectral cross-domain neural network with soft-adaptive threshold spectral enhancement](https://arxiv.org/abs/2301.10171)|[scdnn-ts](https://github.com/dl-wg/scdnn-ts)| -|[weighted sum-rate maximization with causal inference for latent interference estimation](https://arxiv.org/abs/2211.08327)|[research-weighted-sum-rate](https://github.com/youlei202/research-weighted-sum-rate)| +|date|paper|code| +|---|---|---| +|2301.09439|[autoencoder-based joint communication and sensing of multiple targets](https://arxiv.org/abs/2301.09439)|[JCAS_multitarg](https://github.com/frozenhairdryer/JCAS_multitarg)| +|2301.10171|[spectral cross-domain neural network with soft-adaptive threshold spectral enhancement](https://arxiv.org/abs/2301.10171)|[scdnn-ts](https://github.com/dl-wg/scdnn-ts)| ## 2023-01-24 -|paper|code| -|---|---| -|[propagation of linear uncertainties through multiline thru-reflect-line calibration](https://arxiv.org/abs/2301.09126)|[uncertainty-multiline-trl-calibration](https://github.com/ZiadHatab/uncertainty-multiline-trl-calibration)| -|[energy prediction using federated learning](https://arxiv.org/abs/2301.09165)|[energy_prediction](https://github.com/sanjana-sarda/energy_prediction)| +|date|paper|code| +|---|---|---| +|2301.09126|[propagation of linear uncertainties through multiline thru-reflect-line calibration](https://arxiv.org/abs/2301.09126)|[uncertainty-multiline-trl-calibration](https://github.com/ZiadHatab/uncertainty-multiline-trl-calibration)| +|2301.09165|[energy prediction using federated learning](https://arxiv.org/abs/2301.09165)|[energy_prediction](https://github.com/sanjana-sarda/energy_prediction)| ## 2023-01-23 -|paper|code| -|---|---| -|[source-free subject adaptation for eeg-based visual recognition](https://arxiv.org/abs/2301.08448)|[Deep-BCI](https://github.com/DeepBCI/Deep-BCI)| +|date|paper|code| +|---|---|---| +|2301.08448|[source-free subject adaptation for eeg-based visual recognition](https://arxiv.org/abs/2301.08448)|[Deep-BCI](https://github.com/DeepBCI/Deep-BCI)| ## 2023-01-20 -|paper|code| -|---|---| -|[emergence of the svd as an interpretable factorization in deep learning for inverse problems](https://arxiv.org/abs/2301.07820)|[descrambling-nn](https://github.com/shashanksule/descrambling-nn)| +|date|paper|code| +|---|---|---| +|2301.07820|[emergence of the svd as an interpretable factorization in deep learning for inverse problems](https://arxiv.org/abs/2301.07820)|[descrambling-nn](https://github.com/shashanksule/descrambling-nn)| ## 2023-01-19 -|paper|code| -|---|---| -|[learning task-oriented communication for edge inference: an information bottleneck approach](https://arxiv.org/abs/2102.04170)|[VL-VFE](https://github.com/shaojiawei07/VL-VFE)| -|[descod-ecg: deep score-based diffusion model for ecg baseline wander and noise removal](https://arxiv.org/abs/2208.00542)|[score-based-ecg-denoising](https://github.com/huayuliarizona/score-based-ecg-denoising)| -|[digital twin-based multiple access optimization and monitoring via model-driven bayesian learning](https://arxiv.org/abs/2210.05582)|[bayesian-dt](https://github.com/kclip/bayesian-dt)| -|[pendantss: penalized norm-ratios disentangling additive noise, trend and sparse spikes](https://arxiv.org/abs/2301.01514)|[pendantss](https://github.com/paulzhengfr/pendantss)| -|[sen2dwater: a novel multispectral and multitemporal dataset and deep learning benchmark for water resources analysis](https://arxiv.org/abs/2301.07452)|[impact-of-climate-change-on-water-resources](https://github.com/francescomauro1998/impact-of-climate-change-on-water-resources)| +|date|paper|code| +|---|---|---| +|2301.01514|[pendantss: penalized norm-ratios disentangling additive noise, trend and sparse spikes](https://arxiv.org/abs/2301.01514)|[pendantss](https://github.com/paulzhengfr/pendantss)| +|2301.07452|[sen2dwater: a novel multispectral and multitemporal dataset and deep learning benchmark for water resources analysis](https://arxiv.org/abs/2301.07452)|[impact-of-climate-change-on-water-resources](https://github.com/francescomauro1998/impact-of-climate-change-on-water-resources)| ## 2023-01-18 -|paper|code| -|---|---| -|[q-eegnet: an energy-efficient 8-bit quantized parallel eegnet implementation for edge motor-imagery brain--machine interfaces](https://arxiv.org/abs/2004.11690)|[q-eegnet](https://github.com/pulp-platform/q-eegnet)| -|[k-deep simplex: deep manifold learning via local dictionaries](https://arxiv.org/abs/2012.02134)|[manifold-learning-with-simplex-constraints](https://github.com/pbt17/manifold-learning-with-simplex-constraints)| -|[model-based and graph-based priors for group testing](https://arxiv.org/abs/2205.11838)|[priors_group_testing](https://github.com/ethangela/priors_group_testing)| -|[semi-blind source separation using convolutive transfer function for nonlinear acoustic echo cancellation](https://arxiv.org/abs/2207.01556)|[audio-samples2](https://github.com/chengguoliang0/audio-samples2)| -|[self-supervised learning for anomalous channel detection in eeg graphs: application to seizure analysis](https://arxiv.org/abs/2208.07448)|[EEG-CGS](https://github.com/Armanfard-Lab/EEG-CGS)| -|[stimulus-informed generalized canonical correlation analysis of stimulus-following brain responses](https://arxiv.org/abs/2210.13297)|[si-gcca](https://github.com/alexanderbertrandlab/si-gcca)| -|[stratified multivariate multiscale dispersion entropy for physiological signal analysis](https://arxiv.org/abs/2202.09298)|[smvmde](https://github.com/evangeloskafantaris/smvmde)| -|[crc-aided learned ensembles of belief-propagation polar decoders](https://arxiv.org/abs/2301.06060)|[polar-ensembles](https://github.com/tomerraviv95/polar-ensembles)| +|date|paper|code| +|---|---|---| +|2301.06060|[crc-aided learned ensembles of belief-propagation polar decoders](https://arxiv.org/abs/2301.06060)|[polar-ensembles](https://github.com/tomerraviv95/polar-ensembles)| ## 2023-01-17 -|paper|code| -|---|---| -|[mical: mutual information-based cnn-aided learned factor graphs for seizure detection from eeg signals](https://arxiv.org/abs/2206.02298)|[cnn-aided-factor-graphs-with-estimated-mutual-information-features-for-seizure-detection-mical](https://github.com/bsalafia/cnn-aided-factor-graphs-with-estimated-mutual-information-features-for-seizure-detection-mical)| +|date|paper|code| +|---|---|---| ## 2023-01-16 -|paper|code| -|---|---| -|[imitation learning-based implicit semantic-aware communication networks: multi-layer representation and collaborative reasoning](https://arxiv.org/abs/2210.16118)|[irml](https://github.com/zjs919/irml)| +|date|paper|code| +|---|---|---| ## 2023-01-13 -|paper|code| -|---|---| -|[automated sleep staging via parallel frequency-cut attention](https://arxiv.org/abs/2204.03173)|[transformer_sleep](https://github.com/zhengchen3/transformer_sleep)| -|[grant-free random access of iot devices in massive mimo with partial csi](https://arxiv.org/abs/2301.04861)|[grant-free-random-access-partial-csi](https://github.com/wavecore-research/grant-free-random-access-partial-csi)| -|[a stochastic optimization framework for fair risk minimization](https://arxiv.org/abs/2102.12586)|[FERMI](https://github.com/optimization-for-data-driven-science/FERMI)| +|date|paper|code| +|---|---|---| +|2301.04861|[grant-free random access of iot devices in massive mimo with partial csi](https://arxiv.org/abs/2301.04861)|[grant-free-random-access-partial-csi](https://github.com/wavecore-research/grant-free-random-access-partial-csi)| ## 2023-01-12 -|paper|code| -|---|---| -|[da-music: data-driven doa estimation via deep augmented music algorithm](https://arxiv.org/abs/2109.10581)|[tvt23](https://github.com/da-music/tvt23)| +|date|paper|code| +|---|---|---| ## 2023-01-11 -|paper|code| -|---|---| -|[bayesian active meta-learning for few pilot demodulation and equalization](https://arxiv.org/abs/2108.00785)|[bayesian_active_meta_learning](https://github.com/kclip/bayesian_active_meta_learning)| -|[mixcycle: unsupervised speech separation via cyclic mixture permutation invariant training](https://arxiv.org/abs/2202.03875)|[mixcycle](https://github.com/ertug/mixcycle)| -|[learning representations for new sound classes with continual self-supervised learning](https://arxiv.org/abs/2205.07390)|[cssl_sound](https://github.com/zhepeiw/cssl_sound)| -|[multiple-access channel coding with non-signaling correlations](https://arxiv.org/abs/2206.10968)|[mac_ns_lp](https://github.com/pferme/mac_ns_lp)| +|date|paper|code| +|---|---|---| ## 2023-01-10 -|paper|code| -|---|---| -|[physfad: physics-based end-to-end channel modeling of ris-parametrized environments with adjustable fading](https://arxiv.org/abs/2202.02673)|[physfad](https://github.com/philipp-delhougne/physfad)| -|[principal component analysis in space forms](https://arxiv.org/abs/2301.02750)|[HoroPCA](https://github.com/HazyResearch/HoroPCA)| -|[deep injective prior for inverse scattering](https://arxiv.org/abs/2301.03092)|[scattering_injective_prior](https://github.com/swing-research/scattering_injective_prior)| -|[unsupervised multivariate time-series transformers for seizure identification on eeg](https://arxiv.org/abs/2301.03470)|[eeg_mvts](https://github.com/ilkyyldz95/eeg_mvts)| -|[the entropy rate of linear additive markov processes](https://arxiv.org/abs/2211.05350)|[LAMPEntropyEstimates](https://github.com/bridget-smart/LAMPEntropyEstimates)| +|date|paper|code| +|---|---|---| +|2301.02750|[principal component analysis in space forms](https://arxiv.org/abs/2301.02750)|[HoroPCA](https://github.com/HazyResearch/HoroPCA)| +|2301.03092|[deep injective prior for inverse scattering](https://arxiv.org/abs/2301.03092)|[scattering_injective_prior](https://github.com/swing-research/scattering_injective_prior)| +|2301.03470|[unsupervised multivariate time-series transformers for seizure identification on eeg](https://arxiv.org/abs/2301.03470)|[eeg_mvts](https://github.com/ilkyyldz95/eeg_mvts)| ## 2023-01-09 -|paper|code| -|---|---| -|[expanding boundaries of gap safe screening](https://arxiv.org/abs/2102.10846)|[kl_screening](https://github.com/cassiofragadantas/kl_screening)| +|date|paper|code| +|---|---|---| ## 2023-01-06 -|paper|code| -|---|---| -|[frequency-dependent f-number increases the contrast and the spatial resolution in fast pulse-echo ultrasound imaging](https://arxiv.org/abs/2111.04593)|[f_number](https://github.com/mschiffn/f_number)| +|date|paper|code| +|---|---|---| ## 2023-01-05 -|paper|code| -|---|---| -|[pendantss: penalized norm-ratios disentangling additive noise, trend and sparse spikes](https://arxiv.org/abs/2301.01514)|[pendantss](https://github.com/paulzhengfr/pendantss)| +|date|paper|code| +|---|---|---| +|2301.01514|[pendantss: penalized norm-ratios disentangling additive noise, trend and sparse spikes](https://arxiv.org/abs/2301.01514)|[pendantss](https://github.com/paulzhengfr/pendantss)| ## 2023-01-04 -|paper|code| -|---|---| -|[multiscale adaptive scheduling and path-planning for power-constrained uav-relays via smdps](https://arxiv.org/abs/2209.07655)|[MAESTRO-X](https://github.com/bharathkeshavamurthy/MAESTRO-X)| -|[anxolotl, an anxiety companion app -- stress detection](https://arxiv.org/abs/2212.14006)|[cfp-workshop-and-challenge-wellbeing](https://github.com/matpato/cfp-workshop-and-challenge-wellbeing)| -|[moreau-yosida $f$-divergences](https://arxiv.org/abs/2102.13416)|[moreau-yosida-f-divergences](https://github.com/renyi-ai/moreau-yosida-f-divergences)| +|date|paper|code| +|---|---|---| ## 2023-01-03 -|paper|code| -|---|---| -|[bayesian active meta-learning for few pilot demodulation and equalization](https://arxiv.org/abs/2108.00785)|[bayesian_active_meta_learning](https://github.com/kclip/bayesian_active_meta_learning)| -|[rtsnet: learning to smooth in partially known state-space models](https://arxiv.org/abs/2110.04717)|[rtsnet_tsp](https://github.com/kalmannet/rtsnet_tsp)| -|[deep learning of near field beam focusing in terahertz wideband massive mimo systems](https://arxiv.org/abs/2210.02980)|[nfwb_bf](https://github.com/yuzhang-github/nfwb_bf)| -|[learn to rapidly and robustly optimize hybrid precoding](https://arxiv.org/abs/2301.00369)|[learn-to-rapidly-optimize-hybrid-precoding](https://github.com/ortalagiv/learn-to-rapidly-optimize-hybrid-precoding)| -|[fusing models for prognostics and health management of lithium-ion batteries based on physics-informed neural networks](https://arxiv.org/abs/2301.00776)|[PINN-Battery-Prognostics](https://github.com/WenPengfei0823/PINN-Battery-Prognostics)| -|[learning to maximize mutual information for dynamic feature selection](https://arxiv.org/abs/2301.00557)|[dynamic-selection](https://github.com/iancovert/dynamic-selection)| -|[data-driven optimization of directed information over discrete alphabets](https://arxiv.org/abs/2301.00621)|[discrete_di_optimization](https://github.com/dortsur/discrete_di_optimization)| +|date|paper|code| +|---|---|---| +|2301.00369|[learn to rapidly and robustly optimize hybrid precoding](https://arxiv.org/abs/2301.00369)|[learn-to-rapidly-optimize-hybrid-precoding](https://github.com/ortalagiv/learn-to-rapidly-optimize-hybrid-precoding)| +|2301.00776|[fusing models for prognostics and health management of lithium-ion batteries based on physics-informed neural networks](https://arxiv.org/abs/2301.00776)|[PINN-Battery-Prognostics](https://github.com/WenPengfei0823/PINN-Battery-Prognostics)| +|2301.00557|[learning to maximize mutual information for dynamic feature selection](https://arxiv.org/abs/2301.00557)|[dynamic-selection](https://github.com/iancovert/dynamic-selection)| +|2301.00621|[data-driven optimization of directed information over discrete alphabets](https://arxiv.org/abs/2301.00621)|[discrete_di_optimization](https://github.com/dortsur/discrete_di_optimization)| ## 2023-01-02 -|paper|code| -|---|---| -|[efficient approximation of jacobian matrices involving a non-uniform fast fourier transform (nufft)](https://arxiv.org/abs/2111.02912)|[Bjork](https://github.com/guanhuaw/Bjork)| -|[semantic communications with discrete-time analog transmission: a papr perspective](https://arxiv.org/abs/2208.08342)|[semanticpapr](https://github.com/lynshao/semanticpapr)| -|[power control for 6g industrial wireless subnetworks: a graph neural network approach](https://arxiv.org/abs/2212.14051)|[Power_Control_GNN](https://github.com/danieloaAAU/Power_Control_GNN)| -|[sheaf-theoretic self-filtering network of low-cost sensors for local air quality monitoring: a causal approach](https://arxiv.org/abs/2212.14353)|[AirSheaf](https://github.com/a11to1n3/AirSheaf)| -|[similarity-based predictive maintenance framework for rotating machinery](https://arxiv.org/abs/2212.14550)|[similarity-based-predictive-maintenance-framework-for-rotating-machinery](https://github.com/western-oc2-lab/similarity-based-predictive-maintenance-framework-for-rotating-machinery)| -|[lab-scale vibration analysis dataset and baseline methods for machinery fault diagnosis with machine learning](https://arxiv.org/abs/2212.14732)|[vbl-va001](https://github.com/bagustris/vbl-va001)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/02.md b/archives/2023/02.md index c608f68a..b7c6cf2b 100644 --- a/archives/2023/02.md +++ b/archives/2023/02.md @@ -1,174 +1,120 @@ # February 2023 Archive ## 2023-02-28 -|paper|code| -|---|---| -|[compressing multisets with large alphabets using bits-back coding](https://arxiv.org/abs/2107.09202)|[multiset-compression](https://github.com/facebookresearch/multiset-compression)| -|[hybrid far- and near-field channel estimation for thz ultra-massive mimo via fixed point networks](https://arxiv.org/abs/2205.04944)|[FPN-OAMP-THz-Channel-Estimation](https://github.com/wyuaq/FPN-OAMP-THz-Channel-Estimation)| -|[learned robust pca: a scalable deep unfolding approach for high-dimensional outlier detection](https://arxiv.org/abs/2110.05649)|[lrpca](https://github.com/caesarcai/lrpca)| +|date|paper|code| +|---|---|---| ## 2023-02-27 -|paper|code| -|---|---| -|[evaluation of interpretability for deep learning algorithms in eeg emotion recognition: a case study in autism](https://arxiv.org/abs/2111.13208)|[deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals](https://github.com/meiyor/deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals)| -|[a ris-based vehicle doa estimation method with integrated sensing and communication system](https://arxiv.org/abs/2204.11626)|[passivedoa-isac-ris](https://github.com/chenpengseu/passivedoa-isac-ris)| +|date|paper|code| +|---|---|---| ## 2023-02-24 -|paper|code| -|---|---| -|[information fragmentation, encryption and information flow in complex biological networks](https://arxiv.org/abs/2105.13585)|[fragmentation_replication_instructions](https://github.com/cliff-bohm/fragmentation_replication_instructions)| -|[nonparametric two-sample testing by betting](https://arxiv.org/abs/2112.09162)|[nonparametric-testing-by-betting](https://github.com/sshekhar17/nonparametric-testing-by-betting)| -|[bayesian estimation of information-theoretic metrics for sparsely sampled distributions](https://arxiv.org/abs/2301.13647)|[info-metric-estimation](https://github.com/angelopiga/info-metric-estimation)| -|[information theory inspired pattern analysis for time-series data](https://arxiv.org/abs/2302.11654)|[entropypipeline](https://github.com/yushan-huang/entropypipeline)| -|[rna secondary structures: from ab initio prediction to better compression, and back](https://arxiv.org/abs/2302.11669)|[joint-rna-compression](https://github.com/evita35/joint-rna-compression)| -|[quantifying & modeling feature interactions: an information decomposition framework](https://arxiv.org/abs/2302.12247)|[pid](https://github.com/pliang279/pid)| +|date|paper|code| +|---|---|---| +|2302.11654|[information theory inspired pattern analysis for time-series data](https://arxiv.org/abs/2302.11654)|[entropypipeline](https://github.com/yushan-huang/entropypipeline)| +|2302.11669|[rna secondary structures: from ab initio prediction to better compression, and back](https://arxiv.org/abs/2302.11669)|[joint-rna-compression](https://github.com/evita35/joint-rna-compression)| +|2302.12247|[quantifying & modeling feature interactions: an information decomposition framework](https://arxiv.org/abs/2302.12247)|[pid](https://github.com/pliang279/pid)| ## 2023-02-23 -|paper|code| -|---|---| -|[estimating total correlation with mutual information estimators](https://arxiv.org/abs/2011.04794)|[tc-estimation](https://github.com/linear95/tc-estimation)| -|[unsourced multiple access with random user activity](https://arxiv.org/abs/2202.06365)|[uma_random_user_activity](https://github.com/khachoang1412/uma_random_user_activity)| +|date|paper|code| +|---|---|---| ## 2023-02-22 -|paper|code| -|---|---| -|[power scaling laws and near-field behaviors of massive mimo and intelligent reflecting surfaces](https://arxiv.org/abs/2002.04960)|[near-field-behavior](https://github.com/emilbjornson/near-field-behavior)| -|[lightweight and high-fidelity end-to-end text-to-speech with multi-band generation and inverse short-time fourier transform](https://arxiv.org/abs/2210.15975)|[mb-istft-vits](https://github.com/masayakawamura/mb-istft-vits)| -|[versatile neural processes for learning implicit neural representations](https://arxiv.org/abs/2301.08883)|[versatile-np](https://github.com/zongyuguo/versatile-np)| -|[energy-efficient blockchain-enabled user-centric mobile edge computing](https://arxiv.org/abs/2302.10515)|[blockchain-enabled-ucmec](https://github.com/qlt315/blockchain-enabled-ucmec)| -|[joint optimization of base station clustering and service caching in user-centric mec](https://arxiv.org/abs/2302.10558)|[jo-cdsd](https://github.com/qlt315/jo-cdsd)| -|[a local machine learning approach for fingerprint-based indoor localization](https://arxiv.org/abs/2302.10810)|[-a-local-machine-learning-approach-for-fingerprint-based-indoor-localization](https://github.com/noraagah/-a-local-machine-learning-approach-for-fingerprint-based-indoor-localization)| -|[scalable infomin learning](https://arxiv.org/abs/2302.10701)|[infomin](https://github.com/cyz-ai/infomin)| +|date|paper|code| +|---|---|---| +|2302.10515|[energy-efficient blockchain-enabled user-centric mobile edge computing](https://arxiv.org/abs/2302.10515)|[blockchain-enabled-ucmec](https://github.com/qlt315/blockchain-enabled-ucmec)| +|2302.10558|[joint optimization of base station clustering and service caching in user-centric mec](https://arxiv.org/abs/2302.10558)|[jo-cdsd](https://github.com/qlt315/jo-cdsd)| +|2302.10810|[a local machine learning approach for fingerprint-based indoor localization](https://arxiv.org/abs/2302.10810)|[-a-local-machine-learning-approach-for-fingerprint-based-indoor-localization](https://github.com/noraagah/-a-local-machine-learning-approach-for-fingerprint-based-indoor-localization)| +|2302.10701|[scalable infomin learning](https://arxiv.org/abs/2302.10701)|[infomin](https://github.com/cyz-ai/infomin)| ## 2023-02-21 -|paper|code| -|---|---| -|[bolt: fused window transformers for fmri time series analysis](https://arxiv.org/abs/2205.11578)|[bolt](https://github.com/icon-lab/bolt)| -|[towards unsupervised assessment with open-source data of the accuracy of deep learning-based distributed pv mapping](https://arxiv.org/abs/2207.07466)|[deeppvmapper](https://github.com/gabrielkasmi/deeppvmapper)| -|[quantized compressed sensing with score-based generative models](https://arxiv.org/abs/2211.13006)|[qcs-sgm](https://github.com/mengxiangming/qcs-sgm)| -|[incipient fault detection in power distribution system: a time-frequency embedded deep learning based approach](https://arxiv.org/abs/2302.09332)|[AD-TFM-AT-Model](https://github.com/smartlab-hfut/AD-TFM-AT-Model)| -|[implementation of dnn based data detector for qpsk systems](https://arxiv.org/abs/2302.10073)|[qpsk_sdr_dnn_detector](https://github.com/abadi13/qpsk_sdr_dnn_detector)| -|[a dnn based normalized time-frequency weighted criterion for robust wideband doa estimation](https://arxiv.org/abs/2302.10147)|[dnnnormtimefreq4doa](https://github.com/kjason/dnnnormtimefreq4doa)| -|[overparameterized relu neural networks learn the simplest models: neural isometry and exact recovery](https://arxiv.org/abs/2209.15265)|[neural-recovery](https://github.com/pilancilab/neural-recovery)| -|[synchronizing many filesystems in near linear time](https://arxiv.org/abs/2302.09666)|[algebraic-reconciler](https://github.com/csirmaz/algebraic-reconciler)| -|[nystr\"om $m$-hilbert-schmidt independence criterion](https://arxiv.org/abs/2302.09930)|[nystroem-mhsic](https://github.com/flopska/nystroem-mhsic)| +|date|paper|code| +|---|---|---| +|2302.09332|[incipient fault detection in power distribution system: a time-frequency embedded deep learning based approach](https://arxiv.org/abs/2302.09332)|[AD-TFM-AT-Model](https://github.com/smartlab-hfut/AD-TFM-AT-Model)| +|2302.10073|[implementation of dnn based data detector for qpsk systems](https://arxiv.org/abs/2302.10073)|[qpsk_sdr_dnn_detector](https://github.com/abadi13/qpsk_sdr_dnn_detector)| +|2302.10147|[a dnn based normalized time-frequency weighted criterion for robust wideband doa estimation](https://arxiv.org/abs/2302.10147)|[dnnnormtimefreq4doa](https://github.com/kjason/dnnnormtimefreq4doa)| +|2302.09666|[synchronizing many filesystems in near linear time](https://arxiv.org/abs/2302.09666)|[algebraic-reconciler](https://github.com/csirmaz/algebraic-reconciler)| +|2302.09930|[nystr\"om $m$-hilbert-schmidt independence criterion](https://arxiv.org/abs/2302.09930)|[nystroem-mhsic](https://github.com/flopska/nystroem-mhsic)| ## 2023-02-20 -|paper|code| -|---|---| -|[mm-alt: a multimodal automatic lyric transcription system](https://arxiv.org/abs/2207.06127)|[MM_ALT](https://github.com/guxm2021/MM_ALT)| -|[sensefi: a library and benchmark on deep-learning-empowered wifi human sensing](https://arxiv.org/abs/2207.07859)|[wifi-csi-sensing-benchmark](https://github.com/chenxinyan-sg/wifi-csi-sensing-benchmark)| -|[detecting non-overlapping signals with dynamic programming](https://arxiv.org/abs/2208.07830)|[Signal-detection-with-dynamic-programming](https://github.com/MordechaiRoth1/Signal-detection-with-dynamic-programming)| -|[calibration and uncertainty characterization for ultra-wideband two-way-ranging measurements](https://arxiv.org/abs/2210.05888)|[uwb_calibration](https://github.com/decargroup/uwb_calibration)| -|[real-time wireless ecg-derived respiration rate estimation using an autoencoder with a dct layer](https://arxiv.org/abs/2211.08491)|[icassp2023-ae-dct](https://github.com/phy710/icassp2023-ae-dct)| -|[cell-free isac mimo systems: joint sensing and communication beamforming](https://arxiv.org/abs/2301.11328)|[Cell-free-ISAC-beamforming](https://github.com/umut-demirhan/Cell-free-ISAC-beamforming)| -|[audioldm: text-to-audio generation with latent diffusion models](https://arxiv.org/abs/2301.12503)|[audioldm_eval](https://github.com/haoheliu/audioldm_eval)| -|[propagation measurements and analyses at 28 ghz via an autonomous beam-steering platform](https://arxiv.org/abs/2302.08584)|[SPAVE-28G](https://github.com/bharathkeshavamurthy/SPAVE-28G)| -|[deep comparisons of neural networks from the eegnet family](https://arxiv.org/abs/2302.08797)|[bionic_apps](https://github.com/kolcs/bionic_apps)| -|[smart 6g sky for green mobile iot networks](https://arxiv.org/abs/2302.09022)|[smart-6g-sky-for-green-mobile-iot-networks](https://github.com/qusaibshiwa/smart-6g-sky-for-green-mobile-iot-networks)| -|[ultra-marginal feature importance: learning from data with causal guarantees](https://arxiv.org/abs/2204.09938)|[umfi](https://github.com/hydroml/umfi)| -|[raw radar data based object detection and heading estimation using cross attention](https://arxiv.org/abs/2205.08406)|[crossattention_radar_detector](https://github.com/ravikothari510/crossattention_radar_detector)| -|[consistent diffusion models: mitigating sampling drift by learning to be consistent](https://arxiv.org/abs/2302.09057)|[cdm](https://github.com/giannisdaras/cdm)| +|date|paper|code| +|---|---|---| +|2302.08584|[propagation measurements and analyses at 28 ghz via an autonomous beam-steering platform](https://arxiv.org/abs/2302.08584)|[SPAVE-28G](https://github.com/bharathkeshavamurthy/SPAVE-28G)| +|2302.08797|[deep comparisons of neural networks from the eegnet family](https://arxiv.org/abs/2302.08797)|[bionic_apps](https://github.com/kolcs/bionic_apps)| +|2302.09022|[smart 6g sky for green mobile iot networks](https://arxiv.org/abs/2302.09022)|[smart-6g-sky-for-green-mobile-iot-networks](https://github.com/qusaibshiwa/smart-6g-sky-for-green-mobile-iot-networks)| +|2302.09057|[consistent diffusion models: mitigating sampling drift by learning to be consistent](https://arxiv.org/abs/2302.09057)|[cdm](https://github.com/giannisdaras/cdm)| ## 2023-02-17 -|paper|code| -|---|---| -|[a ris-based vehicle doa estimation method with integrated sensing and communication system](https://arxiv.org/abs/2204.11626)|[passivedoa-isac-ris](https://github.com/chenpengseu/passivedoa-isac-ris)| -|[stimulus-informed generalized canonical correlation analysis of stimulus-following brain responses](https://arxiv.org/abs/2210.13297)|[si-gcca](https://github.com/alexanderbertrandlab/si-gcca)| -|[pendantss: penalized norm-ratios disentangling additive noise, trend and sparse spikes](https://arxiv.org/abs/2301.01514)|[pendantss](https://github.com/paulzhengfr/pendantss)| -|[selective noise suppression in random svpwm to shape the voltage and current spectrum](https://arxiv.org/abs/2302.08053)|[SNS-in-random-SVPWM](https://github.com/IoaJianWen/SNS-in-random-SVPWM)| -|[a millimeter-wave software-defined radio for wireless experimentation](https://arxiv.org/abs/2302.08444)|[mmwavesdr](https://github.com/alphansahin/mmwavesdr)| +|date|paper|code| +|---|---|---| +|2302.08053|[selective noise suppression in random svpwm to shape the voltage and current spectrum](https://arxiv.org/abs/2302.08053)|[SNS-in-random-SVPWM](https://github.com/IoaJianWen/SNS-in-random-SVPWM)| +|2302.08444|[a millimeter-wave software-defined radio for wireless experimentation](https://arxiv.org/abs/2302.08444)|[mmwavesdr](https://github.com/alphansahin/mmwavesdr)| ## 2023-02-16 -|paper|code| -|---|---| -|[deep learning for hybrid beamforming with finite feedback in gsm aided mmwave mimo systems](https://arxiv.org/abs/2302.07601)|[gsmefbnet](https://github.com/kylin9511/gsmefbnet)| -|[guaranteed dynamic scheduling of ultra-reliable low-latency traffic via conformal prediction](https://arxiv.org/abs/2302.07675)|[online_cp_urllc](https://github.com/kclip/online_cp_urllc)| +|date|paper|code| +|---|---|---| +|2302.07601|[deep learning for hybrid beamforming with finite feedback in gsm aided mmwave mimo systems](https://arxiv.org/abs/2302.07601)|[gsmefbnet](https://github.com/kylin9511/gsmefbnet)| +|2302.07675|[guaranteed dynamic scheduling of ultra-reliable low-latency traffic via conformal prediction](https://arxiv.org/abs/2302.07675)|[online_cp_urllc](https://github.com/kclip/online_cp_urllc)| ## 2023-02-15 -|paper|code| -|---|---| -|[towards interpretable sleep stage classification using cross-modal transformers](https://arxiv.org/abs/2208.06991)|[cross-modal-transformer](https://github.com/jathurshan0330/cross-modal-transformer)| -|[enhancing multivariate time series classifiers through self-attention and relative positioning infusion](https://arxiv.org/abs/2302.06683)|[timeseriesclassification-tps](https://github.com/mehryar72/timeseriesclassification-tps)| -|[a novel poisoned water detection method using smartphone embedded wi-fi technology and machine learning algorithms](https://arxiv.org/abs/2302.07153)|[poisoned_water_detection](https://github.com/halgurd18/poisoned_water_detection)| -|[context query simulation for smart carparking scenarios in the melbourne cdb](https://arxiv.org/abs/2302.07190)|[context-query-simulator](https://github.com/shakthiyasas/context-query-simulator)| +|date|paper|code| +|---|---|---| +|2302.06683|[enhancing multivariate time series classifiers through self-attention and relative positioning infusion](https://arxiv.org/abs/2302.06683)|[timeseriesclassification-tps](https://github.com/mehryar72/timeseriesclassification-tps)| +|2302.07153|[a novel poisoned water detection method using smartphone embedded wi-fi technology and machine learning algorithms](https://arxiv.org/abs/2302.07153)|[poisoned_water_detection](https://github.com/halgurd18/poisoned_water_detection)| +|2302.07190|[context query simulation for smart carparking scenarios in the melbourne cdb](https://arxiv.org/abs/2302.07190)|[context-query-simulator](https://github.com/shakthiyasas/context-query-simulator)| ## 2023-02-14 -|paper|code| -|---|---| -|[self-supervised eeg representation learning for automatic sleep staging](https://arxiv.org/abs/2110.15278)|[contrawr](https://github.com/ycq091044/contrawr)| -|[transformers in time series: a survey](https://arxiv.org/abs/2202.07125)|[time-series-transformers-review](https://github.com/qingsongedu/time-series-transformers-review)| -|[online meta-learning for hybrid model-based deep receivers](https://arxiv.org/abs/2203.14359)|[metadeepsic](https://github.com/tomerraviv95/metadeepsic)| -|[probabilistic estimation of instantaneous frequencies of chirp signals](https://arxiv.org/abs/2205.06306)|[chirpgp](https://github.com/spdes/chirpgp)| -|[software-defined mimo ofdm joint radar-communication platform with fully digital mmwave architecture](https://arxiv.org/abs/2302.05812)|[gr-mimo-ofdm-jrc](https://github.com/ceyhunozkaptan/gr-mimo-ofdm-jrc)| -|[fundamental limits for sensor-based robot control](https://arxiv.org/abs/2202.00129)|[performance-limits](https://github.com/irom-lab/performance-limits)| -|[crc-aided learned ensembles of belief-propagation polar decoders](https://arxiv.org/abs/2301.06060)|[polar-ensembles](https://github.com/tomerraviv95/polar-ensembles)| -|[efficient integer retrieving from unordered compressed sequences](https://arxiv.org/abs/2302.05869)|[directaccess](https://github.com/zavadsky/directaccess)| +|date|paper|code| +|---|---|---| +|2302.05812|[software-defined mimo ofdm joint radar-communication platform with fully digital mmwave architecture](https://arxiv.org/abs/2302.05812)|[gr-mimo-ofdm-jrc](https://github.com/ceyhunozkaptan/gr-mimo-ofdm-jrc)| +|2302.05869|[efficient integer retrieving from unordered compressed sequences](https://arxiv.org/abs/2302.05869)|[directaccess](https://github.com/zavadsky/directaccess)| ## 2023-02-13 -|paper|code| -|---|---| -|[coordinated sum-rate maximization in multicell mu-mimo with deep unrolling](https://arxiv.org/abs/2202.10371)|[gcnwmmse](https://github.com/lsky96/gcnwmmse)| -|[binomial line cox processes: statistical characterization and applications in wireless network analysis](https://arxiv.org/abs/2302.05151)|[blcp](https://github.com/mt19146/blcp)| +|date|paper|code| +|---|---|---| +|2302.05151|[binomial line cox processes: statistical characterization and applications in wireless network analysis](https://arxiv.org/abs/2302.05151)|[blcp](https://github.com/mt19146/blcp)| ## 2023-02-10 -|paper|code| -|---|---| -|[offline learning of closed-loop deep brain stimulation controllers for parkinson disease treatment](https://arxiv.org/abs/2302.02477)|[vlbm](https://github.com/gaoqitong/vlbm)| -|[channelformer: attention based neural solution for wireless channel estimation and effective online training](https://arxiv.org/abs/2302.04368)|[Channelformer](https://github.com/dianixn/Channelformer)| -|[software tools for decoding quantum low-density parity check codes](https://arxiv.org/abs/2209.01180)|[qecc](https://github.com/lucasberent/qecc)| -|[trading information between latents in hierarchical variational autoencoders](https://arxiv.org/abs/2302.04855)|[hit](https://github.com/timxzz/hit)| +|date|paper|code| +|---|---|---| +|2302.02477|[offline learning of closed-loop deep brain stimulation controllers for parkinson disease treatment](https://arxiv.org/abs/2302.02477)|[vlbm](https://github.com/gaoqitong/vlbm)| +|2302.04368|[channelformer: attention based neural solution for wireless channel estimation and effective online training](https://arxiv.org/abs/2302.04368)|[Channelformer](https://github.com/dianixn/Channelformer)| +|2302.04855|[trading information between latents in hierarchical variational autoencoders](https://arxiv.org/abs/2302.04855)|[hit](https://github.com/timxzz/hit)| ## 2023-02-09 -|paper|code| -|---|---| -|[multimodal representation learning using deep multiset canonical correlation](https://arxiv.org/abs/1904.01775)|[mica-deep-mcca](https://github.com/usc-sail/mica-deep-mcca)| -|[evaluation of interpretability for deep learning algorithms in eeg emotion recognition: a case study in autism](https://arxiv.org/abs/2111.13208)|[deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals](https://github.com/meiyor/deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals)| -|[astride: adaptive symbolization for time series databases](https://arxiv.org/abs/2302.04097)|[astride](https://github.com/sylvaincom/astride)| -|[policy evaluation in decentralized pomdps with belief sharing](https://arxiv.org/abs/2302.04151)|[decpomdp_policy_evaluation_w-belief_sharing](https://github.com/asl-epfl/decpomdp_policy_evaluation_w-belief_sharing)| -|[a vector quantized approach for text to speech synthesis on real-world spontaneous speech](https://arxiv.org/abs/2302.04215)|[mqtts](https://github.com/b04901014/mqtts)| +|date|paper|code| +|---|---|---| +|2302.04097|[astride: adaptive symbolization for time series databases](https://arxiv.org/abs/2302.04097)|[astride](https://github.com/sylvaincom/astride)| +|2302.04151|[policy evaluation in decentralized pomdps with belief sharing](https://arxiv.org/abs/2302.04151)|[decpomdp_policy_evaluation_w-belief_sharing](https://github.com/asl-epfl/decpomdp_policy_evaluation_w-belief_sharing)| +|2302.04215|[a vector quantized approach for text to speech synthesis on real-world spontaneous speech](https://arxiv.org/abs/2302.04215)|[mqtts](https://github.com/b04901014/mqtts)| ## 2023-02-08 -|paper|code| -|---|---| -|[dct-former: efficient self-attention with discrete cosine transform](https://arxiv.org/abs/2203.01178)|[dct-former-public](https://github.com/cscribano/dct-former-public)| -|[unsupervised multimodal change detection based on structural relationship graph representation learning](https://arxiv.org/abs/2210.00941)|[srgcae](https://github.com/chenhongruixuan/srgcae)| -|[identification of power system oscillation modes using blind source separation based on copula statistic](https://arxiv.org/abs/2302.03633)|[hobmi](https://github.com/apooja1/hobmi)| +|date|paper|code| +|---|---|---| +|2302.03633|[identification of power system oscillation modes using blind source separation based on copula statistic](https://arxiv.org/abs/2302.03633)|[hobmi](https://github.com/apooja1/hobmi)| ## 2023-02-07 -|paper|code| -|---|---| -|[maestro-x: distributed orchestration of rotary-wing uav-relay swarms](https://arxiv.org/abs/2007.01228)|[MAESTRO-X](https://github.com/bharathkeshavamurthy/MAESTRO-X)| -|[efficient approximation of jacobian matrices involving a non-uniform fast fourier transform (nufft)](https://arxiv.org/abs/2111.02912)|[Bjork](https://github.com/guanhuaw/Bjork)| -|[a covariant, discrete time-frequency representation tailored for zero-based signal detection](https://arxiv.org/abs/2202.03835)|[kravchuk-transform-and-its-zeros](https://github.com/bpascal-fr/kravchuk-transform-and-its-zeros)| -|[graph-based sequential beamforming](https://arxiv.org/abs/2208.12472)|[sequentialvariationalbayesdoa](https://github.com/noiselabucsd/sequentialvariationalbayesdoa)| -|[achieving robust generalization for wireless channel estimation neural networks by designed training data](https://arxiv.org/abs/2302.02302)|[ICC_2023](https://github.com/dianixn/ICC_2023)| -|[modular model-based bayesian learning for uncertainty-aware and reliable deep mimo receivers](https://arxiv.org/abs/2302.02436)|[bayesian-learning-for-receivers](https://github.com/tomerraviv95/bayesian-learning-for-receivers)| +|date|paper|code| +|---|---|---| +|2302.02302|[achieving robust generalization for wireless channel estimation neural networks by designed training data](https://arxiv.org/abs/2302.02302)|[ICC_2023](https://github.com/dianixn/ICC_2023)| +|2302.02436|[modular model-based bayesian learning for uncertainty-aware and reliable deep mimo receivers](https://arxiv.org/abs/2302.02436)|[bayesian-learning-for-receivers](https://github.com/tomerraviv95/bayesian-learning-for-receivers)| ## 2023-02-06 -|paper|code| -|---|---| -|[load modulation for backscatter communication: channel capacity and capacity-approaching finite constellations](https://arxiv.org/abs/2207.08100)|[backscatteratcapacity](https://github.com/grdu/backscatteratcapacity)| -|[enhancing deep learning performance of massive mimo csi feedback](https://arxiv.org/abs/2208.11333)|[jpts](https://github.com/sijieji/jpts)| -|[low-complexity precoding for extremely large-scale mimo over non-stationary channels](https://arxiv.org/abs/2302.00847)|[Low-complexity-precoding-algorithm-for-XL-MIMO](https://github.com/bokaixu5/Low-complexity-precoding-algorithm-for-XL-MIMO)| -|[self-supervised enhancement of stimulus-evoked brain response data](https://arxiv.org/abs/2302.01924)|[shift_detection_icassp2023](https://github.com/exporl/shift_detection_icassp2023)| +|date|paper|code| +|---|---|---| +|2302.00847|[low-complexity precoding for extremely large-scale mimo over non-stationary channels](https://arxiv.org/abs/2302.00847)|[Low-complexity-precoding-algorithm-for-XL-MIMO](https://github.com/bokaixu5/Low-complexity-precoding-algorithm-for-XL-MIMO)| +|2302.01924|[self-supervised enhancement of stimulus-evoked brain response data](https://arxiv.org/abs/2302.01924)|[shift_detection_icassp2023](https://github.com/exporl/shift_detection_icassp2023)| ## 2023-02-03 -|paper|code| -|---|---| -|[closed loop bci system for cybathlon 2020](https://arxiv.org/abs/2212.04172)|[GoPar](https://github.com/kolcs/GoPar)| -|[exposing the csi: a systematic investigation of csi-based wi-fi sensing capabilities and limitations](https://arxiv.org/abs/2302.00992)|[exposing-the-csi](https://github.com/ansresearch/exposing-the-csi)| -|[neural estimation of the rate-distortion function with applications to operational source coding](https://arxiv.org/abs/2204.01612)|[nerd-rcc](https://github.com/leieric/nerd-rcc)| -|[inductive graph transformer for delivery time estimation](https://arxiv.org/abs/2211.02863)|[igt-wsdm23](https://github.com/enoche/igt-wsdm23)| +|date|paper|code| +|---|---|---| +|2302.00992|[exposing the csi: a systematic investigation of csi-based wi-fi sensing capabilities and limitations](https://arxiv.org/abs/2302.00992)|[exposing-the-csi](https://github.com/ansresearch/exposing-the-csi)| ## 2023-02-02 -|paper|code| -|---|---| -|[source detection via multi-label classification](https://arxiv.org/abs/2209.13553)|[Signal_detector](https://github.com/jkrishnan95v/Signal_detector)| +|date|paper|code| +|---|---|---| ## 2023-02-01 -|paper|code| -|---|---| -|[recurrences reveal shared causal drivers of complex time series](https://arxiv.org/abs/2301.13516)|[shrec](https://github.com/williamgilpin/shrec)| -|[bayesian estimation of information-theoretic metrics for sparsely sampled distributions](https://arxiv.org/abs/2301.13647)|[info-metric-estimation](https://github.com/angelopiga/info-metric-estimation)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/03.md b/archives/2023/03.md index f4560556..3e5b6c78 100644 --- a/archives/2023/03.md +++ b/archives/2023/03.md @@ -1,191 +1,131 @@ # March 2023 Archive ## 2023-03-31 -|paper|code| -|---|---| -|[spider-web generates coding algorithms with superior error tolerance and real-time information retrieval capacity](https://arxiv.org/abs/2204.02855)|[dnaspiderweb](https://github.com/haolingzhang/dnaspiderweb)| +|date|paper|code| +|---|---|---| ## 2023-03-30 -|paper|code| -|---|---| -|[urglq: an efficient covariance matrix reconstruction method for robust adaptive beamforming](https://arxiv.org/abs/2210.02214)|[robust-adaptive-beamforming-2022](https://github.com/chenpengseu/robust-adaptive-beamforming-2022)| -|[deep reinforcement learning based joint downlink beamforming and ris configuration in ris-aided mu-miso systems under hardware impairments and imperfect csi](https://arxiv.org/abs/2211.09702)|[ris-miso-pda-deep-reinforcement-learning](https://github.com/baturaysaglam/ris-miso-pda-deep-reinforcement-learning)| -|[lmda-net:a lightweight multi-dimensional attention network for general eeg-based brain-computer interface paradigms and interpretability](https://arxiv.org/abs/2303.16407)|[braindecode](https://github.com/TNTLFreiburg/braindecode)| -|[a framework for control channels applied to reconfigurable intelligent surfaces](https://arxiv.org/abs/2303.16797)|[ris-control](https://github.com/lostinafro/ris-control)| -|[folded polynomial codes for coded distributed $aa^\top$-type matrix multiplication](https://arxiv.org/abs/2211.15267)|[foldedpolynomialcodes](https://github.com/shinez9/foldedpolynomialcodes)| +|date|paper|code| +|---|---|---| +|2303.16407|[lmda-net:a lightweight multi-dimensional attention network for general eeg-based brain-computer interface paradigms and interpretability](https://arxiv.org/abs/2303.16407)|[braindecode](https://github.com/TNTLFreiburg/braindecode)| +|2303.16797|[a framework for control channels applied to reconfigurable intelligent surfaces](https://arxiv.org/abs/2303.16797)|[ris-control](https://github.com/lostinafro/ris-control)| ## 2023-03-29 -|paper|code| -|---|---| -|[dictionary learning for the almost-linear sparsity regime](https://arxiv.org/abs/2210.10855)|[spectral_dict_learn](https://github.com/sew347/spectral_dict_learn)| -|[cosys-airsim: a real-time simulation framework expanded for complex industrial applications](https://arxiv.org/abs/2303.13381)|[Cosys-AirSim](https://github.com/Cosys-Lab/Cosys-AirSim)| -|[transthoracic super-resolution ultrasound localisation microscopy of myocardial vasculature in patients](https://arxiv.org/abs/2303.14003)|[srussoftware](https://github.com/jipengyan1995/srussoftware)| -|[square root {lasso}: well-posedness, lipschitz stability and the tuning trade off](https://arxiv.org/abs/2303.15588)|[srlasso_revolutions](https://github.com/asberk/srlasso_revolutions)| -|[adjacent-bits-swapped polar codes: a new code construction to speed up polarization](https://arxiv.org/abs/2202.04454)|[abs-polar](https://github.com/plumjelly/abs-polar)| +|date|paper|code| +|---|---|---| +|2303.13381|[cosys-airsim: a real-time simulation framework expanded for complex industrial applications](https://arxiv.org/abs/2303.13381)|[Cosys-AirSim](https://github.com/Cosys-Lab/Cosys-AirSim)| +|2303.14003|[transthoracic super-resolution ultrasound localisation microscopy of myocardial vasculature in patients](https://arxiv.org/abs/2303.14003)|[srussoftware](https://github.com/jipengyan1995/srussoftware)| +|2303.15588|[square root {lasso}: well-posedness, lipschitz stability and the tuning trade off](https://arxiv.org/abs/2303.15588)|[srlasso_revolutions](https://github.com/asberk/srlasso_revolutions)| ## 2023-03-28 -|paper|code| -|---|---| -|[wemac: women and emotion multi-modal affective computing dataset](https://arxiv.org/abs/2203.00456)|[wemac_dataset_speech_processing](https://github.com/bindi-uc3m/wemac_dataset_speech_processing)| -|[unsupervised voice activity detection by modeling source and system information using zero frequency filtering](https://arxiv.org/abs/2206.13420)|[zff_vad](https://github.com/idiap/zff_vad)| -|[low-complexity blind parameter estimation in wireless systems with noisy sparse signals](https://arxiv.org/abs/2302.14089)|[blind_and_nonparametric_estimators](https://github.com/iip-group/blind_and_nonparametric_estimators)| -|[dimensionality collapse: optimal measurement selection for low-error infinite-horizon forecasting](https://arxiv.org/abs/2303.15407)|[naumer_dimensionality_2022.jl](https://github.com/helmuthn/naumer_dimensionality_2022.jl)| +|date|paper|code| +|---|---|---| +|2303.15407|[dimensionality collapse: optimal measurement selection for low-error infinite-horizon forecasting](https://arxiv.org/abs/2303.15407)|[naumer_dimensionality_2022.jl](https://github.com/helmuthn/naumer_dimensionality_2022.jl)| ## 2023-03-27 -|paper|code| -|---|---| -|[latent signal models: learning compact representations of signal evolution for improved time-resolved, multi-contrast mri](https://arxiv.org/abs/2208.13003)|[latent_signal_models_mrm_2022](https://github.com/yaminarefeen/latent_signal_models_mrm_2022)| +|date|paper|code| +|---|---|---| ## 2023-03-24 -|paper|code| -|---|---| -|[physical lidar simulation in real-time engine](https://arxiv.org/abs/2208.10295)|[Cosys-AirSim](https://github.com/Cosys-Lab/Cosys-AirSim)| +|date|paper|code| +|---|---|---| ## 2023-03-23 -|paper|code| -|---|---| -|[sdoanet: an efficient deep learning-based doa estimation network for imperfect array](https://arxiv.org/abs/2203.10231)|[sdoanet](https://github.com/chenpengseu/sdoanet)| -|[distributed two-tier drl framework for cell-free network: association, beamforming and power allocation](https://arxiv.org/abs/2303.12479)|[dhdrl](https://github.com/kiven-ykw/dhdrl)| -|[localization-based ofdm framework for ris-aided systems](https://arxiv.org/abs/2303.12763)|[ris-ofdm-loca-scheduling](https://github.com/lostinafro/ris-ofdm-loca-scheduling)| -|[orthogonal non-negative matrix factorization: a maximum-entropy-principle approach](https://arxiv.org/abs/2210.02672)|[mep-orthogonal-nmf](https://github.com/salar96/mep-orthogonal-nmf)| +|date|paper|code| +|---|---|---| +|2303.12479|[distributed two-tier drl framework for cell-free network: association, beamforming and power allocation](https://arxiv.org/abs/2303.12479)|[dhdrl](https://github.com/kiven-ykw/dhdrl)| +|2303.12763|[localization-based ofdm framework for ris-aided systems](https://arxiv.org/abs/2303.12763)|[ris-ofdm-loca-scheduling](https://github.com/lostinafro/ris-ofdm-loca-scheduling)| ## 2023-03-22 -|paper|code| -|---|---| -|[mean subtraction and mode selection in dynamic mode decomposition](https://arxiv.org/abs/2105.03607)|[msub_mdselect_dmd](https://github.com/gowtham-ss-ragavan/msub_mdselect_dmd)| -|[probabilistic estimation of instantaneous frequencies of chirp signals](https://arxiv.org/abs/2205.06306)|[chirpgp](https://github.com/spdes/chirpgp)| -|[integration of physics-based and data-driven models for hyperspectral image unmixing](https://arxiv.org/abs/2206.05508)|[awesome-hyperspectral-image-unmixing](https://github.com/xiuheng-wang/awesome-hyperspectral-image-unmixing)| -|[learning model-free robust precoding for cooperative multibeam satellite communications](https://arxiv.org/abs/2303.11427)|[2302_learning_beamforming_code](https://github.com/steffengra/2302_learning_beamforming_code)| +|date|paper|code| +|---|---|---| +|2303.11427|[learning model-free robust precoding for cooperative multibeam satellite communications](https://arxiv.org/abs/2303.11427)|[2302_learning_beamforming_code](https://github.com/steffengra/2302_learning_beamforming_code)| ## 2023-03-21 -|paper|code| -|---|---| -|[group-level brain decoding with deep learning](https://arxiv.org/abs/2205.14102)|[meg-group-decode](https://github.com/ricsinaruto/meg-group-decode)| -|[defending adversarial attacks on deep learning based power allocation in massive mimo using denoising autoencoders](https://arxiv.org/abs/2211.15365)|[dae_for_adv_attacks_in_mimo](https://github.com/jess-jpg-txt/dae_for_adv_attacks_in_mimo)| -|[modular model-based bayesian learning for uncertainty-aware and reliable deep mimo receivers](https://arxiv.org/abs/2302.02436)|[bayesian-learning-for-receivers](https://github.com/tomerraviv95/bayesian-learning-for-receivers)| -|[emc2-net: joint equalization and modulation classification based on constellation network](https://arxiv.org/abs/2303.10934)|[emc2net](https://github.com/hyun-ryu/emc2net)| -|[adjacent-bits-swapped polar codes: a new code construction to speed up polarization](https://arxiv.org/abs/2202.04454)|[abs-polar](https://github.com/plumjelly/abs-polar)| -|[sionna: an open-source library for next-generation physical layer research](https://arxiv.org/abs/2203.11854)|[sionna](https://github.com/nvlabs/sionna)| -|[structured gradient descent for fast robust low-rank hankel matrix completion](https://arxiv.org/abs/2204.03316)|[hsgd](https://github.com/caesarcai/hsgd)| -|[encoding, decoding, and causality between complex networks](https://arxiv.org/abs/2207.06606)|[analytic-relations-between-complex-networks-encoding-decoding-and-causality](https://github.com/doloming/analytic-relations-between-complex-networks-encoding-decoding-and-causality)| -|[sionna rt: differentiable ray tracing for radio propagation modeling](https://arxiv.org/abs/2303.11103)|[diff-rt](https://github.com/nvlabs/diff-rt)| +|date|paper|code| +|---|---|---| +|2303.10934|[emc2-net: joint equalization and modulation classification based on constellation network](https://arxiv.org/abs/2303.10934)|[emc2net](https://github.com/hyun-ryu/emc2net)| +|2303.11103|[sionna rt: differentiable ray tracing for radio propagation modeling](https://arxiv.org/abs/2303.11103)|[diff-rt](https://github.com/nvlabs/diff-rt)| ## 2023-03-20 -|paper|code| -|---|---| -|[annealed langevin dynamics for massive mimo detection](https://arxiv.org/abs/2205.05776)|[langevin-mimo-detector](https://github.com/nzilberstein/langevin-mimo-detector)| +|date|paper|code| +|---|---|---| ## 2023-03-17 -|paper|code| -|---|---| -|[srmd: sparse random mode decomposition](https://arxiv.org/abs/2204.06108)|[sparserandommodedecomposition](https://github.com/giangttran/sparserandommodedecomposition)| -|[pendantss: penalized norm-ratios disentangling additive noise, trend and sparse spikes](https://arxiv.org/abs/2301.01514)|[pendantss](https://github.com/paulzhengfr/pendantss)| -|[offline learning of closed-loop deep brain stimulation controllers for parkinson disease treatment](https://arxiv.org/abs/2302.02477)|[vlbm](https://github.com/gaoqitong/vlbm)| -|[synthetic ecg signal generation using probabilistic diffusion models](https://arxiv.org/abs/2303.02475)|[augmentation-of-ecg-training-dataset-with-cgan](https://github.com/mah533/augmentation-of-ecg-training-dataset-with-cgan)| -|[text-to-ecg: 12-lead electrocardiogram synthesis conditioned on clinical text reports](https://arxiv.org/abs/2303.09395)|[text_to_ecg](https://github.com/tclife/text_to_ecg)| -|[tackling clutter in radar data -- label generation and detection using pointnet++](https://arxiv.org/abs/2303.09530)|[clutter-ds](https://github.com/kopp-j/clutter-ds)| +|date|paper|code| +|---|---|---| +|2303.02475|[synthetic ecg signal generation using probabilistic diffusion models](https://arxiv.org/abs/2303.02475)|[augmentation-of-ecg-training-dataset-with-cgan](https://github.com/mah533/augmentation-of-ecg-training-dataset-with-cgan)| +|2303.09395|[text-to-ecg: 12-lead electrocardiogram synthesis conditioned on clinical text reports](https://arxiv.org/abs/2303.09395)|[text_to_ecg](https://github.com/tclife/text_to_ecg)| +|2303.09530|[tackling clutter in radar data -- label generation and detection using pointnet++](https://arxiv.org/abs/2303.09530)|[clutter-ds](https://github.com/kopp-j/clutter-ds)| ## 2023-03-16 -|paper|code| -|---|---| -|[dct-former: efficient self-attention with discrete cosine transform](https://arxiv.org/abs/2203.01178)|[dct-former-public](https://github.com/cscribano/dct-former-public)| -|[learning resilient radio resource management policies with graph neural networks](https://arxiv.org/abs/2203.11012)|[Resilient_RRM_GNN](https://github.com/navid-naderi/Resilient_RRM_GNN)| -|[flex-net: a graph neural network approach to resource management in flexible duplex networks](https://arxiv.org/abs/2301.11166)|[flex-net](https://github.com/tharaka-perera/flex-net)| +|date|paper|code| +|---|---|---| ## 2023-03-15 -|paper|code| -|---|---| -|[phaseaug: a differentiable augmentation for speech synthesis to simulate one-to-many mapping](https://arxiv.org/abs/2211.04610)|[phaseaug](https://github.com/mindslab-ai/phaseaug)| -|[self-attention for enhanced oamp detection in mimo systems](https://arxiv.org/abs/2303.07821)|[self_attention_oamp_mimo](https://github.com/alexf1991/self_attention_oamp_mimo)| -|[transition waste optimization for coded elastic computing](https://arxiv.org/abs/1910.00796)|[coded_elastic_computing](https://github.com/dausonhoang/coded_elastic_computing)| +|date|paper|code| +|---|---|---| +|2303.07821|[self-attention for enhanced oamp detection in mimo systems](https://arxiv.org/abs/2303.07821)|[self_attention_oamp_mimo](https://github.com/alexf1991/self_attention_oamp_mimo)| ## 2023-03-14 -|paper|code| -|---|---| -|[fundamentals of wobbling and hardware impairments-aware air-to-ground channel model](https://arxiv.org/abs/2205.10957)|[Wobbling-HI-Drones](https://github.com/mbanagar/Wobbling-HI-Drones)| -|[a neural-network framework for the design of individualised hearing-loss compensation](https://arxiv.org/abs/2207.07091)|[dnn-ha](https://github.com/hearingtechnology/dnn-ha)| -|[exploiting temporal structures of cyclostationary signals for data-driven single-channel source separation](https://arxiv.org/abs/2208.10325)|[scss_csgaussian](https://github.com/rfchallenge/scss_csgaussian)| -|[graph neural networks on spd manifolds for motor imagery classification: a perspective from the time-frequency analysis](https://arxiv.org/abs/2211.02641)|[Tensor-CSPNet-and-Graph-CSPNet](https://github.com/GeometricBCI/Tensor-CSPNet-and-Graph-CSPNet)| -|[efficient ecg-based atrial fibrillation detection via parameterised hypercomplex neural networks](https://arxiv.org/abs/2211.02678)|[hypercomplexecg](https://github.com/leibniz-future-lab/hypercomplexecg)| -|[assessing gender fairness in eeg-based machine learning detection of parkinson's disease: a multi-center study](https://arxiv.org/abs/2303.06376)|[multicentric-ml-parkinson-detection](https://github.com/biomedical-data-analysis-laboratory/multicentric-ml-parkinson-detection)| -|[challenges facing the explainability of age prediction models: case study for two modalities](https://arxiv.org/abs/2303.06640)|[challenges-xai-aging-aaai23](https://github.com/pbiecek/challenges-xai-aging-aaai23)| -|[securing data in multimode fibers by exploiting mode-dependent light propagation effects](https://arxiv.org/abs/2203.02064)|[mmf-physec](https://github.com/klb2/mmf-physec)| +|date|paper|code| +|---|---|---| +|2303.06376|[assessing gender fairness in eeg-based machine learning detection of parkinson's disease: a multi-center study](https://arxiv.org/abs/2303.06376)|[multicentric-ml-parkinson-detection](https://github.com/biomedical-data-analysis-laboratory/multicentric-ml-parkinson-detection)| +|2303.06640|[challenges facing the explainability of age prediction models: case study for two modalities](https://arxiv.org/abs/2303.06640)|[challenges-xai-aging-aaai23](https://github.com/pbiecek/challenges-xai-aging-aaai23)| ## 2023-03-13 -|paper|code| -|---|---| -|[neonatal eeg graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy](https://arxiv.org/abs/2206.04420)|[downsample_open_eeg](https://github.com/otoolej/downsample_open_eeg)| -|[sliced-wasserstein on symmetric positive definite matrices for m/eeg signals](https://arxiv.org/abs/2303.05798)|[Sliced-Wasserstein_on_Symmetric_Positive_Definite_Matrices](https://github.com/clbonet/Sliced-Wasserstein_on_Symmetric_Positive_Definite_Matrices)| -|[eeg synthetic data generation using probabilistic diffusion models](https://arxiv.org/abs/2303.06068)|[eeg-diffusion-pytorch](https://github.com/devjake/eeg-diffusion-pytorch)| -|[wigner distribution deconvolution adaptation for live ptychography reconstruction](https://arxiv.org/abs/2212.01309)|[livewdd](https://github.com/ptychography-4-0/livewdd)| +|date|paper|code| +|---|---|---| +|2303.05798|[sliced-wasserstein on symmetric positive definite matrices for m/eeg signals](https://arxiv.org/abs/2303.05798)|[Sliced-Wasserstein_on_Symmetric_Positive_Definite_Matrices](https://github.com/clbonet/Sliced-Wasserstein_on_Symmetric_Positive_Definite_Matrices)| +|2303.06068|[eeg synthetic data generation using probabilistic diffusion models](https://arxiv.org/abs/2303.06068)|[eeg-diffusion-pytorch](https://github.com/devjake/eeg-diffusion-pytorch)| ## 2023-03-10 -|paper|code| -|---|---| -|[adaptive decoding mechanisms for uav-enabled double-uplink coordinated noma](https://arxiv.org/abs/2206.13370)|[uav-noma-adm](https://github.com/thanhluannguyen/uav-noma-adm)| -|[invertible kernel pca with random fourier features](https://arxiv.org/abs/2303.05043)|[invertible_kernel_PCA](https://github.com/dgedon/invertible_kernel_PCA)| -|[a classification of s-boxes generated by orthogonal cellular automata](https://arxiv.org/abs/2303.05228)|[orthogonal-ca-sboxes](https://github.com/rymoah/orthogonal-ca-sboxes)| -|[statistical mechanics of the maximum-average submatrix problem](https://arxiv.org/abs/2303.05237)|[Maximum-Average-Submatrix](https://github.com/SPOC-group/Maximum-Average-Submatrix)| +|date|paper|code| +|---|---|---| +|2303.05043|[invertible kernel pca with random fourier features](https://arxiv.org/abs/2303.05043)|[invertible_kernel_PCA](https://github.com/dgedon/invertible_kernel_PCA)| +|2303.05228|[a classification of s-boxes generated by orthogonal cellular automata](https://arxiv.org/abs/2303.05228)|[orthogonal-ca-sboxes](https://github.com/rymoah/orthogonal-ca-sboxes)| +|2303.05237|[statistical mechanics of the maximum-average submatrix problem](https://arxiv.org/abs/2303.05237)|[Maximum-Average-Submatrix](https://github.com/SPOC-group/Maximum-Average-Submatrix)| ## 2023-03-09 -|paper|code| -|---|---| -|[covid19 reproduction number: credibility intervals by blockwise proximal monte carlo samplers](https://arxiv.org/abs/2203.09142)|[OpSiMorE](https://github.com/gfort-lab/OpSiMorE)| -|[neural collapse with normalized features: a geometric analysis over the riemannian manifold](https://arxiv.org/abs/2209.09211)|[normalized-neural-collapse](https://github.com/cjyaras/normalized-neural-collapse)| -|[grid-free harmonic retrieval and model order selection using deep convolutional neural networks](https://arxiv.org/abs/2211.04846)|[deepest-demo](https://huggingface.co/spaces/EMS-TU-Ilmenau/deepest-demo)| -|[nonlinear kalman filtering with reparametrization gradients](https://arxiv.org/abs/2303.04450)|[nonkf_energy_minimization](https://github.com/sangultekin/nonkf_energy_minimization)| +|date|paper|code| +|---|---|---| +|2303.04450|[nonlinear kalman filtering with reparametrization gradients](https://arxiv.org/abs/2303.04450)|[nonkf_energy_minimization](https://github.com/sangultekin/nonkf_energy_minimization)| ## 2023-03-08 -|paper|code| -|---|---| -|[large graph signal denoising with application to differential privacy](https://arxiv.org/abs/2209.02043)|[dp-graph-denoising](https://gitlab.com/elie-chedemail/dp-graph-denoising)| -|[unsupervised particle sorting for cryo-em using probabilistic pca](https://arxiv.org/abs/2210.12811)|[particle_sorting](https://github.com/giliw/particle_sorting)| -|[bit error and block error rate training for ml-assisted communication](https://arxiv.org/abs/2210.14103)|[bler_training](https://github.com/iip-group/bler_training)| -|[fast fullsubnet: accelerate full-band and sub-band fusion model for single-channel speech enhancement](https://arxiv.org/abs/2212.09019)|[fullsubnet](https://github.com/audio-westlakeu/fullsubnet)| -|[a comparative study of deep learning and iterative algorithms for joint channel estimation and signal detection](https://arxiv.org/abs/2303.03678)|[mimo_jcesd](https://github.com/j991222/mimo_jcesd)| -|[a switching gaussian process latent force model for the identification of mechanical systems with a discontinuous nonlinearity](https://arxiv.org/abs/2303.03858)|[switching-gplfm](https://github.com/l-marino/switching-gplfm)| +|date|paper|code| +|---|---|---| +|2303.03678|[a comparative study of deep learning and iterative algorithms for joint channel estimation and signal detection](https://arxiv.org/abs/2303.03678)|[mimo_jcesd](https://github.com/j991222/mimo_jcesd)| +|2303.03858|[a switching gaussian process latent force model for the identification of mechanical systems with a discontinuous nonlinearity](https://arxiv.org/abs/2303.03858)|[switching-gplfm](https://github.com/l-marino/switching-gplfm)| ## 2023-03-07 -|paper|code| -|---|---| -|[few-shot domain adaptation for end-to-end communication](https://arxiv.org/abs/2108.00874)|[domain-adaptation-autoencoder](https://github.com/jayaram-r/domain-adaptation-autoencoder)| -|[a stochastic approximate expectation-maximization for structure determination directly from cryo-em micrographs](https://arxiv.org/abs/2303.02157)|[stochastic-approximate-em-for-cryo-em](https://github.com/krshay/stochastic-approximate-em-for-cryo-em)| -|[data-driven method for generating synthetic electrogastrogram time series](https://arxiv.org/abs/2303.02408)|[syegg](https://github.com/nadicasm/syegg)| -|[synthetic ecg signal generation using probabilistic diffusion models](https://arxiv.org/abs/2303.02475)|[augmentation-of-ecg-training-dataset-with-cgan](https://github.com/mah533/augmentation-of-ecg-training-dataset-with-cgan)| -|[searching for effective neural network architectures for heart murmur detection from phonocardiogram](https://arxiv.org/abs/2303.02988)|[cinc2022](https://github.com/deeppsp/cinc2022)| -|[deepmad: mathematical architecture design for deep convolutional neural network](https://arxiv.org/abs/2303.02165)|[lightweight-neural-architecture-search](https://github.com/alibaba/lightweight-neural-architecture-search)| -|[on probabilistic qam shaping for 5g mimo wireless channel with realistic ldpc codes](https://arxiv.org/abs/2303.02598)|[on-probabilistic-qam-shaping-for-5g-mimo-wireless-channel-with-realistic-ldpc-codes](https://github.com/eugenbobrov/on-probabilistic-qam-shaping-for-5g-mimo-wireless-channel-with-realistic-ldpc-codes)| -|[rotation invariant quantization for model compression](https://arxiv.org/abs/2303.03106)|[riq](https://github.com/ehaleva/riq)| +|date|paper|code| +|---|---|---| +|2303.02157|[a stochastic approximate expectation-maximization for structure determination directly from cryo-em micrographs](https://arxiv.org/abs/2303.02157)|[stochastic-approximate-em-for-cryo-em](https://github.com/krshay/stochastic-approximate-em-for-cryo-em)| +|2303.02408|[data-driven method for generating synthetic electrogastrogram time series](https://arxiv.org/abs/2303.02408)|[syegg](https://github.com/nadicasm/syegg)| +|2303.02475|[synthetic ecg signal generation using probabilistic diffusion models](https://arxiv.org/abs/2303.02475)|[augmentation-of-ecg-training-dataset-with-cgan](https://github.com/mah533/augmentation-of-ecg-training-dataset-with-cgan)| +|2303.02988|[searching for effective neural network architectures for heart murmur detection from phonocardiogram](https://arxiv.org/abs/2303.02988)|[cinc2022](https://github.com/deeppsp/cinc2022)| +|2303.02165|[deepmad: mathematical architecture design for deep convolutional neural network](https://arxiv.org/abs/2303.02165)|[lightweight-neural-architecture-search](https://github.com/alibaba/lightweight-neural-architecture-search)| +|2303.02598|[on probabilistic qam shaping for 5g mimo wireless channel with realistic ldpc codes](https://arxiv.org/abs/2303.02598)|[on-probabilistic-qam-shaping-for-5g-mimo-wireless-channel-with-realistic-ldpc-codes](https://github.com/eugenbobrov/on-probabilistic-qam-shaping-for-5g-mimo-wireless-channel-with-realistic-ldpc-codes)| +|2303.03106|[rotation invariant quantization for model compression](https://arxiv.org/abs/2303.03106)|[riq](https://github.com/ehaleva/riq)| ## 2023-03-06 -|paper|code| -|---|---| -|[graph neural networks for distributed power allocation in wireless networks: aggregation over-the-air](https://arxiv.org/abs/2207.08498)|[gnn-aggregation-over-the-air](https://github.com/yifan-gu-szu/gnn-aggregation-over-the-air)| -|[towards v2i age-aware fairness access: a dqn based intelligent vehicular node training and test method](https://arxiv.org/abs/2208.01283)|[age-fairness](https://github.com/qiongwu86/age-fairness)| -|[distributed deep joint source-channel coding over a multiple access channel](https://arxiv.org/abs/2211.09920)|[deepjscc-noma](https://github.com/ipc-lab/deepjscc-noma)| -|[enhancing multivariate time series classifiers through self-attention and relative positioning infusion](https://arxiv.org/abs/2302.06683)|[timeseriesclassification-tps](https://github.com/mehryar72/timeseriesclassification-tps)| -|[quantized radio map estimation using tensor and deep generative models](https://arxiv.org/abs/2303.01770)|[Quantized-Radio-Map-Estimation-BTD-and-DGM](https://github.com/XiaoFuLab/Quantized-Radio-Map-Estimation-BTD-and-DGM)| +|date|paper|code| +|---|---|---| +|2303.01770|[quantized radio map estimation using tensor and deep generative models](https://arxiv.org/abs/2303.01770)|[Quantized-Radio-Map-Estimation-BTD-and-DGM](https://github.com/XiaoFuLab/Quantized-Radio-Map-Estimation-BTD-and-DGM)| ## 2023-03-03 -|paper|code| -|---|---| -|[signal inpainting from fourier magnitudes](https://arxiv.org/abs/2210.15951)|[inpainting-fourier](https://github.com/louis-bahrman/inpainting-fourier)| -|[distributed adaptive norm estimation for blind system identification in wireless sensor networks](https://arxiv.org/abs/2303.00832)|[icassp2023-adapt-dist-avg](https://github.com/sounds-research/icassp2023-adapt-dist-avg)| -|[pay less but get more: a dual-attention-based channel estimation network for massive mimo systems with low-density pilots](https://arxiv.org/abs/2303.00986)|[dacen](https://github.com/jessezhou18/dacen)| -|[learning transfer operators by kernel density estimation](https://arxiv.org/abs/2210.03124)|[fpoperatorde](https://github.com/sudamphy/fpoperatorde)| -|[the greedy side of the lasso: new algorithms for weighted sparse recovery via loss function-based orthogonal matching pursuit](https://arxiv.org/abs/2303.00844)|[greedy_lasso_womp](https://github.com/sina-taheri/greedy_lasso_womp)| +|date|paper|code| +|---|---|---| +|2303.00832|[distributed adaptive norm estimation for blind system identification in wireless sensor networks](https://arxiv.org/abs/2303.00832)|[icassp2023-adapt-dist-avg](https://github.com/sounds-research/icassp2023-adapt-dist-avg)| +|2303.00986|[pay less but get more: a dual-attention-based channel estimation network for massive mimo systems with low-density pilots](https://arxiv.org/abs/2303.00986)|[dacen](https://github.com/jessezhou18/dacen)| +|2303.00844|[the greedy side of the lasso: new algorithms for weighted sparse recovery via loss function-based orthogonal matching pursuit](https://arxiv.org/abs/2303.00844)|[greedy_lasso_womp](https://github.com/sina-taheri/greedy_lasso_womp)| ## 2023-03-02 -|paper|code| -|---|---| -|[nnsvs: a neural network-based singing voice synthesis toolkit](https://arxiv.org/abs/2210.15987)|[nnsvs](https://github.com/nnsvs/nnsvs)| -|[point cloud forecasting as a proxy for 4d occupancy forecasting](https://arxiv.org/abs/2302.13130)|[4d-occ-forecasting](https://github.com/tarashakhurana/4d-occ-forecasting)| -|[information plane analysis for dropout neural networks](https://arxiv.org/abs/2303.00596)|[ip_dropout](https://github.com/link-er/ip_dropout)| +|date|paper|code| +|---|---|---| +|2303.00596|[information plane analysis for dropout neural networks](https://arxiv.org/abs/2303.00596)|[ip_dropout](https://github.com/link-er/ip_dropout)| ## 2023-03-01 -|paper|code| -|---|---| -|[implementation of dnn based data detector for qpsk systems](https://arxiv.org/abs/2302.10073)|[qpsk_sdr_dnn_detector](https://github.com/abadi13/qpsk_sdr_dnn_detector)| -|[brainbert: self-supervised representation learning for intracranial recordings](https://arxiv.org/abs/2302.14367)|[brainbert](https://github.com/czlwang/brainbert)| -|[robust one-shot estimation over shared networks in the presence of denial-of-service attacks](https://arxiv.org/abs/2302.14689)|[ieee-tac2023](https://github.com/mullervasconcelos/ieee-tac2023)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/04.md b/archives/2023/04.md index 2852dc06..b51f68d5 100644 --- a/archives/2023/04.md +++ b/archives/2023/04.md @@ -1,150 +1,107 @@ # April 2023 Archive ## 2023-04-28 -|paper|code| -|---|---| -|[spiking neural network decision feedback equalization for im/dd systems](https://arxiv.org/abs/2304.14152)|[snn-dfe](https://github.com/kit-cel/snn-dfe)| -|[self-dual hadamard bent sequences](https://arxiv.org/abs/2203.16439)|[hadamard_bent](https://github.com/qomo-cheng/hadamard_bent)| -|[randomized and exchangeable improvements of markov's, chebyshev's and chernoff's inequalities](https://arxiv.org/abs/2304.02611)|[randomized-markov](https://github.com/tmanole/randomized-markov)| +|date|paper|code| +|---|---|---| +|2304.14152|[spiking neural network decision feedback equalization for im/dd systems](https://arxiv.org/abs/2304.14152)|[snn-dfe](https://github.com/kit-cel/snn-dfe)| +|2304.02611|[randomized and exchangeable improvements of markov's, chebyshev's and chernoff's inequalities](https://arxiv.org/abs/2304.02611)|[randomized-markov](https://github.com/tmanole/randomized-markov)| ## 2023-04-27 -|paper|code| -|---|---| -|[computationally-efficient initialisation of gps: the generalised variogram method](https://arxiv.org/abs/2210.05394)|[generalised-variogram-method](https://github.com/games-uchile/generalised-variogram-method)| -|[quantifying the impact of data characteristics on the transferability of sleep stage scoring models](https://arxiv.org/abs/2304.06033)|[transferability_sleep](https://github.com/akaraspt/transferability_sleep)| +|date|paper|code| +|---|---|---| +|2304.06033|[quantifying the impact of data characteristics on the transferability of sleep stage scoring models](https://arxiv.org/abs/2304.06033)|[transferability_sleep](https://github.com/akaraspt/transferability_sleep)| ## 2023-04-26 -|paper|code| -|---|---| -|[data-driven modeling of noise time series with convolutional generative adversarial networks](https://arxiv.org/abs/2207.01110)|[noisegan](https://github.com/usnistgov/noisegan)| -|[toward integrated sensing and communications in ieee 802.11bf wi-fi networks](https://arxiv.org/abs/2212.13930)|[sharpax](https://github.com/francescamen/sharpax)| +|date|paper|code| +|---|---|---| ## 2023-04-25 -|paper|code| -|---|---| -|[ultra lite convolutional neural network for fast automatic modulation classification in low-resource scenarios](https://arxiv.org/abs/2208.04659)|[ultra-lite-convolutional-neural-network-for-automatic-modulation-classification](https://github.com/beechburgpiestar/ultra-lite-convolutional-neural-network-for-automatic-modulation-classification)| -|[energy-efficient cell-free massive mimo through sparse large-scale fading processing](https://arxiv.org/abs/2208.13552)|[sparse-lsfprocess-cfmmimo](https://github.com/shuaifeichen273/sparse-lsfprocess-cfmmimo)| -|[score-based data generation for eeg spatial covariance matrices: towards boosting bci performance](https://arxiv.org/abs/2302.11410)|[Tensor-CSPNet-and-Graph-CSPNet](https://github.com/GeometricBCI/Tensor-CSPNet-and-Graph-CSPNet)| -|[locality sensitive hashing via mechanical behavior](https://arxiv.org/abs/2304.06505)|[mechhs](https://github.com/elejeune11/mechhs)| -|[identifying stochasticity in time-series with autoencoder-based content-aware 2d representation: application to black hole data](https://arxiv.org/abs/2304.11560)|[blackhole_1d_2d_label](https://github.com/csai-arc/blackhole_1d_2d_label)| -|[a lightweight recurrent learning network for sustainable compressed sensing](https://arxiv.org/abs/2304.11674)|[csrn](https://github.com/c66yu/csrn)| -|[model-free learning of optimal two-stage beamformers for passive irs-aided network design](https://arxiv.org/abs/2304.11464)|[zosga-irs](https://github.com/hassaanhashmi/zosga-irs)| +|date|paper|code| +|---|---|---| +|2304.06505|[locality sensitive hashing via mechanical behavior](https://arxiv.org/abs/2304.06505)|[mechhs](https://github.com/elejeune11/mechhs)| +|2304.11560|[identifying stochasticity in time-series with autoencoder-based content-aware 2d representation: application to black hole data](https://arxiv.org/abs/2304.11560)|[blackhole_1d_2d_label](https://github.com/csai-arc/blackhole_1d_2d_label)| +|2304.11674|[a lightweight recurrent learning network for sustainable compressed sensing](https://arxiv.org/abs/2304.11674)|[csrn](https://github.com/c66yu/csrn)| +|2304.11464|[model-free learning of optimal two-stage beamformers for passive irs-aided network design](https://arxiv.org/abs/2304.11464)|[zosga-irs](https://github.com/hassaanhashmi/zosga-irs)| ## 2023-04-24 -|paper|code| -|---|---| -|[smoothed separable nonnegative matrix factorization](https://arxiv.org/abs/2110.05528)|[smoothed-separable-nmf](https://gitlab.com/nnadisic/smoothed-separable-nmf)| -|[transformers in time series: a survey](https://arxiv.org/abs/2202.07125)|[time-series-transformers-review](https://github.com/qingsongedu/time-series-transformers-review)| -|[an orchestration framework for open system models of reconfigurable intelligent surfaces](https://arxiv.org/abs/2304.10858)|[self-configuring-orchestration](https://github.com/victorcroisfelt/self-configuring-orchestration)| +|date|paper|code| +|---|---|---| +|2304.10858|[an orchestration framework for open system models of reconfigurable intelligent surfaces](https://arxiv.org/abs/2304.10858)|[self-configuring-orchestration](https://github.com/victorcroisfelt/self-configuring-orchestration)| ## 2023-04-21 -|paper|code| -|---|---| -|[outlier detection of vital sign trajectories from covid-19 patients](https://arxiv.org/abs/2207.07572)|[outlier-detection-recap-data](https://github.com/sara-es/outlier-detection-recap-data)| -|[latent-kalmannet: learned kalman filtering for tracking from high-dimensional signals](https://arxiv.org/abs/2304.07827)|[latent_kalmannet_tsp](https://github.com/kalmannet/latent_kalmannet_tsp)| +|date|paper|code| +|---|---|---| +|2304.07827|[latent-kalmannet: learned kalman filtering for tracking from high-dimensional signals](https://arxiv.org/abs/2304.07827)|[latent_kalmannet_tsp](https://github.com/kalmannet/latent_kalmannet_tsp)| ## 2023-04-20 -|paper|code| -|---|---| -|[robust semantic communications with masked vq-vae enabled codebook](https://arxiv.org/abs/2206.04011)|[RobustSemanComm](https://github.com/hqyyqh888/RobustSemanComm)| -|[entropy estimation via uniformization](https://arxiv.org/abs/2304.09700)|[nfee](https://github.com/ziq-ao/nfee)| +|date|paper|code| +|---|---|---| +|2304.09700|[entropy estimation via uniformization](https://arxiv.org/abs/2304.09700)|[nfee](https://github.com/ziq-ao/nfee)| ## 2023-04-19 -|paper|code| -|---|---| -|[tree-amp: compositional inference with tree approximate message passing](https://arxiv.org/abs/2004.01571)|[tramp](https://github.com/sphinxteam/tramp)| -|[towards best practice of interpreting deep learning models for eeg-based brain computer interfaces](https://arxiv.org/abs/2202.06948)|[Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI](https://github.com/cuijiancorbin/Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI)| -|[covid19 reproduction number: credibility intervals by blockwise proximal monte carlo samplers](https://arxiv.org/abs/2203.09142)|[OpSiMorE](https://github.com/gfort-lab/OpSiMorE)| -|[a semi-supervised adaptive discriminative discretization method improving discrimination power of regularized naive bayes](https://arxiv.org/abs/2111.10983)|[Semi-supervised-Adaptive-Discriminative-Discretization-for-Naive-Bayes-classifier](https://github.com/shellpower96/Semi-supervised-Adaptive-Discriminative-Discretization-for-Naive-Bayes-classifier)| +|date|paper|code| +|---|---|---| ## 2023-04-18 -|paper|code| -|---|---| -|[random access protocol with channel oracle enabled by a reconfigurable intelligent surface](https://arxiv.org/abs/2210.04230)|[ris-random-access-channel-oracle](https://github.com/victorcroisfelt/ris-random-access-channel-oracle)| -|[data-driven method for generating synthetic electrogastrogram time series](https://arxiv.org/abs/2303.02408)|[syegg](https://github.com/nadicasm/syegg)| -|[dimensionality collapse: optimal measurement selection for low-error infinite-horizon forecasting](https://arxiv.org/abs/2303.15407)|[naumer_dimensionality_2022.jl](https://github.com/helmuthn/naumer_dimensionality_2022.jl)| -|[learning to predict arbitrary quantum processes](https://arxiv.org/abs/2210.14894)|[learning-quantum-process](https://github.com/hsinyuan-huang/learning-quantum-process)| +|date|paper|code| +|---|---|---| ## 2023-04-17 -|paper|code| -|---|---| -|[denoiser-based projections for 2-d super-resolution multi-reference alignment](https://arxiv.org/abs/2204.04754)|[denoiser_projection](https://github.com/jonathanshani/denoiser_projection)| -|[cast: a toolchain for creating and characterizing realistic wireless network emulation scenarios](https://arxiv.org/abs/2208.03993)|[cast](https://github.com/wineslab/cast)| -|[online recognition of incomplete gesture data to interface collaborative robots](https://arxiv.org/abs/2304.06777)|[uc2017_classification](https://github.com/miguelsimao/uc2017_classification)| -|[a byte sequence is worth an image: cnn for file fragment classification using bit shift and n-gram embeddings](https://arxiv.org/abs/2304.06983)|[byte2image](https://github.com/wenyang001/byte2image)| -|[compressing multidimensional weather and climate data into neural networks](https://arxiv.org/abs/2210.12538)|[nncompression](https://github.com/spcl/nncompression)| +|date|paper|code| +|---|---|---| +|2304.06777|[online recognition of incomplete gesture data to interface collaborative robots](https://arxiv.org/abs/2304.06777)|[uc2017_classification](https://github.com/miguelsimao/uc2017_classification)| +|2304.06983|[a byte sequence is worth an image: cnn for file fragment classification using bit shift and n-gram embeddings](https://arxiv.org/abs/2304.06983)|[byte2image](https://github.com/wenyang001/byte2image)| ## 2023-04-14 -|paper|code| -|---|---| -|[neural network based generation of 1-dimensional stochastic fields with turbulent velocity statistics](https://arxiv.org/abs/2211.11580)|[nn-turb](https://github.com/cgranerob/nn-turb)| -|[square root lasso: well-posedness, lipschitz stability and the tuning trade off](https://arxiv.org/abs/2303.15588)|[srlasso_revolutions](https://github.com/asberk/srlasso_revolutions)| -|[eegmatch: learning with incomplete labels for semi-supervised eeg-based cross-subject emotion recognition](https://arxiv.org/abs/2304.06496)|[eegmatch](https://github.com/kazabana/eegmatch)| -|[multi-kernel correntropy-based orientation estimation of imus: gradient descent methods](https://arxiv.org/abs/2304.06548)|[mc_gd_imu](https://github.com/lsl-zsj/mc_gd_imu)| +|date|paper|code| +|---|---|---| +|2304.06496|[eegmatch: learning with incomplete labels for semi-supervised eeg-based cross-subject emotion recognition](https://arxiv.org/abs/2304.06496)|[eegmatch](https://github.com/kazabana/eegmatch)| +|2304.06548|[multi-kernel correntropy-based orientation estimation of imus: gradient descent methods](https://arxiv.org/abs/2304.06548)|[mc_gd_imu](https://github.com/lsl-zsj/mc_gd_imu)| ## 2023-04-13 -|paper|code| -|---|---| -|[olia: an open-source digital lock-in amplifier](https://arxiv.org/abs/2211.08889)|[olia](https://github.com/openlockin/olia)| -|[interpreting neural min-sum decoders](https://arxiv.org/abs/2205.10684)|[nams](https://github.com/sravan-ankireddy/nams)| +|date|paper|code| +|---|---|---| ## 2023-04-12 -|paper|code| -|---|---| -|[self-stabilization: the implicit bias of gradient descent at the edge of stability](https://arxiv.org/abs/2209.15594)|[eos](https://github.com/adamian98/eos)| +|date|paper|code| +|---|---|---| ## 2023-04-11 -|paper|code| -|---|---| -|[real-time outdoor localization using radio maps: a deep learning approach](https://arxiv.org/abs/2106.12556)|[LocUNet](https://github.com/CagkanYapar/LocUNet)| -|[correlative information maximization based biologically plausible neural networks for correlated source separation](https://arxiv.org/abs/2210.04222)|[Biologically-Plausible-Correlative-Information-Maximization-for-Blind-Source-Separation](https://github.com/BariscanBozkurt/Biologically-Plausible-Correlative-Information-Maximization-for-Blind-Source-Separation)| -|[minimal algorithmic information loss methods for dimension reduction, feature selection and network sparsification](https://arxiv.org/abs/1802.05843)|[Network-Robustness-by-Kolmogorov-Complexity](https://github.com/andandandand/Network-Robustness-by-Kolmogorov-Complexity)| +|date|paper|code| +|---|---|---| ## 2023-04-10 -|paper|code| -|---|---| -|[a novel channel model for reconfigurable intelligent surfaces with consideration of polarization and switch impairments](https://arxiv.org/abs/2304.03713)|[matlab_ris_channelmodel](https://github.com/icefreeman123/matlab_ris_channelmodel)| -|[quantum conformal prediction for reliable uncertainty quantification in quantum machine learning](https://arxiv.org/abs/2304.03398)|[quantum-cp](https://github.com/kclip/quantum-cp)| +|date|paper|code| +|---|---|---| +|2304.03713|[a novel channel model for reconfigurable intelligent surfaces with consideration of polarization and switch impairments](https://arxiv.org/abs/2304.03713)|[matlab_ris_channelmodel](https://github.com/icefreeman123/matlab_ris_channelmodel)| +|2304.03398|[quantum conformal prediction for reliable uncertainty quantification in quantum machine learning](https://arxiv.org/abs/2304.03398)|[quantum-cp](https://github.com/kclip/quantum-cp)| ## 2023-04-07 -|paper|code| -|---|---| -|[optimal discrete beamforming of ris-aided wireless communications: an inner product maximization approach](https://arxiv.org/abs/2211.04167)|[RIS_Optimization](https://github.com/RujingXiong/RIS_Optimization)| -|[towards flexibility and interpretability of gaussian process state-space model](https://arxiv.org/abs/2301.08843)|[tgpssm](https://github.com/zhidilin/tgpssm)| -|[learning stage-wise gans for whistle extraction in time-frequency spectrograms](https://arxiv.org/abs/2304.02714)|[CompositeGAN_WhistleAugment](https://github.com/Paul-LiPu/CompositeGAN_WhistleAugment)| +|date|paper|code| +|---|---|---| +|2304.02714|[learning stage-wise gans for whistle extraction in time-frequency spectrograms](https://arxiv.org/abs/2304.02714)|[CompositeGAN_WhistleAugment](https://github.com/Paul-LiPu/CompositeGAN_WhistleAugment)| ## 2023-04-06 -|paper|code| -|---|---| -|[a semi-supervised adaptive discriminative discretization method improving discrimination power of regularized naive bayes](https://arxiv.org/abs/2111.10983)|[Semi-supervised-Adaptive-Discriminative-Discretization-for-Naive-Bayes-classifier](https://github.com/shellpower96/Semi-supervised-Adaptive-Discriminative-Discretization-for-Naive-Bayes-classifier)| -|[the optimality of word lengths. theoretical foundations and an empirical study](https://arxiv.org/abs/2208.10384)|[iql-research-project-21-22](https://github.com/iql-course/iql-research-project-21-22)| -|[visualizing quantum circuit probability -- estimating computational action for quantum program synthesis](https://arxiv.org/abs/2304.02358)|[qcircscape](https://github.com/advanced-research-centre/qcircscape)| -|[reliability and latency analysis for wireless communication systems with a secret-key budget](https://arxiv.org/abs/2304.02538)|[secret-key-budget-ruin](https://github.com/klb2/secret-key-budget-ruin)| -|[randomized and exchangeable improvements of markov's, chebyshev's and chernoff's inequalities](https://arxiv.org/abs/2304.02611)|[randomized-markov](https://github.com/tmanole/randomized-markov)| +|date|paper|code| +|---|---|---| +|2304.02358|[visualizing quantum circuit probability -- estimating computational action for quantum program synthesis](https://arxiv.org/abs/2304.02358)|[qcircscape](https://github.com/advanced-research-centre/qcircscape)| +|2304.02538|[reliability and latency analysis for wireless communication systems with a secret-key budget](https://arxiv.org/abs/2304.02538)|[secret-key-budget-ruin](https://github.com/klb2/secret-key-budget-ruin)| +|2304.02611|[randomized and exchangeable improvements of markov's, chebyshev's and chernoff's inequalities](https://arxiv.org/abs/2304.02611)|[randomized-markov](https://github.com/tmanole/randomized-markov)| ## 2023-04-05 -|paper|code| -|---|---| -|[communication-efficient federated linear and deep generalized canonical correlation analysis](https://arxiv.org/abs/2109.12400)|[federated_max_var_gcca](https://github.com/XiaoFuLab/federated_max_var_gcca)| -|[attention-embedded quadratic network (qttention) for effective and interpretable bearing fault diagnosis](https://arxiv.org/abs/2206.00390)|[QCNN_for_bearing_diagnosis](https://github.com/asdvfghg/QCNN_for_bearing_diagnosis)| -|[autoencoder based iterative modeling and multivariate time-series subsequence clustering algorithm](https://arxiv.org/abs/2209.04213)|[abimca](https://github.com/jokonu/abimca)| -|[time-space-frequency feature fusion for 3-channel motor imagery classification](https://arxiv.org/abs/2304.01461)|[tsff](https://github.com/miaozhengqing/tsff)| -|[arrhythmia classifier based on ultra-lightweight binary neural network](https://arxiv.org/abs/2304.01568)|[ecg_bnn_net](https://github.com/xpww/ecg_bnn_net)| +|date|paper|code| +|---|---|---| +|2304.01461|[time-space-frequency feature fusion for 3-channel motor imagery classification](https://arxiv.org/abs/2304.01461)|[tsff](https://github.com/miaozhengqing/tsff)| +|2304.01568|[arrhythmia classifier based on ultra-lightweight binary neural network](https://arxiv.org/abs/2304.01568)|[ecg_bnn_net](https://github.com/xpww/ecg_bnn_net)| ## 2023-04-04 -|paper|code| -|---|---| -|[localizing unsynchronized sensors with unknown sources](https://arxiv.org/abs/2102.03565)|[xtdoa](https://github.com/swing-research/xtdoa)| -|[modeling multivariate biosignals with graph neural networks and structured state space models](https://arxiv.org/abs/2211.11176)|[graphs4mer](https://github.com/tsy935/graphs4mer)| -|[guaranteed dynamic scheduling of ultra-reliable low-latency traffic via conformal prediction](https://arxiv.org/abs/2302.07675)|[online_cp_urllc](https://github.com/kclip/online_cp_urllc)| -|[deep graph unfolding for beamforming in mu-mimo interference networks](https://arxiv.org/abs/2304.00446)|[unrolled-wmmse-for-mu-mimo](https://github.com/archo48/unrolled-wmmse-for-mu-mimo)| -|[on the optimal recovery of graph signals](https://arxiv.org/abs/2304.00474)|[orofgraphsignals](https://github.com/liaochunyang/orofgraphsignals)| -|[multi-layer state evolution under random convolutional design](https://arxiv.org/abs/2205.13503)|[conv-ml-amp](https://github.com/mdnls/conv-ml-amp)| -|[amgc: adaptive match-based genomic compression algorithm](https://arxiv.org/abs/2304.01031)|[amgc](https://github.com/wj-inf/amgc)| +|date|paper|code| +|---|---|---| +|2304.00446|[deep graph unfolding for beamforming in mu-mimo interference networks](https://arxiv.org/abs/2304.00446)|[unrolled-wmmse-for-mu-mimo](https://github.com/archo48/unrolled-wmmse-for-mu-mimo)| +|2304.00474|[on the optimal recovery of graph signals](https://arxiv.org/abs/2304.00474)|[orofgraphsignals](https://github.com/liaochunyang/orofgraphsignals)| +|2304.01031|[amgc: adaptive match-based genomic compression algorithm](https://arxiv.org/abs/2304.01031)|[amgc](https://github.com/wj-inf/amgc)| ## 2023-04-03 -|paper|code| -|---|---| -|[bounded simplex-structured matrix factorization: algorithms, identifiability and applications](https://arxiv.org/abs/2209.12638)|[bssmf.jl](https://gitlab.com/vuthanho/bssmf.jl)| -|[far from asymptopia](https://arxiv.org/abs/2205.03343)|[atomicpriors.jl](https://github.com/mcabbott/atomicpriors.jl)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/05.md b/archives/2023/05.md index 41206350..bd4fb284 100644 --- a/archives/2023/05.md +++ b/archives/2023/05.md @@ -1,190 +1,136 @@ # May 2023 Archive ## 2023-05-31 -|paper|code| -|---|---| -|[computational doob's h-transforms for online filtering of discretely observed diffusions](https://arxiv.org/abs/2206.03369)|[CompDoobTransform](https://github.com/jeremyhengjm/CompDoobTransform)| -|[invertible kernel pca with random fourier features](https://arxiv.org/abs/2303.05043)|[invertible_kernel_PCA](https://github.com/dgedon/invertible_kernel_PCA)| -|[on the optimal recovery of graph signals](https://arxiv.org/abs/2304.00474)|[orofgraphsignals](https://github.com/liaochunyang/orofgraphsignals)| -|[e-panns: sound recognition using efficient pre-trained audio neural networks](https://arxiv.org/abs/2305.18665)|[e-panns](https://github.com/arshdeep-singh-boparai/e-panns)| -|[the representation jensen-r\'enyi divergence](https://arxiv.org/abs/2112.01583)|[jensen-renyi-divergence](https://github.com/uk-cliplab/jensen-renyi-divergence)| -|[distributed inference over linear models using alternating gaussian belief propagation](https://arxiv.org/abs/2210.09808)|[FactorGraph.jl](https://github.com/mcosovic/FactorGraph.jl)| -|[structured model selection via $\ell_1-\ell_2$ optimization](https://arxiv.org/abs/2305.17467)|[nonconvexsparsecyclicrecovery](https://github.com/linanzhang/nonconvexsparsecyclicrecovery)| -|[how does information bottleneck help deep learning?](https://arxiv.org/abs/2305.18887)|[information-bottleneck](https://github.com/xu-ji/information-bottleneck)| -|[ambient diffusion: learning clean distributions from corrupted data](https://arxiv.org/abs/2305.19256)|[ambient-diffusion](https://github.com/giannisdaras/ambient-diffusion)| +|date|paper|code| +|---|---|---| +|2305.18665|[e-panns: sound recognition using efficient pre-trained audio neural networks](https://arxiv.org/abs/2305.18665)|[e-panns](https://github.com/arshdeep-singh-boparai/e-panns)| +|2305.17467|[structured model selection via $\ell_1-\ell_2$ optimization](https://arxiv.org/abs/2305.17467)|[nonconvexsparsecyclicrecovery](https://github.com/linanzhang/nonconvexsparsecyclicrecovery)| +|2305.18887|[how does information bottleneck help deep learning?](https://arxiv.org/abs/2305.18887)|[information-bottleneck](https://github.com/xu-ji/information-bottleneck)| +|2305.19256|[ambient diffusion: learning clean distributions from corrupted data](https://arxiv.org/abs/2305.19256)|[ambient-diffusion](https://github.com/giannisdaras/ambient-diffusion)| ## 2023-05-30 -|paper|code| -|---|---| -|[traffic simulator for multibeam satellite communication systems](https://arxiv.org/abs/2007.07148)|[Satellite-Traffic-Simulator](https://github.com/hayder-hussein/Satellite-Traffic-Simulator)| -|[exploring self-attention mechanisms for speech separation](https://arxiv.org/abs/2202.02884)|[speechbrain](https://github.com/speechbrain/speechbrain)| -|[doubly-iterative sparsified mmse turbo equalization for otfs modulation](https://arxiv.org/abs/2207.00866)|[dismmse-turbo-equalizer-for-otfs](https://github.com/alga53/dismmse-turbo-equalizer-for-otfs)| -|[optimal resource allocation with delay guarantees for network slicing in disaggregated ran](https://arxiv.org/abs/2305.17321)|[paper-fgkcj-2023](https://github.com/labora-inf-ufg/paper-fgkcj-2023)| -|[pulse shape discrimination based on the tempotron: a powerful classifier on gpu](https://arxiv.org/abs/2305.18205)|[TempotronGPU](https://github.com/HaoranLiu507/TempotronGPU)| -|[crisp: curriculum based sequential neural decoders for polar code family](https://arxiv.org/abs/2210.00313)|[neural_polar_decoder](https://github.com/hebbarashwin/neural_polar_decoder)| -|[diffusion model based posterior sampling for noisy linear inverse problems](https://arxiv.org/abs/2211.12343)|[dmps](https://github.com/mengxiangming/dmps)| -|[dime: maximizing mutual information by a difference of matrix-based entropies](https://arxiv.org/abs/2301.08164)|[DiME](https://github.com/uk-cliplab/DiME)| -|[on probability shaping for 5g mimo wireless channel with realistic ldpc codes](https://arxiv.org/abs/2303.02598)|[on-probabilistic-qam-shaping-for-5g-mimo-wireless-channel-with-realistic-ldpc-codes](https://github.com/eugenbobrov/on-probabilistic-qam-shaping-for-5g-mimo-wireless-channel-with-realistic-ldpc-codes)| +|date|paper|code| +|---|---|---| +|2305.17321|[optimal resource allocation with delay guarantees for network slicing in disaggregated ran](https://arxiv.org/abs/2305.17321)|[paper-fgkcj-2023](https://github.com/labora-inf-ufg/paper-fgkcj-2023)| +|2305.18205|[pulse shape discrimination based on the tempotron: a powerful classifier on gpu](https://arxiv.org/abs/2305.18205)|[TempotronGPU](https://github.com/HaoranLiu507/TempotronGPU)| ## 2023-05-29 -|paper|code| -|---|---| -|[modulate your spectrum in self-supervised learning](https://arxiv.org/abs/2305.16789)|[intl](https://github.com/winci-ai/intl)| -|[the representation jensen-shannon divergence](https://arxiv.org/abs/2305.16446)|[representationjsd](https://github.com/uk-cliplab/representationjsd)| -|[computation of reliability statistics for finite samples of success-failure experiments](https://arxiv.org/abs/2305.16578)|[relistats](https://github.com/sanjaymjoshi/relistats)| +|date|paper|code| +|---|---|---| +|2305.16789|[modulate your spectrum in self-supervised learning](https://arxiv.org/abs/2305.16789)|[intl](https://github.com/winci-ai/intl)| +|2305.16446|[the representation jensen-shannon divergence](https://arxiv.org/abs/2305.16446)|[representationjsd](https://github.com/uk-cliplab/representationjsd)| +|2305.16578|[computation of reliability statistics for finite samples of success-failure experiments](https://arxiv.org/abs/2305.16578)|[relistats](https://github.com/sanjaymjoshi/relistats)| ## 2023-05-26 -|paper|code| -|---|---| -|[qcm-sgm+: improved quantized compressed sensing with score-based generative models](https://arxiv.org/abs/2302.00919)|[qcs-sgm-plus](https://github.com/mengxiangming/qcs-sgm-plus)| -|[emergency response person localization and vital sign estimation using a semi-autonomous robot mounted sfcw radar](https://arxiv.org/abs/2305.15795)|[radar-vitals-estimation](https://github.com/schrchr/radar-vitals-estimation)| +|date|paper|code| +|---|---|---| +|2305.15795|[emergency response person localization and vital sign estimation using a semi-autonomous robot mounted sfcw radar](https://arxiv.org/abs/2305.15795)|[radar-vitals-estimation](https://github.com/schrchr/radar-vitals-estimation)| ## 2023-05-25 -|paper|code| -|---|---| -|[sliced-wasserstein on symmetric positive definite matrices for m/eeg signals](https://arxiv.org/abs/2303.05798)|[spdsw](https://github.com/clbonet/spdsw)| -|[slicertms: interactive real-time visualization of transcranial magnetic stimulation using augmented reality and deep learning](https://arxiv.org/abs/2305.06459)|[SlicerTMS](https://github.com/lorifranke/SlicerTMS)| -|[stochastic unrolled federated learning](https://arxiv.org/abs/2305.15371)|[fed-surf](https://github.com/smrhadou/fed-surf)| -|[infoshape: task-based neural data shaping via mutual information](https://arxiv.org/abs/2210.15034)|[infoshape](https://github.com/billywu1029/infoshape)| -|[directed message passing based on attention for prediction of molecular properties](https://arxiv.org/abs/2305.14819)|[d-gats](https://github.com/gongchen-1995/d-gats)| -|[selection for short-term empowerment accelerates the evolution of homeostatic neural cellular automata](https://arxiv.org/abs/2305.15220)|[empowered-nca-ii](https://github.com/caitlingrasso/empowered-nca-ii)| +|date|paper|code| +|---|---|---| +|2305.06459|[slicertms: interactive real-time visualization of transcranial magnetic stimulation using augmented reality and deep learning](https://arxiv.org/abs/2305.06459)|[SlicerTMS](https://github.com/lorifranke/SlicerTMS)| +|2305.15371|[stochastic unrolled federated learning](https://arxiv.org/abs/2305.15371)|[fed-surf](https://github.com/smrhadou/fed-surf)| +|2305.14819|[directed message passing based on attention for prediction of molecular properties](https://arxiv.org/abs/2305.14819)|[d-gats](https://github.com/gongchen-1995/d-gats)| +|2305.15220|[selection for short-term empowerment accelerates the evolution of homeostatic neural cellular automata](https://arxiv.org/abs/2305.15220)|[empowered-nca-ii](https://github.com/caitlingrasso/empowered-nca-ii)| ## 2023-05-24 -|paper|code| -|---|---| -|[extending conformal prediction to hidden markov models with exact validity via de finetti's theorem for markov chains](https://arxiv.org/abs/2210.02271)|[cp_hmm](https://github.com/complexinfo/cp_hmm)| -|[cooperative channel capacity learning](https://arxiv.org/abs/2305.13493)|[CORTICAL](https://github.com/tonellolab/CORTICAL)| -|[temporally causal discovery tests for discrete time series and neural spike trains](https://arxiv.org/abs/2305.14131)|[github_temporal_causality](https://github.com/andreas947/github_temporal_causality)| +|date|paper|code| +|---|---|---| +|2305.13493|[cooperative channel capacity learning](https://arxiv.org/abs/2305.13493)|[CORTICAL](https://github.com/tonellolab/CORTICAL)| +|2305.14131|[temporally causal discovery tests for discrete time series and neural spike trains](https://arxiv.org/abs/2305.14131)|[github_temporal_causality](https://github.com/andreas947/github_temporal_causality)| ## 2023-05-23 -|paper|code| -|---|---| -|[gradient-based learning of discrete structured measurement operators for signal recovery](https://arxiv.org/abs/2202.03391)|[glodismo](https://github.com/josauder/glodismo)| -|[machine learning-based csi feedback with variable length in fdd massive mimo](https://arxiv.org/abs/2204.04723)|[ml-based-csi-feedback](https://github.com/matteonerini/ml-based-csi-feedback)| -|[synthetic ecg signal generation using probabilistic diffusion models](https://arxiv.org/abs/2303.02475)|[augmentation-of-ecg-training-dataset-with-cgan](https://github.com/mah533/augmentation-of-ecg-training-dataset-with-cgan)| -|[appliance detection using very low-frequency smart meter time series](https://arxiv.org/abs/2305.10352)|[ApplianceDetectionBenchmark](https://github.com/adrienpetralia/ApplianceDetectionBenchmark)| -|[thraws: a novel dataset for thermal hotspots detection in raw sentinel-2 data](https://arxiv.org/abs/2305.11891)|[pyraws](https://github.com/esa-philab/pyraws)| -|[deepjscc-l++: robust and bandwidth-adaptive wireless image transmission](https://arxiv.org/abs/2305.13161)|[deepjscc-lplusplus](https://github.com/aprilbian/deepjscc-lplusplus)| -|[classification utility, fairness, and compactness via tunable information bottleneck and r\'enyi measures](https://arxiv.org/abs/2206.10043)|[rfib-code](https://github.com/agronowski/rfib-code)| -|[commodity-specific triads in the dutch inter-industry production network](https://arxiv.org/abs/2305.12179)|[numetris](https://github.com/marsmdk/numetris)| -|[evaluating prompt-based question answering for object prediction in the open research knowledge graph](https://arxiv.org/abs/2305.12900)|[thesis_work](https://github.com/as18cia/thesis_work)| +|date|paper|code| +|---|---|---| +|2305.10352|[appliance detection using very low-frequency smart meter time series](https://arxiv.org/abs/2305.10352)|[ApplianceDetectionBenchmark](https://github.com/adrienpetralia/ApplianceDetectionBenchmark)| +|2305.11891|[thraws: a novel dataset for thermal hotspots detection in raw sentinel-2 data](https://arxiv.org/abs/2305.11891)|[pyraws](https://github.com/esa-philab/pyraws)| +|2305.13161|[deepjscc-l++: robust and bandwidth-adaptive wireless image transmission](https://arxiv.org/abs/2305.13161)|[deepjscc-lplusplus](https://github.com/aprilbian/deepjscc-lplusplus)| +|2305.12179|[commodity-specific triads in the dutch inter-industry production network](https://arxiv.org/abs/2305.12179)|[numetris](https://github.com/marsmdk/numetris)| +|2305.12900|[evaluating prompt-based question answering for object prediction in the open research knowledge graph](https://arxiv.org/abs/2305.12900)|[thesis_work](https://github.com/as18cia/thesis_work)| ## 2023-05-22 -|paper|code| -|---|---| -|[joint distribution of distance and angles in finite wireless networks](https://arxiv.org/abs/2203.13510)|[joint_pdf_dist_angles](https://github.com/franmarve/joint_pdf_dist_angles)| -|[grid-free harmonic retrieval and model order selection using deep convolutional neural networks](https://arxiv.org/abs/2211.04846)|[deepest-demo](https://huggingface.co/spaces/EMS-TU-Ilmenau/deepest-demo)| -|[parameter-efficient learning for text-to-speech accent adaptation](https://arxiv.org/abs/2305.11320)|[PEL-TTS](https://github.com/TTS-Research/PEL-TTS)| -|[marginalized beam search algorithms for hierarchical hmms](https://arxiv.org/abs/2305.11752)|[mbs](https://github.com/chunxxc/mbs)| +|date|paper|code| +|---|---|---| +|2305.11320|[parameter-efficient learning for text-to-speech accent adaptation](https://arxiv.org/abs/2305.11320)|[PEL-TTS](https://github.com/TTS-Research/PEL-TTS)| +|2305.11752|[marginalized beam search algorithms for hierarchical hmms](https://arxiv.org/abs/2305.11752)|[mbs](https://github.com/chunxxc/mbs)| ## 2023-05-19 -|paper|code| -|---|---| -|[neural network entropy (nneten): entropy-based eeg signal and chaotic time series classification, python package for nneten calculation](https://arxiv.org/abs/2303.17995)|[nneten](https://github.com/izotov93/nneten)| -|[nonparametric two-sample testing by betting](https://arxiv.org/abs/2112.09162)|[nonparametric-testing-by-betting](https://github.com/sshekhar17/nonparametric-testing-by-betting)| -|[a measure of the complexity of neural representations based on partial information decomposition](https://arxiv.org/abs/2209.10438)|[nninfo](https://github.com/priesemann-group/nninfo)| -|[synchronizing many filesystems in near linear time](https://arxiv.org/abs/2302.09666)|[algebraic-reconciler](https://github.com/csirmaz/algebraic-reconciler)| -|[deir: efficient and robust exploration through discriminative-model-based episodic intrinsic rewards](https://arxiv.org/abs/2304.10770)|[deir](https://github.com/swan-utokyo/deir)| +|date|paper|code| +|---|---|---| ## 2023-05-18 -|paper|code| -|---|---| -|[pmnet: robust pathloss map prediction via supervised learning](https://arxiv.org/abs/2211.10527)|[pmnet](https://github.com/abman23/pmnet)| -|[outage performance and novel loss function for an ml-assisted resource allocation: an exact analytical framework](https://arxiv.org/abs/2305.09739)|[greedy-resource-allocation-outage-classification](https://github.com/ml4comms/greedy-resource-allocation-outage-classification)| -|[a modular and high-resolution time-frequency post-processing technique](https://arxiv.org/abs/2305.10009)|[Time-frequency-analysis](https://github.com/jsshen1/Time-frequency-analysis)| -|[algorithms for boolean matrix factorization using integer programming](https://arxiv.org/abs/2305.10185)|[booleanmf](https://gitlab.com/ngillis/booleanmf)| -|[random edge coding: one-shot bits-back coding of large labeled graphs](https://arxiv.org/abs/2305.09705)|[random-edge-coding](https://github.com/dsevero/random-edge-coding)| +|date|paper|code| +|---|---|---| +|2305.09739|[outage performance and novel loss function for an ml-assisted resource allocation: an exact analytical framework](https://arxiv.org/abs/2305.09739)|[greedy-resource-allocation-outage-classification](https://github.com/ml4comms/greedy-resource-allocation-outage-classification)| +|2305.10009|[a modular and high-resolution time-frequency post-processing technique](https://arxiv.org/abs/2305.10009)|[Time-frequency-analysis](https://github.com/jsshen1/Time-frequency-analysis)| +|2305.10185|[algorithms for boolean matrix factorization using integer programming](https://arxiv.org/abs/2305.10185)|[booleanmf](https://gitlab.com/ngillis/booleanmf)| +|2305.09705|[random edge coding: one-shot bits-back coding of large labeled graphs](https://arxiv.org/abs/2305.09705)|[random-edge-coding](https://github.com/dsevero/random-edge-coding)| ## 2023-05-17 -|paper|code| -|---|---| -|[on the convergence of inexact gradient descent with controlled synchronization steps](https://arxiv.org/abs/2208.07797)|[inexact-gradient-descent](https://github.com/Sandushan/inexact-gradient-descent)| -|[policy evaluation in decentralized pomdps with belief sharing](https://arxiv.org/abs/2302.04151)|[decpomdp_policy_evaluation_w-belief_sharing](https://github.com/asl-epfl/decpomdp_policy_evaluation_w-belief_sharing)| -|[guaranteed dynamic scheduling of ultra-reliable low-latency traffic via conformal prediction](https://arxiv.org/abs/2302.07675)|[online_cp_urllc](https://github.com/kclip/online_cp_urllc)| -|[phase retrieval via model-free power flow jacobian recovery](https://arxiv.org/abs/2305.09661)|[powerphaseretrieval.jl](https://github.com/samtalki/powerphaseretrieval.jl)| +|date|paper|code| +|---|---|---| +|2305.09661|[phase retrieval via model-free power flow jacobian recovery](https://arxiv.org/abs/2305.09661)|[powerphaseretrieval.jl](https://github.com/samtalki/powerphaseretrieval.jl)| ## 2023-05-16 -|paper|code| -|---|---| -|[locality sensitive hashing via mechanical behavior](https://arxiv.org/abs/2304.06505)|[mechhs](https://github.com/elejeune11/mechhs)| -|[slicertms: interactive real-time visualization of transcranial magnetic stimulation using augmented reality and deep learning](https://arxiv.org/abs/2305.06459)|[SlicerTMS](https://github.com/lorifranke/SlicerTMS)| -|[accelerated algorithms for nonlinear matrix decomposition with the relu function](https://arxiv.org/abs/2305.08687)|[relu-nmd](https://gitlab.com/ngillis/relu-nmd)| -|[adjacent-bits-swapped polar codes: a new code construction to speed up polarization](https://arxiv.org/abs/2202.04454)|[abs-polar](https://github.com/plumjelly/abs-polar)| -|[detection and mitigation of byzantine attacks in distributed training](https://arxiv.org/abs/2208.08085)|[aspis](https://github.com/kkonstantinidis/aspis)| +|date|paper|code| +|---|---|---| +|2305.06459|[slicertms: interactive real-time visualization of transcranial magnetic stimulation using augmented reality and deep learning](https://arxiv.org/abs/2305.06459)|[SlicerTMS](https://github.com/lorifranke/SlicerTMS)| +|2305.08687|[accelerated algorithms for nonlinear matrix decomposition with the relu function](https://arxiv.org/abs/2305.08687)|[relu-nmd](https://gitlab.com/ngillis/relu-nmd)| ## 2023-05-15 -|paper|code| -|---|---| -|[transformers in time series: a survey](https://arxiv.org/abs/2202.07125)|[time-series-transformers-review](https://github.com/qingsongedu/time-series-transformers-review)| -|[hierarchical bayesian modelling for knowledge transfer across engineering fleets via multitask learning](https://arxiv.org/abs/2204.12404)|[engineeringpatternrecognition](https://github.com/labull/engineeringpatternrecognition)| -|[over-the-air computation with multiple receivers: a space-time approach](https://arxiv.org/abs/2208.11751)|[space-time-ota](https://github.com/ymalitsky/space-time-ota)| -|[active sensing for two-sided beam alignment and reflection design using ping-pong pilots](https://arxiv.org/abs/2305.07130)|[active-sensing-beam-alignment](https://github.com/taojiang-github/active-sensing-beam-alignment)| -|[improved upper and lower bounds on the capacity of the binary deletion channel](https://arxiv.org/abs/2305.07156)|[bdc_upper_bounds](https://github.com/ittai-rubinstein/bdc_upper_bounds)| -|[learning to code on graphs for topological interference management](https://arxiv.org/abs/2305.07186)|[learning-to-code-on-graphs](https://github.com/zhiweishan/learning-to-code-on-graphs)| -|[adaptive and flexible model-based ai for deep receivers in dynamic channels](https://arxiv.org/abs/2305.07309)|[facilitating-adaptation-deep-receivers](https://github.com/tomerraviv95/facilitating-adaptation-deep-receivers)| +|date|paper|code| +|---|---|---| +|2305.07130|[active sensing for two-sided beam alignment and reflection design using ping-pong pilots](https://arxiv.org/abs/2305.07130)|[active-sensing-beam-alignment](https://github.com/taojiang-github/active-sensing-beam-alignment)| +|2305.07156|[improved upper and lower bounds on the capacity of the binary deletion channel](https://arxiv.org/abs/2305.07156)|[bdc_upper_bounds](https://github.com/ittai-rubinstein/bdc_upper_bounds)| +|2305.07186|[learning to code on graphs for topological interference management](https://arxiv.org/abs/2305.07186)|[learning-to-code-on-graphs](https://github.com/zhiweishan/learning-to-code-on-graphs)| +|2305.07309|[adaptive and flexible model-based ai for deep receivers in dynamic channels](https://arxiv.org/abs/2305.07309)|[facilitating-adaptation-deep-receivers](https://github.com/tomerraviv95/facilitating-adaptation-deep-receivers)| ## 2023-05-12 -|paper|code| -|---|---| -|[resource allocation for text semantic communications](https://arxiv.org/abs/2201.06023)|[semantic-resource-allocation-S-SE-](https://github.com/YL12345/semantic-resource-allocation-S-SE-)| -|[a unified algorithmic framework for distributed adaptive signal and feature fusion problems -- part i: algorithm derivation](https://arxiv.org/abs/2208.08867)|[DASF_toolbox](https://github.com/AlexanderBertrandLab/DASF_toolbox)| -|[a unified algorithmic framework for distributed adaptive signal and feature fusion problems -- part ii: convergence properties](https://arxiv.org/abs/2208.09088)|[DASF_toolbox](https://github.com/AlexanderBertrandLab/DASF_toolbox)| +|date|paper|code| +|---|---|---| ## 2023-05-11 -|paper|code| -|---|---| -|[phaseaug: a differentiable augmentation for speech synthesis to simulate one-to-many mapping](https://arxiv.org/abs/2211.04610)|[phaseaug](https://github.com/mindslab-ai/phaseaug)| -|[spiking neural networks in the alexiewicz topology: a new perspective on analysis and error bounds](https://arxiv.org/abs/2305.05772)|[alexsnn](https://github.com/lunglmayrmoser/alexsnn)| +|date|paper|code| +|---|---|---| +|2305.05772|[spiking neural networks in the alexiewicz topology: a new perspective on analysis and error bounds](https://arxiv.org/abs/2305.05772)|[alexsnn](https://github.com/lunglmayrmoser/alexsnn)| ## 2023-05-10 -|paper|code| -|---|---| -|[robust information bottleneck for task-oriented communication with digital modulation](https://arxiv.org/abs/2209.10382)|[Discrete-TaskOriented-JSCC](https://github.com/SongjieXie/Discrete-TaskOriented-JSCC)| -|[gaussian process deconvolution](https://arxiv.org/abs/2305.04871)|[gaussian-process-deconvolution](https://github.com/games-uchile/gaussian-process-deconvolution)| -|[bistatic mimo radar sensing of specularly reflecting surfaces for wireless power transfer](https://arxiv.org/abs/2305.05002)|[bistatic-mimo-radar-sensing](https://gitlab.com/baenshy/bistatic-mimo-radar-sensing)| -|[3dinvnet: a deep learning-based 3d ground-penetrating radar data inversion](https://arxiv.org/abs/2305.05425)|[3dinvnet](https://github.com/qiqi-dai/3dinvnet)| -|[randomized and exchangeable improvements of markov's, chebyshev's and chernoff's inequalities](https://arxiv.org/abs/2304.02611)|[randomized-markov](https://github.com/tmanole/randomized-markov)| +|date|paper|code| +|---|---|---| +|2305.04871|[gaussian process deconvolution](https://arxiv.org/abs/2305.04871)|[gaussian-process-deconvolution](https://github.com/games-uchile/gaussian-process-deconvolution)| +|2305.05002|[bistatic mimo radar sensing of specularly reflecting surfaces for wireless power transfer](https://arxiv.org/abs/2305.05002)|[bistatic-mimo-radar-sensing](https://gitlab.com/baenshy/bistatic-mimo-radar-sensing)| +|2305.05425|[3dinvnet: a deep learning-based 3d ground-penetrating radar data inversion](https://arxiv.org/abs/2305.05425)|[3dinvnet](https://github.com/qiqi-dai/3dinvnet)| ## 2023-05-09 -|paper|code| -|---|---| -|[simple pooling front-ends for efficient audio classification](https://arxiv.org/abs/2210.00943)|[simpfs](https://github.com/liuxubo717/simpfs)| -|[selective noise suppression using random svpwm to shape the voltage spectrum](https://arxiv.org/abs/2302.08053)|[SNS-in-random-SVPWM](https://github.com/IoaJianWen/SNS-in-random-SVPWM)| -|[multi-scale transformer-based network for emotion recognition from multi physiological signals](https://arxiv.org/abs/2305.00769)|[EPiC-2023-ACII](https://github.com/vsl-team/EPiC-2023-ACII)| -|[unrolled architectures for high-throughput encoding of multi-kernel polar codes](https://arxiv.org/abs/2305.04257)|[polar-encoder-compiler](https://github.com/hosseinrezaeii91/polar-encoder-compiler)| +|date|paper|code| +|---|---|---| +|2305.00769|[multi-scale transformer-based network for emotion recognition from multi physiological signals](https://arxiv.org/abs/2305.00769)|[EPiC-2023-ACII](https://github.com/vsl-team/EPiC-2023-ACII)| +|2305.04257|[unrolled architectures for high-throughput encoding of multi-kernel polar codes](https://arxiv.org/abs/2305.04257)|[polar-encoder-compiler](https://github.com/hosseinrezaeii91/polar-encoder-compiler)| ## 2023-05-08 -|paper|code| -|---|---| -|[slurp! spectroscopy of liquids using robot pre-touch sensing](https://arxiv.org/abs/2210.04941)|[slurp_grasping](https://github.com/river-lab/slurp_grasping)| -|[model-free reinforcement learning of semantic communication by stochastic policy gradient](https://arxiv.org/abs/2305.03571)|[sinfony](https://github.com/ant-uni-bremen/sinfony)| -|[a thru-free multiline calibration](https://arxiv.org/abs/2305.03597)|[thru-free-multiline-calibration](https://github.com/ZiadHatab/thru-free-multiline-calibration)| +|date|paper|code| +|---|---|---| +|2305.03571|[model-free reinforcement learning of semantic communication by stochastic policy gradient](https://arxiv.org/abs/2305.03571)|[sinfony](https://github.com/ant-uni-bremen/sinfony)| +|2305.03597|[a thru-free multiline calibration](https://arxiv.org/abs/2305.03597)|[thru-free-multiline-calibration](https://github.com/ZiadHatab/thru-free-multiline-calibration)| ## 2023-05-05 -|paper|code| -|---|---| -|[conditional and residual methods in scalable coding for humans and machines](https://arxiv.org/abs/2305.02562)|[research](https://github.com/adeandrade/research)| +|date|paper|code| +|---|---|---| +|2305.02562|[conditional and residual methods in scalable coding for humans and machines](https://arxiv.org/abs/2305.02562)|[research](https://github.com/adeandrade/research)| ## 2023-05-03 -|paper|code| -|---|---| -|[recurrences reveal shared causal drivers of complex time series](https://arxiv.org/abs/2301.13516)|[shrec](https://github.com/williamgilpin/shrec)| +|date|paper|code| +|---|---|---| ## 2023-05-02 -|paper|code| -|---|---| -|[latent signal models: learning compact representations of signal evolution for improved time-resolved, multi-contrast mri](https://arxiv.org/abs/2208.13003)|[latent_signal_models_mrm_2022](https://github.com/yaminarefeen/latent_signal_models_mrm_2022)| -|[modeling multivariate biosignals with graph neural networks and structured state space models](https://arxiv.org/abs/2211.11176)|[graphs4mer](https://github.com/tsy935/graphs4mer)| -|[point cloud forecasting as a proxy for 4d occupancy forecasting](https://arxiv.org/abs/2302.13130)|[4d-occ-forecasting](https://github.com/tarashakhurana/4d-occ-forecasting)| -|[leveraging label non-uniformity for node classification in graph neural networks](https://arxiv.org/abs/2305.00139)|[label-non-uniformity-gnn](https://github.com/amblee0306/label-non-uniformity-gnn)| -|[non-linear phase-retrieval algorithms for x-ray propagation-based phase-contrast tomography](https://arxiv.org/abs/2305.00334)|[phasetorch](https://github.com/phasetorch/phasetorch)| -|[multi-scale transformer-based network for emotion recognition from multi physiological signals](https://arxiv.org/abs/2305.00769)|[EPiC-2023-ACII](https://github.com/vsl-team/EPiC-2023-ACII)| +|date|paper|code| +|---|---|---| +|2305.00139|[leveraging label non-uniformity for node classification in graph neural networks](https://arxiv.org/abs/2305.00139)|[label-non-uniformity-gnn](https://github.com/amblee0306/label-non-uniformity-gnn)| +|2305.00334|[non-linear phase-retrieval algorithms for x-ray propagation-based phase-contrast tomography](https://arxiv.org/abs/2305.00334)|[phasetorch](https://github.com/phasetorch/phasetorch)| +|2305.00769|[multi-scale transformer-based network for emotion recognition from multi physiological signals](https://arxiv.org/abs/2305.00769)|[EPiC-2023-ACII](https://github.com/vsl-team/EPiC-2023-ACII)| ## 2023-05-01 -|paper|code| -|---|---| -|[clnet: complex input lightweight neural network designed for massive mimo csi feedback](https://arxiv.org/abs/2102.07507)|[CLNet](https://github.com/SIJIEJI/CLNet)| -|[scatterformer: locally-invariant scattering transformer for patient-independent multispectral detection of epileptiform discharges](https://arxiv.org/abs/2304.14919)|[scatterformer](https://github.com/albertcheng19/scatterformer)| -|[information theory inspired pattern analysis for time-series data](https://arxiv.org/abs/2302.11654)|[entropypipeline](https://github.com/yushan-huang/entropypipeline)| -|[deepmad: mathematical architecture design for deep convolutional neural network](https://arxiv.org/abs/2303.02165)|[lightweight-neural-architecture-search](https://github.com/alibaba/lightweight-neural-architecture-search)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/06.md b/archives/2023/06.md index fcffe6aa..c21f78c9 100644 --- a/archives/2023/06.md +++ b/archives/2023/06.md @@ -1,182 +1,128 @@ # June 2023 Archive ## 2023-06-30 -|paper|code| -|---|---| -|[noise detection with spectator qubits and quantum feature engineering](https://arxiv.org/abs/2103.13018)|[QFEND](https://github.com/akramyoussry/QFEND)| -|[assessing the performance of 1d-convolution neural networks to predict concentration of mixture components from raman spectra](https://arxiv.org/abs/2306.16621)|[ramix](https://github.com/dexterantonio/ramix)| -|[accurate pet reconstruction from reduced set of measurements based on gmm](https://arxiv.org/abs/2306.17028)|[accurate-pet-reconstruction-from-reduced-set-of-measurements-based-on-gmm](https://github.com/tm2005/accurate-pet-reconstruction-from-reduced-set-of-measurements-based-on-gmm)| -|[tokenization and the noiseless channel](https://arxiv.org/abs/2306.16842)|[tokenization-scorer](https://github.com/zouharvi/tokenization-scorer)| +|date|paper|code| +|---|---|---| +|2306.16621|[assessing the performance of 1d-convolution neural networks to predict concentration of mixture components from raman spectra](https://arxiv.org/abs/2306.16621)|[ramix](https://github.com/dexterantonio/ramix)| +|2306.17028|[accurate pet reconstruction from reduced set of measurements based on gmm](https://arxiv.org/abs/2306.17028)|[accurate-pet-reconstruction-from-reduced-set-of-measurements-based-on-gmm](https://github.com/tm2005/accurate-pet-reconstruction-from-reduced-set-of-measurements-based-on-gmm)| +|2306.16842|[tokenization and the noiseless channel](https://arxiv.org/abs/2306.16842)|[tokenization-scorer](https://github.com/zouharvi/tokenization-scorer)| ## 2023-06-29 -|paper|code| -|---|---| -|[ai-generated incentive mechanism and full-duplex semantic communications for information sharing](https://arxiv.org/abs/2303.01896)|[semsharing](https://github.com/hongyangdu/semsharing)| -|[ecg-qa: a comprehensive question answering dataset combined with electrocardiogram](https://arxiv.org/abs/2306.15681)|[ecg-qa](https://github.com/jwoo5/ecg-qa)| -|[understanding a version of multivariate symmetric uncertainty to assist in feature selection](https://arxiv.org/abs/1709.08730)|[package=msu](https://cran.r-project.org/package=msu)| -|[on graph uncertainty principle and eigenvector delocalization](https://arxiv.org/abs/2306.15810)|[uncertainty-delocalization](https://github.com/erebrova/uncertainty-delocalization)| -|[on information captured by neural networks: connections with memorization and generalization](https://arxiv.org/abs/2306.15918)|[aws-cv-unique-information](https://github.com/awslabs/aws-cv-unique-information)| +|date|paper|code| +|---|---|---| +|2306.15681|[ecg-qa: a comprehensive question answering dataset combined with electrocardiogram](https://arxiv.org/abs/2306.15681)|[ecg-qa](https://github.com/jwoo5/ecg-qa)| +|2306.15810|[on graph uncertainty principle and eigenvector delocalization](https://arxiv.org/abs/2306.15810)|[uncertainty-delocalization](https://github.com/erebrova/uncertainty-delocalization)| +|2306.15918|[on information captured by neural networks: connections with memorization and generalization](https://arxiv.org/abs/2306.15918)|[aws-cv-unique-information](https://github.com/awslabs/aws-cv-unique-information)| ## 2023-06-28 -|paper|code| -|---|---| -|[sinr: deconvolving circular sas images using implicit neural representations](https://arxiv.org/abs/2204.10428)|[csas_deconvolution_inr](https://github.com/awreed/csas_deconvolution_inr)| -|[data-driven blind synchronization and interference rejection for digital communication signals](https://arxiv.org/abs/2209.04871)|[scss_sync](https://github.com/rfchallenge/scss_sync)| -|[on neural architectures for deep learning-based source separation of co-channel ofdm signals](https://arxiv.org/abs/2303.06438)|[scss_ofdmarchitecture](https://github.com/rfchallenge/scss_ofdmarchitecture)| -|[statistical component separation for targeted signal recovery in noisy mixtures](https://arxiv.org/abs/2306.15012)|[stat_comp_sep](https://github.com/bregaldo/stat_comp_sep)| -|[llmzip: lossless text compression using large language models](https://arxiv.org/abs/2306.04050)|[LLMzip](https://github.com/vcskaushik/LLMzip)| +|date|paper|code| +|---|---|---| +|2306.15012|[statistical component separation for targeted signal recovery in noisy mixtures](https://arxiv.org/abs/2306.15012)|[stat_comp_sep](https://github.com/bregaldo/stat_comp_sep)| +|2306.04050|[llmzip: lossless text compression using large language models](https://arxiv.org/abs/2306.04050)|[LLMzip](https://github.com/vcskaushik/LLMzip)| ## 2023-06-27 -|paper|code| -|---|---| -|[openfwi: large-scale multi-structural benchmark datasets for seismic full waveform inversion](https://arxiv.org/abs/2111.02926)|[openfwi](https://github.com/lanl/openfwi)| -|[binary spatial random field reconstruction from non-gaussian inhomogeneous time-series observations](https://arxiv.org/abs/2204.03343)|[WarpedGaussianProcesses](https://github.com/ShunanSheng/WarpedGaussianProcesses)| -|[robust spatiotemporal traffic forecasting with reinforced dynamic adversarial training](https://arxiv.org/abs/2306.14126)|[rdat](https://github.com/usail-hkust/rdat)| -|[cst-yolo: a novel method for blood cell detection based on improved yolov7 and cnn-swin transformer](https://arxiv.org/abs/2306.14590)|[CST-YOLO](https://github.com/mkang315/CST-YOLO)| -|[folded polynomial codes for coded distributed $aa^\top$-type matrix multiplication](https://arxiv.org/abs/2211.15267)|[foldedpolynomialcodes](https://github.com/shinez9/foldedpolynomialcodes)| -|[domain adaptive decision trees: implications for accuracy and fairness](https://arxiv.org/abs/2302.13846)|[domain-adaptive-trees](https://github.com/nobias-project/domain-adaptive-trees)| -|[compression with bayesian implicit neural representations](https://arxiv.org/abs/2305.19185)|[combiner](https://github.com/cambridge-mlg/combiner)| -|[recoil: parallel rans decoding with decoder-adaptive scalability](https://arxiv.org/abs/2306.12141)|[recoil](https://github.com/lin-toto/recoil)| +|date|paper|code| +|---|---|---| +|2306.14126|[robust spatiotemporal traffic forecasting with reinforced dynamic adversarial training](https://arxiv.org/abs/2306.14126)|[rdat](https://github.com/usail-hkust/rdat)| +|2306.14590|[cst-yolo: a novel method for blood cell detection based on improved yolov7 and cnn-swin transformer](https://arxiv.org/abs/2306.14590)|[CST-YOLO](https://github.com/mkang315/CST-YOLO)| +|2306.12141|[recoil: parallel rans decoding with decoder-adaptive scalability](https://arxiv.org/abs/2306.12141)|[recoil](https://github.com/lin-toto/recoil)| ## 2023-06-26 -|paper|code| -|---|---| -|[multi-task learning for radar signal characterisation](https://arxiv.org/abs/2306.13105)|[radchar](https://github.com/abcxyzi/radchar)| -|[necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables](https://arxiv.org/abs/2102.10324)|[tigramite](https://github.com/jakobrunge/tigramite)| +|date|paper|code| +|---|---|---| +|2306.13105|[multi-task learning for radar signal characterisation](https://arxiv.org/abs/2306.13105)|[radchar](https://github.com/abcxyzi/radchar)| ## 2023-06-23 -|paper|code| -|---|---| -|[signal inpainting from fourier magnitudes](https://arxiv.org/abs/2210.15951)|[inpainting-fourier](https://github.com/louis-bahrman/inpainting-fourier)| +|date|paper|code| +|---|---|---| ## 2023-06-22 -|paper|code| -|---|---| -|[space-time design for deep joint source channel coding of images over mimo channels](https://arxiv.org/abs/2210.16985)|[st_jscc](https://github.com/aprilbian/st_jscc)| -|[high throughput open-source implementation of wi-fi 6 and wimax ldpc encoder and decoder](https://arxiv.org/abs/2306.12063)|[yaldpc](https://github.com/talenik/yaldpc)| +|date|paper|code| +|---|---|---| +|2306.12063|[high throughput open-source implementation of wi-fi 6 and wimax ldpc encoder and decoder](https://arxiv.org/abs/2306.12063)|[yaldpc](https://github.com/talenik/yaldpc)| ## 2023-06-21 -|paper|code| -|---|---| -|[distributed set-based observers using diffusion strategies](https://arxiv.org/abs/2003.10347)|[distributed-set-based-observers-using-diffusion-strategies](https://github.com/aalanwar/distributed-set-based-observers-using-diffusion-strategies)| -|[scale dependencies and self-similar models with wavelet scattering spectra](https://arxiv.org/abs/2204.10177)|[scattering_spectra](https://github.com/rudymorel/scattering_spectra)| -|[decomposed linear dynamical systems (dlds) for learning the latent components of neural dynamics](https://arxiv.org/abs/2206.02972)|[dLDS-Discrete-Python-Model](https://github.com/dLDS-Decomposed-Linear-Dynamics/dLDS-Discrete-Python-Model)| -|[data-driven denoising of stationary accelerometer signals](https://arxiv.org/abs/2206.05937)|[MEMS-IMU-Denoising](https://github.com/ansfl/MEMS-IMU-Denoising)| -|[a neural-network framework for the design of individualised hearing-loss compensation](https://arxiv.org/abs/2207.07091)|[dnn-ha](https://github.com/hearingtechnology/dnn-ha)| -|[tfn: an interpretable neural network with time-frequency transform embedded for intelligent fault diagnosis](https://arxiv.org/abs/2209.01992)|[tfn](https://github.com/chenqian0618/tfn)| -|[bayesian optimization of sampling densities in mri](https://arxiv.org/abs/2209.07170)|[bindings-nufft-pytorch](https://github.com/albangossard/bindings-nufft-pytorch)| -|[short-length ssvep data extension by a novel generative adversarial networks based framework](https://arxiv.org/abs/2301.05599)|[tegan](https://github.com/yudongpan/tegan)| -|[deep comparisons of neural networks from the eegnet family](https://arxiv.org/abs/2302.08797)|[bionic_apps](https://github.com/kolcs/bionic_apps)| -|[lora backscatter communications: temporal, spectral, and error performance analysis](https://arxiv.org/abs/2306.02323)|[lora-backscatter-performance-analysis](https://github.com/slingovie/lora-backscatter-performance-analysis)| -|[multiwave: multiresolution deep architectures through wavelet decomposition for multivariate time series prediction](https://arxiv.org/abs/2306.10164)|[multiwave](https://github.com/information-fusion-lab-umass/multiwave)| -|[matnet: multi-level fusion and self-attention transformer-based model for multivariate multi-step day-ahead pv generation forecasting](https://arxiv.org/abs/2306.10356)|[matnet](https://github.com/cosbidev/matnet)| -|[duta-vc: a duration-aware typical-to-atypical voice conversion approach with diffusion probabilistic model](https://arxiv.org/abs/2306.10588)|[duta-vc](https://github.com/wanghelin1997/duta-vc)| -|[to fold or not to fold: graph regularized tensor train for visual data completion](https://arxiv.org/abs/2306.11123)|[graphttc](https://github.com/xumaomao94/graphttc)| -|[fdnet: focal decomposed network for efficient, robust and practical time series forecasting](https://arxiv.org/abs/2306.10703)|[fdnet](https://github.com/origamisl/fdnet)| -|[beyond normal: on the evaluation of mutual information estimators](https://arxiv.org/abs/2306.11078)|[bmi](https://github.com/cbg-ethz/bmi)| +|date|paper|code| +|---|---|---| +|2306.02323|[lora backscatter communications: temporal, spectral, and error performance analysis](https://arxiv.org/abs/2306.02323)|[lora-backscatter-performance-analysis](https://github.com/slingovie/lora-backscatter-performance-analysis)| +|2306.10164|[multiwave: multiresolution deep architectures through wavelet decomposition for multivariate time series prediction](https://arxiv.org/abs/2306.10164)|[multiwave](https://github.com/information-fusion-lab-umass/multiwave)| +|2306.10356|[matnet: multi-level fusion and self-attention transformer-based model for multivariate multi-step day-ahead pv generation forecasting](https://arxiv.org/abs/2306.10356)|[matnet](https://github.com/cosbidev/matnet)| +|2306.10588|[duta-vc: a duration-aware typical-to-atypical voice conversion approach with diffusion probabilistic model](https://arxiv.org/abs/2306.10588)|[duta-vc](https://github.com/wanghelin1997/duta-vc)| +|2306.11123|[to fold or not to fold: graph regularized tensor train for visual data completion](https://arxiv.org/abs/2306.11123)|[graphttc](https://github.com/xumaomao94/graphttc)| +|2306.10703|[fdnet: focal decomposed network for efficient, robust and practical time series forecasting](https://arxiv.org/abs/2306.10703)|[fdnet](https://github.com/origamisl/fdnet)| +|2306.11078|[beyond normal: on the evaluation of mutual information estimators](https://arxiv.org/abs/2306.11078)|[bmi](https://github.com/cbg-ethz/bmi)| ## 2023-06-19 -|paper|code| -|---|---| -|[super-resolution radar imaging with sparse arrays using a deep neural network trained with enhanced virtual data](https://arxiv.org/abs/2306.09839)|[sparse-array-radar-imaging](https://github.com/christianschuessler/sparse-array-radar-imaging)| +|date|paper|code| +|---|---|---| +|2306.09839|[super-resolution radar imaging with sparse arrays using a deep neural network trained with enhanced virtual data](https://arxiv.org/abs/2306.09839)|[sparse-array-radar-imaging](https://github.com/christianschuessler/sparse-array-radar-imaging)| ## 2023-06-16 -|paper|code| -|---|---| -|[hierarchical dirichlet process based gamma mixture modelling for terahertz band wireless communication channels](https://arxiv.org/abs/2205.03812)|[DPGMM-Channel-Modelling](https://github.com/erhankarakoca/DPGMM-Channel-Modelling)| -|[closed-form global optimization of beyond diagonal reconfigurable intelligent surfaces](https://arxiv.org/abs/2211.06117)|[optimization-of-bdris](https://github.com/matteonerini/optimization-of-bdris)| -|[diffusion-based conditional ecg generation with structured state space models](https://arxiv.org/abs/2301.08227)|[sssd-ecg](https://github.com/ai4healthuol/sssd-ecg)| -|[low-complexity steered response power mapping based on low-rank and sparse interpolation](https://arxiv.org/abs/2306.08514)|[lr-sp-int-srp](https://github.com/tdietzen/lr-sp-int-srp)| -|[towards trustworthy seizure onset detection using workflow notes](https://arxiv.org/abs/2306.08728)|[eeg_robustness](https://github.com/khaledsaab/eeg_robustness)| -|[two-way semantic transmission of images without feedback](https://arxiv.org/abs/2306.08903)|[TW-SemanticComm](https://github.com/Kiven-ykw/TW-SemanticComm)| -|[safeguarding data in multimodal ai: a differentially private approach to clip training](https://arxiv.org/abs/2306.08173)|[dpclip](https://github.com/dpclip/dpclip)| +|date|paper|code| +|---|---|---| +|2306.08514|[low-complexity steered response power mapping based on low-rank and sparse interpolation](https://arxiv.org/abs/2306.08514)|[lr-sp-int-srp](https://github.com/tdietzen/lr-sp-int-srp)| +|2306.08728|[towards trustworthy seizure onset detection using workflow notes](https://arxiv.org/abs/2306.08728)|[eeg_robustness](https://github.com/khaledsaab/eeg_robustness)| +|2306.08903|[two-way semantic transmission of images without feedback](https://arxiv.org/abs/2306.08903)|[TW-SemanticComm](https://github.com/Kiven-ykw/TW-SemanticComm)| +|2306.08173|[safeguarding data in multimodal ai: a differentially private approach to clip training](https://arxiv.org/abs/2306.08173)|[dpclip](https://github.com/dpclip/dpclip)| ## 2023-06-14 -|paper|code| -|---|---| -|[semantic information recovery in wireless networks](https://arxiv.org/abs/2204.13366)|[sinfony](https://github.com/ant-uni-bremen/sinfony)| -|[deep demixing: reconstructing the evolution of network epidemics](https://arxiv.org/abs/2306.07938)|[Deep_demixing](https://github.com/gojkoc54/Deep_demixing)| -|[binomial line cox processes: statistical characterization and applications in wireless network analysis](https://arxiv.org/abs/2302.05151)|[blcp](https://github.com/mt19146/blcp)| +|date|paper|code| +|---|---|---| +|2306.07938|[deep demixing: reconstructing the evolution of network epidemics](https://arxiv.org/abs/2306.07938)|[Deep_demixing](https://github.com/gojkoc54/Deep_demixing)| ## 2023-06-13 -|paper|code| -|---|---| -|[weight freezing: a regularization approach for fully connected layers with an application in eeg classification](https://arxiv.org/abs/2306.05775)|[weightfreezing](https://github.com/miaozhengqing/weightfreezing)| -|[bayesian calibration of mems accelerometers](https://arxiv.org/abs/2306.06144)|[bayes_cal_paper](https://github.com/oduerr/bayes_cal_paper)| -|[optimized gradient tracking for decentralized online learning](https://arxiv.org/abs/2306.06375)|[Optimized-Gradient-Tracking](https://github.com/Shivangi-Dubey-Sharma/Optimized-Gradient-Tracking)| -|[ts-moco: time-series momentum contrast for self-supervised physiological representation learning](https://arxiv.org/abs/2306.06522)|[ts-moco](https://github.com/philipph77/ts-moco)| -|[evaluating prompt-based question answering for object prediction in the open research knowledge graph](https://arxiv.org/abs/2305.12900)|[thesis_work](https://github.com/as18cia/thesis_work)| +|date|paper|code| +|---|---|---| +|2306.05775|[weight freezing: a regularization approach for fully connected layers with an application in eeg classification](https://arxiv.org/abs/2306.05775)|[weightfreezing](https://github.com/miaozhengqing/weightfreezing)| +|2306.06144|[bayesian calibration of mems accelerometers](https://arxiv.org/abs/2306.06144)|[bayes_cal_paper](https://github.com/oduerr/bayes_cal_paper)| +|2306.06375|[optimized gradient tracking for decentralized online learning](https://arxiv.org/abs/2306.06375)|[Optimized-Gradient-Tracking](https://github.com/Shivangi-Dubey-Sharma/Optimized-Gradient-Tracking)| +|2306.06522|[ts-moco: time-series momentum contrast for self-supervised physiological representation learning](https://arxiv.org/abs/2306.06522)|[ts-moco](https://github.com/philipph77/ts-moco)| ## 2023-06-12 -|paper|code| -|---|---| -|[hrtf upsampling with a generative adversarial network using a gnomonic equiangular projection](https://arxiv.org/abs/2306.05812)|[hrtf-upsampling-with-a-generative-adversarial-network-using-a-gnomonic-equiangular-projection](https://github.com/ahogg/hrtf-upsampling-with-a-generative-adversarial-network-using-a-gnomonic-equiangular-projection)| -|[correlative information maximization: a biologically plausible approach to supervised deep neural networks without weight symmetry](https://arxiv.org/abs/2306.04810)|[Supervised-CorInfoMax](https://github.com/BariscanBozkurt/Supervised-CorInfoMax)| +|date|paper|code| +|---|---|---| +|2306.05812|[hrtf upsampling with a generative adversarial network using a gnomonic equiangular projection](https://arxiv.org/abs/2306.05812)|[hrtf-upsampling-with-a-generative-adversarial-network-using-a-gnomonic-equiangular-projection](https://github.com/ahogg/hrtf-upsampling-with-a-generative-adversarial-network-using-a-gnomonic-equiangular-projection)| +|2306.04810|[correlative information maximization: a biologically plausible approach to supervised deep neural networks without weight symmetry](https://arxiv.org/abs/2306.04810)|[Supervised-CorInfoMax](https://github.com/BariscanBozkurt/Supervised-CorInfoMax)| ## 2023-06-09 -|paper|code| -|---|---| -|[validation of the reference impedance in multiline calibration with stepped impedance standards](https://arxiv.org/abs/2209.09163)|[verification-multiline-trl-calibration](https://github.com/ZiadHatab/verification-multiline-trl-calibration)| -|[an adaptive and robust deep learning framework for thz ultra-massive mimo channel estimation](https://arxiv.org/abs/2211.15939)|[FPN-OAMP-THz-Channel-Estimation](https://github.com/wyuaq/FPN-OAMP-THz-Channel-Estimation)| -|[toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation](https://arxiv.org/abs/2306.05255)|[drca-mlhm](https://github.com/xzhan96-stf/drca-mlhm)| -|[power allocation algorithms for massive mimo systems with multi-antenna users](https://arxiv.org/abs/2201.08068)|[Power-Allocation-Algorithms-for-Massive-MIMO-Systems-with-Multi-Antenna-Users](https://github.com/eugenbobrov/Power-Allocation-Algorithms-for-Massive-MIMO-Systems-with-Multi-Antenna-Users)| -|[learning to maximize mutual information for dynamic feature selection](https://arxiv.org/abs/2301.00557)|[dynamic-selection](https://github.com/iancovert/dynamic-selection)| -|[generic decoding of restricted errors](https://arxiv.org/abs/2303.08882)|[rest-dec](https://github.com/sebastianbitzer/rest-dec)| +|date|paper|code| +|---|---|---| +|2306.05255|[toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation](https://arxiv.org/abs/2306.05255)|[drca-mlhm](https://github.com/xzhan96-stf/drca-mlhm)| ## 2023-06-08 -|paper|code| -|---|---| -|[one-dimensional deep image prior for curve fitting of s-parameters from electromagnetic solvers](https://arxiv.org/abs/2306.04001)|[curvefitting-dip](https://github.com/sriram-ravula/curvefitting-dip)| -|[model-based deep learning](https://arxiv.org/abs/2306.04469)|[mbdl_book](https://github.com/shlezingerlab/mbdl_book)| -|[a measure of the complexity of neural representations based on partial information decomposition](https://arxiv.org/abs/2209.10438)|[nninfo](https://github.com/priesemann-group/nninfo)| -|[multimodal learning without labeled multimodal data: guarantees and applications](https://arxiv.org/abs/2306.04539)|[pid](https://github.com/pliang279/pid)| +|date|paper|code| +|---|---|---| +|2306.04001|[one-dimensional deep image prior for curve fitting of s-parameters from electromagnetic solvers](https://arxiv.org/abs/2306.04001)|[curvefitting-dip](https://github.com/sriram-ravula/curvefitting-dip)| +|2306.04469|[model-based deep learning](https://arxiv.org/abs/2306.04469)|[mbdl_book](https://github.com/shlezingerlab/mbdl_book)| +|2306.04539|[multimodal learning without labeled multimodal data: guarantees and applications](https://arxiv.org/abs/2306.04539)|[pid](https://github.com/pliang279/pid)| ## 2023-06-07 -|paper|code| -|---|---| -|[lora backscatter communications: temporal, spectral, and error performance analysis](https://arxiv.org/abs/2306.02323)|[lora-backscatter-communications-temperal-spectral-and-error-performance-analysis](https://github.com/slingovie/lora-backscatter-communications-temperal-spectral-and-error-performance-analysis)| -|[under-counted tensor completion with neural incorporation of attributes](https://arxiv.org/abs/2306.03273)|[undercounted-tensor-completion](https://github.com/shahanaibrahimosu/undercounted-tensor-completion)| -|[deep learning from crowdsourced labels: coupled cross-entropy minimization, identifiability, and regularization](https://arxiv.org/abs/2306.03288)|[end-to-end-crowdsourcing](https://github.com/shahanaibrahimosu/end-to-end-crowdsourcing)| -|[criteria tell you more than ratings: criteria preference-aware light graph convolution for effective multi-criteria recommendation](https://arxiv.org/abs/2305.18885)|[cpa-lgc-recbole](https://github.com/jindeok/cpa-lgc-recbole)| -|[estimating conditional mutual information for dynamic feature selection](https://arxiv.org/abs/2306.03301)|[dime](https://github.com/suinleelab/dime)| +|date|paper|code| +|---|---|---| +|2306.02323|[lora backscatter communications: temporal, spectral, and error performance analysis](https://arxiv.org/abs/2306.02323)|[lora-backscatter-communications-temperal-spectral-and-error-performance-analysis](https://github.com/slingovie/lora-backscatter-communications-temperal-spectral-and-error-performance-analysis)| +|2306.03273|[under-counted tensor completion with neural incorporation of attributes](https://arxiv.org/abs/2306.03273)|[undercounted-tensor-completion](https://github.com/shahanaibrahimosu/undercounted-tensor-completion)| +|2306.03288|[deep learning from crowdsourced labels: coupled cross-entropy minimization, identifiability, and regularization](https://arxiv.org/abs/2306.03288)|[end-to-end-crowdsourcing](https://github.com/shahanaibrahimosu/end-to-end-crowdsourcing)| +|2306.03301|[estimating conditional mutual information for dynamic feature selection](https://arxiv.org/abs/2306.03301)|[dime](https://github.com/suinleelab/dime)| ## 2023-06-06 -|paper|code| -|---|---| -|[adaptive whitening in neural populations with gain-modulating interneurons](https://arxiv.org/abs/2301.11955)|[frame_whitening](https://github.com/lyndond/frame_whitening)| -|[data augmentation for generating synthetic electrogastrogram time series](https://arxiv.org/abs/2303.02408)|[syegg](https://github.com/nadicasm/syegg)| -|[optimal resource allocation with delay guarantees for network slicing in disaggregated ran](https://arxiv.org/abs/2305.17321)|[paper-fgkcj-2023](https://github.com/labora-inf-ufg/paper-fgkcj-2023)| -|[fast and interpretable nonlocal neural networks for image denoising via group-sparse convolutional dictionary learning](https://arxiv.org/abs/2306.01950)|[groupcdl-tip](https://github.com/nikopj/groupcdl-tip)| -|[why we should report the details in subjective evaluation of tts more rigorously](https://arxiv.org/abs/2306.02044)|[subjectiveevaluation](https://github.com/d223302/subjectiveevaluation)| -|[subspacenet: deep learning-aided subspace methods for doa estimation](https://arxiv.org/abs/2306.02271)|[subspacenet](https://github.com/shlezingerlab/subspacenet)| -|[infoshape: task-based neural data shaping via mutual information](https://arxiv.org/abs/2210.15034)|[infoshape](https://github.com/billywu1029/infoshape)| -|[admm-based detector for large-scale mimo code-domain noma systems](https://arxiv.org/abs/2306.02032)|[admm-based-detector-for-noma](https://github.com/vikas2020-del/admm-based-detector-for-noma)| +|date|paper|code| +|---|---|---| +|2306.01950|[fast and interpretable nonlocal neural networks for image denoising via group-sparse convolutional dictionary learning](https://arxiv.org/abs/2306.01950)|[groupcdl-tip](https://github.com/nikopj/groupcdl-tip)| +|2306.02044|[why we should report the details in subjective evaluation of tts more rigorously](https://arxiv.org/abs/2306.02044)|[subjectiveevaluation](https://github.com/d223302/subjectiveevaluation)| +|2306.02271|[subspacenet: deep learning-aided subspace methods for doa estimation](https://arxiv.org/abs/2306.02271)|[subspacenet](https://github.com/shlezingerlab/subspacenet)| +|2306.02032|[admm-based detector for large-scale mimo code-domain noma systems](https://arxiv.org/abs/2306.02032)|[admm-based-detector-for-noma](https://github.com/vikas2020-del/admm-based-detector-for-noma)| ## 2023-06-05 -|paper|code| -|---|---| -|[swl-adapt: an unsupervised domain adaptation model with sample weight learning for cross-user wearable human activity recognition](https://arxiv.org/abs/2212.00724)|[SWL-Adapt](https://github.com/Rxannro/SWL-Adapt)| -|[bayes-optimal limits in structured pca, and how to reach them](https://arxiv.org/abs/2210.01237)|[structured-pca-](https://github.com/fcamilli95/structured-pca-)| -|[probably anytime-safe stochastic combinatorial semi-bandits](https://arxiv.org/abs/2301.13393)|[passcsb](https://github.com/y-hou/passcsb)| +|date|paper|code| +|---|---|---| ## 2023-06-02 -|paper|code| -|---|---| -|[structural optimization of factor graphs for symbol detection via continuous clustering and machine learning](https://arxiv.org/abs/2211.11406)|[factor_graph_structural_opt](https://github.com/kit-cel/factor_graph_structural_opt)| -|[unearthing insights into mars: unsupervised source separation with limited data](https://arxiv.org/abs/2301.11981)|[insight_src_sep](https://github.com/alisiahkoohi/insight_src_sep)| -|[conditionally strongly log-concave generative models](https://arxiv.org/abs/2306.00181)|[wcrg](https://github.com/elempereur/wcrg)| -|[graph neural networks-based user pairing in wireless communication systems](https://arxiv.org/abs/2306.00717)|[userpairing](https://github.com/sharanmourya/userpairing)| -|[on tilted losses in machine learning: theory and applications](https://arxiv.org/abs/2109.06141)|[TERM](https://github.com/litian96/TERM)| -|[outsourcing control requires control complexity](https://arxiv.org/abs/2209.01418)|[learningrequiresintinf](https://github.com/carlottalanger/learningrequiresintinf)| +|date|paper|code| +|---|---|---| +|2306.00181|[conditionally strongly log-concave generative models](https://arxiv.org/abs/2306.00181)|[wcrg](https://github.com/elempereur/wcrg)| +|2306.00717|[graph neural networks-based user pairing in wireless communication systems](https://arxiv.org/abs/2306.00717)|[userpairing](https://github.com/sharanmourya/userpairing)| ## 2023-06-01 -|paper|code| -|---|---| -|[on the convergence of inexact gradient descent with controlled synchronization steps](https://arxiv.org/abs/2208.07797)|[inexact-gradient-descent](https://github.com/Sandushan/inexact-gradient-descent)| -|[a hybrid quantum-classical approach based on the hadamard transform for the convolutional layer](https://arxiv.org/abs/2305.17510)|[icml2023-ht](https://github.com/phy710/icml2023-ht)| -|[variational $f$-divergence and derangements for discriminative mutual information estimation](https://arxiv.org/abs/2305.20025)|[fdime](https://github.com/tonellolab/fdime)| -|[recovering top-two answers and confusion probability in multi-choice crowdsourcing](https://arxiv.org/abs/2301.00006)|[toptwo](https://github.com/hyeonsu-jeong/toptwo)| -|[domain adaptive decision trees: implications for accuracy and fairness](https://arxiv.org/abs/2302.13846)|[domain-adaptive-trees](https://github.com/nobias-project/domain-adaptive-trees)| -|[deepmad: mathematical architecture design for deep convolutional neural network](https://arxiv.org/abs/2303.02165)|[lightweight-neural-architecture-search](https://github.com/alibaba/lightweight-neural-architecture-search)| -|[causal discovery for time series with constraint-based model and pmime measure](https://arxiv.org/abs/2305.19695)|[cd_for_ts_with_cbm_and_pmime](https://github.com/aarsac/cd_for_ts_with_cbm_and_pmime)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/07.md b/archives/2023/07.md index 424fb082..aaae1003 100644 --- a/archives/2023/07.md +++ b/archives/2023/07.md @@ -1,155 +1,105 @@ # July 2023 Archive ## 2023-07-31 -|paper|code| -|---|---| -|[dime: maximizing mutual information by a difference of matrix-based entropies](https://arxiv.org/abs/2301.08164)|[DiME](https://github.com/uk-cliplab/DiME)| -|[quantifying & modeling multimodal interactions: an information decomposition framework](https://arxiv.org/abs/2302.12247)|[pid](https://github.com/pliang279/pid)| +|date|paper|code| +|---|---|---| ## 2023-07-28 -|paper|code| -|---|---| -|[learning transfer operators by kernel density estimation](https://arxiv.org/abs/2210.03124)|[fpoperatorde](https://github.com/sudamphy/fpoperatorde)| +|date|paper|code| +|---|---|---| ## 2023-07-27 -|paper|code| -|---|---| -|[multi-target tracking with transferable convolutional neural networks](https://arxiv.org/abs/2210.15539)|[mtt](https://github.com/damowerko/mtt)| -|[manifold filter-combine networks](https://arxiv.org/abs/2307.04056)|[mfcn](https://github.com/krishnaswamylab/mfcn)| -|[learning to design analog circuits to meet threshold specifications](https://arxiv.org/abs/2307.13861)|[circuit-synthesis](https://github.com/indylab/circuit-synthesis)| +|date|paper|code| +|---|---|---| +|2307.04056|[manifold filter-combine networks](https://arxiv.org/abs/2307.04056)|[mfcn](https://github.com/krishnaswamylab/mfcn)| +|2307.13861|[learning to design analog circuits to meet threshold specifications](https://arxiv.org/abs/2307.13861)|[circuit-synthesis](https://github.com/indylab/circuit-synthesis)| ## 2023-07-26 -|paper|code| -|---|---| -|[noise detection with spectator qubits and quantum feature engineering](https://arxiv.org/abs/2103.13018)|[QFEND](https://github.com/akramyoussry/QFEND)| -|[denoising noisy neural networks: a bayesian approach with compensation](https://arxiv.org/abs/2105.10699)|[NoisyNN](https://github.com/lynshao/NoisyNN)| -|[bounded simplex-structured matrix factorization: algorithms, identifiability and applications](https://arxiv.org/abs/2209.12638)|[bssmf.jl](https://gitlab.com/vuthanho/bssmf.jl)| -|[a switching gaussian process latent force model for the identification of mechanical systems with a discontinuous nonlinearity](https://arxiv.org/abs/2303.03858)|[switching-gplfm](https://github.com/l-marino/switching-gplfm)| -|[adaptive regularized zero-forcing beamforming in massive mimo with multi-antenna users](https://arxiv.org/abs/2107.00853)|[Adaptive-Regularized-Zero-Forcing-Beamforming-in-Massive-MIMO-with-Multi-Antenna-Users](https://github.com/eugenbobrov/Adaptive-Regularized-Zero-Forcing-Beamforming-in-Massive-MIMO-with-Multi-Antenna-Users)| +|date|paper|code| +|---|---|---| ## 2023-07-25 -|paper|code| -|---|---| -|[nilm as a regression versus classification problem: the importance of thresholding](https://arxiv.org/abs/2010.16050)|[better_nilm](https://github.com/UCA-Datalab/better_nilm)| -|[trumpets: injective flows for inference and inverse problems](https://arxiv.org/abs/2102.10461)|[trumpets](https://github.com/swing-research/trumpets)| -|[self-supervised learning for human activity recognition using 700,000 person-days of wearable data](https://arxiv.org/abs/2206.02909)|[ssl-wearables](https://github.com/OxWearables/ssl-wearables)| -|[deep injective prior for inverse scattering](https://arxiv.org/abs/2301.03092)|[scattering_injective_prior](https://github.com/swing-research/scattering_injective_prior)| -|[self-supervised learning for time series analysis: taxonomy, progress, and prospects](https://arxiv.org/abs/2306.10125)|[Awesome-SSL4TS](https://github.com/qingsongedu/Awesome-SSL4TS)| -|[deep unfolded simulated bifurcation for massive mimo signal detection](https://arxiv.org/abs/2306.16264)|[unfolded_simbif](https://github.com/s-takabe/unfolded_simbif)| -|[remote bio-sensing: open source benchmark framework for fair evaluation of rppg](https://arxiv.org/abs/2307.12644)|[rppg](https://github.com/remotebiosensing/rppg)| -|[concept-based explainability for an eeg transformer model](https://arxiv.org/abs/2307.12745)|[tcav-bendr](https://github.com/andersgmadsen/tcav-bendr)| -|[in search of maximum non-overlapping codes](https://arxiv.org/abs/2307.12593)|[nono-codes](https://github.com/magdevska/nono-codes)| +|date|paper|code| +|---|---|---| +|2307.12644|[remote bio-sensing: open source benchmark framework for fair evaluation of rppg](https://arxiv.org/abs/2307.12644)|[rppg](https://github.com/remotebiosensing/rppg)| +|2307.12745|[concept-based explainability for an eeg transformer model](https://arxiv.org/abs/2307.12745)|[tcav-bendr](https://github.com/andersgmadsen/tcav-bendr)| +|2307.12593|[in search of maximum non-overlapping codes](https://arxiv.org/abs/2307.12593)|[nono-codes](https://github.com/magdevska/nono-codes)| ## 2023-07-24 -|paper|code| -|---|---| -|[lrh-net: a multi-level knowledge distillation approach for low-resource heart network](https://arxiv.org/abs/2204.08000)|[lrh-net](https://github.com/ekansh09/lrh-net)| -|[successive linear approximation vbi for joint sparse signal recovery and dynamic grid parameters estimation](https://arxiv.org/abs/2307.09149)|[sla-vbi](https://github.com/zju-xwk/sla-vbi)| -|[transferability of convolutional neural networks in stationary learning tasks](https://arxiv.org/abs/2307.11588)|[mtt](https://github.com/damowerko/mtt)| -|[adjacent-bits-swapped polar codes: a new code construction to speed up polarization](https://arxiv.org/abs/2202.04454)|[abs-polar](https://github.com/plumjelly/abs-polar)| +|date|paper|code| +|---|---|---| +|2307.09149|[successive linear approximation vbi for joint sparse signal recovery and dynamic grid parameters estimation](https://arxiv.org/abs/2307.09149)|[sla-vbi](https://github.com/zju-xwk/sla-vbi)| +|2307.11588|[transferability of convolutional neural networks in stationary learning tasks](https://arxiv.org/abs/2307.11588)|[mtt](https://github.com/damowerko/mtt)| ## 2023-07-21 -|paper|code| -|---|---| -|[learning-based reconstruction of fri signals](https://arxiv.org/abs/2212.08758)|[LearningBasedFRI](https://github.com/vchleung/LearningBasedFRI)| -|[multi-view self-supervised learning for multivariate variable-channel time series](https://arxiv.org/abs/2307.09614)|[multiview_ts_ssl](https://github.com/theabrusch/multiview_ts_ssl)| -|[novel batch active learning approach and its application to synthetic aperture radar datasets](https://arxiv.org/abs/2307.10495)|[sar_bal](https://github.com/chapman20j/sar_bal)| -|[can information flows suggest targets for interventions in neural circuits?](https://arxiv.org/abs/2111.05299)|[ann-info-flow](https://github.com/praveenv253/ann-info-flow)| +|date|paper|code| +|---|---|---| +|2307.09614|[multi-view self-supervised learning for multivariate variable-channel time series](https://arxiv.org/abs/2307.09614)|[multiview_ts_ssl](https://github.com/theabrusch/multiview_ts_ssl)| +|2307.10495|[novel batch active learning approach and its application to synthetic aperture radar datasets](https://arxiv.org/abs/2307.10495)|[sar_bal](https://github.com/chapman20j/sar_bal)| ## 2023-07-20 -|paper|code| -|---|---| -|[dreamr: diffusion-driven counterfactual explanation for functional mri](https://arxiv.org/abs/2307.09547)|[dreamr](https://github.com/icon-lab/dreamr)| -|[sionna rt: differentiable ray tracing for radio propagation modeling](https://arxiv.org/abs/2303.11103)|[diff-rt](https://github.com/nvlabs/diff-rt)| -|[genkl: an iterative framework for resolving label ambiguity and label non-conformity in web images via a new generalized kl divergence](https://arxiv.org/abs/2307.09810)|[genkl](https://github.com/codetopaper/genkl)| +|date|paper|code| +|---|---|---| +|2307.09547|[dreamr: diffusion-driven counterfactual explanation for functional mri](https://arxiv.org/abs/2307.09547)|[dreamr](https://github.com/icon-lab/dreamr)| +|2307.09810|[genkl: an iterative framework for resolving label ambiguity and label non-conformity in web images via a new generalized kl divergence](https://arxiv.org/abs/2307.09810)|[genkl](https://github.com/codetopaper/genkl)| ## 2023-07-19 -|paper|code| -|---|---| -|[on the convergence of inexact gradient descent with controlled synchronization steps](https://arxiv.org/abs/2208.07797)|[inexact-gradient-descent](https://github.com/Sandushan/inexact-gradient-descent)| -|[propagation of linear uncertainties through multiline thru-reflect-line calibration](https://arxiv.org/abs/2301.09126)|[uncertainty-multiline-trl-calibration](https://github.com/ZiadHatab/uncertainty-multiline-trl-calibration)| -|[implicit anatomical rendering for medical image segmentation with stochastic experts](https://arxiv.org/abs/2304.03209)|[morse](https://github.com/charlesyou999648/morse)| -|[gaussian process deconvolution](https://arxiv.org/abs/2305.04871)|[gaussian-process-deconvolution](https://github.com/games-uchile/gaussian-process-deconvolution)| -|[3dinvnet: a deep learning-based 3d ground-penetrating radar data inversion](https://arxiv.org/abs/2305.05425)|[3dinvnet](https://github.com/qiqi-dai/3dinvnet)| -|[classification with incoherent kernel dictionary learning](https://arxiv.org/abs/2307.08796)|[incoherent-kernel-dictionary-learning](https://github.com/denisilie94/incoherent-kernel-dictionary-learning)| -|[reduced kernel dictionary learning](https://arxiv.org/abs/2307.08798)|[rkdl](https://github.com/denisilie94/rkdl)| -|[radar-stda: a high-performance spatial-temporal denoising autoencoder for interference mitigation of fmcw radars](https://arxiv.org/abs/2307.09063)|[rd_map_temporal_spatial_denoising_autoencoder](https://github.com/guanrunwei/rd_map_temporal_spatial_denoising_autoencoder)| -|[application of bert in wind power forecasting-teletraan's solution in baidu kdd cup 2022](https://arxiv.org/abs/2307.09248)|[kdd2022-baidu](https://github.com/longxingtan/kdd2022-baidu)| -|[deepcabac: a universal compression algorithm for deep neural networks](https://arxiv.org/abs/1907.11900)|[DeepCABAC](https://github.com/fraunhoferhhi/DeepCABAC)| +|date|paper|code| +|---|---|---| +|2307.08796|[classification with incoherent kernel dictionary learning](https://arxiv.org/abs/2307.08796)|[incoherent-kernel-dictionary-learning](https://github.com/denisilie94/incoherent-kernel-dictionary-learning)| +|2307.08798|[reduced kernel dictionary learning](https://arxiv.org/abs/2307.08798)|[rkdl](https://github.com/denisilie94/rkdl)| +|2307.09063|[radar-stda: a high-performance spatial-temporal denoising autoencoder for interference mitigation of fmcw radars](https://arxiv.org/abs/2307.09063)|[rd_map_temporal_spatial_denoising_autoencoder](https://github.com/guanrunwei/rd_map_temporal_spatial_denoising_autoencoder)| +|2307.09248|[application of bert in wind power forecasting-teletraan's solution in baidu kdd cup 2022](https://arxiv.org/abs/2307.09248)|[kdd2022-baidu](https://github.com/longxingtan/kdd2022-baidu)| ## 2023-07-18 -|paper|code| -|---|---| -|[wifi based distance estimation using supervised machine learning](https://arxiv.org/abs/2208.07190)|[wifi-fingerprint](https://github.com/kahramankostas/wifi-fingerprint)| -|[multi-target tracking with transferable convolutional neural networks](https://arxiv.org/abs/2210.15539)|[mtt](https://github.com/damowerko/mtt)| -|[graph neural networks on spd manifolds for motor imagery classification: a perspective from the time-frequency analysis](https://arxiv.org/abs/2211.02641)|[Tensor-CSPNet-and-Graph-CSPNet](https://github.com/GeometricBCI/Tensor-CSPNet-and-Graph-CSPNet)| -|[learning to reconstruct signals from binary measurements](https://arxiv.org/abs/2303.08691)|[ssbm](https://github.com/tachella/ssbm)| -|[source-free domain adaptation with temporal imputation for time series data](https://arxiv.org/abs/2307.07542)|[mapu_sfda_ts](https://github.com/mohamedr002/mapu_sfda_ts)| -|[harpa: high-rate phase association with travel time neural fields](https://arxiv.org/abs/2307.07572)|[phase_association](https://github.com/dadacheng/phase_association)| +|date|paper|code| +|---|---|---| +|2307.07542|[source-free domain adaptation with temporal imputation for time series data](https://arxiv.org/abs/2307.07542)|[mapu_sfda_ts](https://github.com/mohamedr002/mapu_sfda_ts)| +|2307.07572|[harpa: high-rate phase association with travel time neural fields](https://arxiv.org/abs/2307.07572)|[phase_association](https://github.com/dadacheng/phase_association)| ## 2023-07-14 -|paper|code| -|---|---| -|[semantic information recovery in wireless networks](https://arxiv.org/abs/2204.13366)|[sinfony](https://github.com/ant-uni-bremen/sinfony)| -|[human biophysics as network weights: conditional generative models for dynamic simulation](https://arxiv.org/abs/2211.01856)|[biomime](https://github.com/shihan-ma/biomime)| +|date|paper|code| +|---|---|---| ## 2023-07-13 -|paper|code| -|---|---| -|[b-har: an open-source baseline framework for in depth study of human activity recognition datasets and workflows](https://arxiv.org/abs/2101.10870)|[B-HAR](https://github.com/B-HAR-HumanActivityRecognition/B-HAR)| -|[semi-device-dependent blind quantum tomography](https://arxiv.org/abs/2006.03069)|[blind-quantum-tomography](https://gitlab.com/wilkensJ/blind-quantum-tomography)| -|[fundamental limits for sensor-based robot control](https://arxiv.org/abs/2202.00129)|[performance-limits](https://github.com/irom-lab/performance-limits)| +|date|paper|code| +|---|---|---| ## 2023-07-12 -|paper|code| -|---|---| -|[super-resolution radar imaging with sparse arrays using a deep neural network trained with enhanced virtual data](https://arxiv.org/abs/2306.09839)|[sparse-array-radar-imaging](https://github.com/christianschuessler/sparse-array-radar-imaging)| -|[tsdownsample: high-performance time series downsampling for scalable visualization](https://arxiv.org/abs/2307.05389)|[tsdownsample](https://github.com/predict-idlab/tsdownsample)| +|date|paper|code| +|---|---|---| +|2307.05389|[tsdownsample: high-performance time series downsampling for scalable visualization](https://arxiv.org/abs/2307.05389)|[tsdownsample](https://github.com/predict-idlab/tsdownsample)| ## 2023-07-11 -|paper|code| -|---|---| -|[grid-free mimo beam alignment through site-specific deep learning](https://arxiv.org/abs/2209.08198)|[dlgf](https://github.com/yuqiangheng/dlgf)| -|[manifold filter-combine networks](https://arxiv.org/abs/2307.04056)|[mfcn](https://github.com/krishnaswamylab/mfcn)| -|[spoofing-resilient lidar-gps factor graph localization with chimera authentication](https://arxiv.org/abs/2307.04692)|[chimera_fgo](https://github.com/stanford-navlab/chimera_fgo)| -|[set learning for accurate and calibrated models](https://arxiv.org/abs/2307.02245)|[oko](https://github.com/lukasmut/oko)| +|date|paper|code| +|---|---|---| +|2307.04056|[manifold filter-combine networks](https://arxiv.org/abs/2307.04056)|[mfcn](https://github.com/krishnaswamylab/mfcn)| +|2307.04692|[spoofing-resilient lidar-gps factor graph localization with chimera authentication](https://arxiv.org/abs/2307.04692)|[chimera_fgo](https://github.com/stanford-navlab/chimera_fgo)| +|2307.02245|[set learning for accurate and calibrated models](https://arxiv.org/abs/2307.02245)|[oko](https://github.com/lukasmut/oko)| ## 2023-07-10 -|paper|code| -|---|---| -|[deep optimal transport for domain adaptation on spd manifolds](https://arxiv.org/abs/2201.05745)|[deep-optimal-transport-for-domain-adaptation-on-spd-manifolds](https://github.com/geometricbci/deep-optimal-transport-for-domain-adaptation-on-spd-manifolds)| -|[avoiding post-processing with event-based detection in biomedical signals](https://arxiv.org/abs/2209.11007)|[eventnet](https://github.com/n1xu5/eventnet)| -|[exact recovery of the support of piecewise constant images via total variation regularization](https://arxiv.org/abs/2307.03709)|[2023-support-recovery-tv](https://github.com/rpetit/2023-support-recovery-tv)| +|date|paper|code| +|---|---|---| +|2307.03709|[exact recovery of the support of piecewise constant images via total variation regularization](https://arxiv.org/abs/2307.03709)|[2023-support-recovery-tv](https://github.com/rpetit/2023-support-recovery-tv)| ## 2023-07-07 -|paper|code| -|---|---| -|[alpcah: sample-wise heteroscedastic pca with tail singular value regularization](https://arxiv.org/abs/2307.02745)|[alpcah](https://github.com/javiersc1/alpcah)| -|[fast and multi-aspect mining of complex time-stamped event streams](https://arxiv.org/abs/2303.03789)|[cubescope](https://github.com/kotanakm/cubescope)| -|[on the noise sensitivity of the randomized svd](https://arxiv.org/abs/2305.17435)|[randomized-svd-code](https://github.com/eladromanov/randomized-svd-code)| +|date|paper|code| +|---|---|---| +|2307.02745|[alpcah: sample-wise heteroscedastic pca with tail singular value regularization](https://arxiv.org/abs/2307.02745)|[alpcah](https://github.com/javiersc1/alpcah)| ## 2023-07-06 -|paper|code| -|---|---| -|[d\'em\'elange, d\'econvolution et d\'ebruitage conjoints d'un mod\`ele convolutif parcimonieux avec d\'erive instrumentale, par p\'enalisation de rapports de normes ou quasi-normes liss\'ees (pendantss)](https://arxiv.org/abs/2307.01761)|[pendantss](https://github.com/paulzhengfr/pendantss)| -|[deep generation of heterogeneous networks](https://arxiv.org/abs/2206.12336)|[hgen](https://github.com/lingchen0331/hgen)| -|[on probability shaping for 5g mimo wireless channel with realistic ldpc codes](https://arxiv.org/abs/2303.02598)|[on-probabilistic-qam-shaping-for-5g-mimo-wireless-channel-with-realistic-ldpc-codes](https://github.com/eugenbobrov/on-probabilistic-qam-shaping-for-5g-mimo-wireless-channel-with-realistic-ldpc-codes)| -|[conditional and residual methods in scalable coding for humans and machines](https://arxiv.org/abs/2305.02562)|[research](https://github.com/adeandrade/research)| -|[a neural collapse perspective on feature evolution in graph neural networks](https://arxiv.org/abs/2307.01951)|[gnn_collapse](https://github.com/kvignesh1420/gnn_collapse)| +|date|paper|code| +|---|---|---| +|2307.01761|[d\'em\'elange, d\'econvolution et d\'ebruitage conjoints d'un mod\`ele convolutif parcimonieux avec d\'erive instrumentale, par p\'enalisation de rapports de normes ou quasi-normes liss\'ees (pendantss)](https://arxiv.org/abs/2307.01761)|[pendantss](https://github.com/paulzhengfr/pendantss)| +|2307.01951|[a neural collapse perspective on feature evolution in graph neural networks](https://arxiv.org/abs/2307.01951)|[gnn_collapse](https://github.com/kvignesh1420/gnn_collapse)| ## 2023-07-04 -|paper|code| -|---|---| -|[propagation of linear uncertainties through multiline thru-reflect-line calibration](https://arxiv.org/abs/2301.09126)|[uncertainty-multiline-trl-calibration](https://github.com/ZiadHatab/uncertainty-multiline-trl-calibration)| -|[towards domain generalization for ecg and eeg classification: algorithms and benchmarks](https://arxiv.org/abs/2303.11338)|[biodg](https://github.com/aristotelisballas/biodg)| -|[decision-oriented two-parameter fisher information sensitivity using symplectic decomposition](https://arxiv.org/abs/2207.12077)|[symplecticfishersensitivity](https://github.com/longitude-jyang/symplecticfishersensitivity)| -|[a lego-brick approach to coding for network communication](https://arxiv.org/abs/2211.07208)|[lego-brick](https://github.com/nadimgh/lego-brick)| -|[worth of knowledge in deep learning](https://arxiv.org/abs/2307.00712)|[worth_of_knowledge](https://github.com/woshixuhao/worth_of_knowledge)| -|[engage: explanation guided data augmentation for graph representation learning](https://arxiv.org/abs/2307.01053)|[engage](https://github.com/sycny/engage)| +|date|paper|code| +|---|---|---| +|2307.00712|[worth of knowledge in deep learning](https://arxiv.org/abs/2307.00712)|[worth_of_knowledge](https://github.com/woshixuhao/worth_of_knowledge)| +|2307.01053|[engage: explanation guided data augmentation for graph representation learning](https://arxiv.org/abs/2307.01053)|[engage](https://github.com/sycny/engage)| ## 2023-07-03 -|paper|code| -|---|---| -|[learning bilinear models of actuated koopman generators from partially-observed trajectories](https://arxiv.org/abs/2209.09977)|[koopmangeneratorem](https://github.com/samotto1/koopmangeneratorem)| -|[root tracking for rate-distortion: approximating a solution curve with higher implicit multivariate derivatives](https://arxiv.org/abs/2206.11369)|[rtrd](https://github.com/shlomiag/rtrd)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/08.md b/archives/2023/08.md index 482ea89f..50ba2ed8 100644 --- a/archives/2023/08.md +++ b/archives/2023/08.md @@ -1,161 +1,119 @@ # August 2023 Archive ## 2023-08-31 -|paper|code| -|---|---| -|[on low-rank trace regression under general sampling distribution](https://arxiv.org/abs/1904.08576)|[cv-impute](https://github.com/mohsenbayati/cv-impute)| +|date|paper|code| +|---|---|---| ## 2023-08-30 -|paper|code| -|---|---| -|[fundamentals of wobbling and hardware impairments-aware air-to-ground channel model](https://arxiv.org/abs/2205.10957)|[Wobbling-HI-Drones](https://github.com/mbanagar/Wobbling-HI-Drones)| -|[towards domain generalization for ecg and eeg classification: algorithms and benchmarks](https://arxiv.org/abs/2303.11338)|[biodg](https://github.com/aristotelisballas/biodg)| -|[towards quantitative precision for ecg analysis: leveraging state space models, self-supervision and patient metadata](https://arxiv.org/abs/2308.15291)|[ssm_ecg](https://github.com/tmehari/ssm_ecg)| -|[ridgeless regression with random features](https://arxiv.org/abs/2205.00477)|[ridgeless-regression-with-random-features](https://github.com/superlj666/ridgeless-regression-with-random-features)| +|date|paper|code| +|---|---|---| +|2308.15291|[towards quantitative precision for ecg analysis: leveraging state space models, self-supervision and patient metadata](https://arxiv.org/abs/2308.15291)|[ssm_ecg](https://github.com/tmehari/ssm_ecg)| ## 2023-08-29 -|paper|code| -|---|---| -|[self-supervised scalable deep compressed sensing](https://arxiv.org/abs/2308.13777)|[scnet](https://github.com/guaishou74851/scnet)| -|[a comparison of neural networks for wireless channel prediction](https://arxiv.org/abs/2308.14020)|[channel_prediction_dnn](https://github.com/osst3224/channel_prediction_dnn)| -|[on the statistical relation of ultra-reliable wireless and location estimation](https://arxiv.org/abs/2308.14416)|[localization-and-reliability-in-urllc](https://github.com/tobiaskallehauge/localization-and-reliability-in-urllc)| -|[fast and low-memory compressive sensing algorithms for low tucker-rank tensor approximation from streamed measurements](https://arxiv.org/abs/2308.13709)|[leave_one_out_recovery](https://github.com/cahaselby/leave_one_out_recovery)| -|[a spatially non-stationary fading channel model for simulation and (semi-) analytical study of elaa-mimo](https://arxiv.org/abs/2308.13858)|[non-stationary-fading-channel-model](https://github.com/elaa-mimo/non-stationary-fading-channel-model)| +|date|paper|code| +|---|---|---| +|2308.13777|[self-supervised scalable deep compressed sensing](https://arxiv.org/abs/2308.13777)|[scnet](https://github.com/guaishou74851/scnet)| +|2308.14020|[a comparison of neural networks for wireless channel prediction](https://arxiv.org/abs/2308.14020)|[channel_prediction_dnn](https://github.com/osst3224/channel_prediction_dnn)| +|2308.14416|[on the statistical relation of ultra-reliable wireless and location estimation](https://arxiv.org/abs/2308.14416)|[localization-and-reliability-in-urllc](https://github.com/tobiaskallehauge/localization-and-reliability-in-urllc)| +|2308.13709|[fast and low-memory compressive sensing algorithms for low tucker-rank tensor approximation from streamed measurements](https://arxiv.org/abs/2308.13709)|[leave_one_out_recovery](https://github.com/cahaselby/leave_one_out_recovery)| +|2308.13858|[a spatially non-stationary fading channel model for simulation and (semi-) analytical study of elaa-mimo](https://arxiv.org/abs/2308.13858)|[non-stationary-fading-channel-model](https://github.com/elaa-mimo/non-stationary-fading-channel-model)| ## 2023-08-28 -|paper|code| -|---|---| -|[early stopping for deep image prior](https://arxiv.org/abs/2112.06074)|[early_stopping_for_dip](https://github.com/sun-umn/early_stopping_for_dip)| -|[arrhythmia classifier based on ultra-lightweight binary neural network](https://arxiv.org/abs/2304.01568)|[ecg_bnn_net](https://github.com/xpww/ecg_bnn_net)| -|[parameter-efficient learning for text-to-speech accent adaptation](https://arxiv.org/abs/2305.11320)|[PEL-TTS](https://github.com/TTS-Research/PEL-TTS)| -|[a multi-dimensional deep structured state space approach to speech enhancement using small-footprint models](https://arxiv.org/abs/2306.00331)|[s4nd-u-net_speech_enhancement](https://github.com/kuray107/s4nd-u-net_speech_enhancement)| +|date|paper|code| +|---|---|---| ## 2023-08-25 -|paper|code| -|---|---| -|[quantized radio map estimation using tensor and deep generative models](https://arxiv.org/abs/2303.01770)|[Quantized-Radio-Map-Estimation-BTD-and-DGM](https://github.com/XiaoFuLab/Quantized-Radio-Map-Estimation-BTD-and-DGM)| -|[dh-ptam: a deep hybrid stereo events-frames parallel tracking and mapping system](https://arxiv.org/abs/2306.01891)|[dh-ptam](https://github.com/abanobsoliman/dh-ptam)| +|date|paper|code| +|---|---|---| ## 2023-08-24 -|paper|code| -|---|---| -|[a thru-free multiline calibration](https://arxiv.org/abs/2305.03597)|[thru-free-multiline-calibration](https://github.com/ZiadHatab/thru-free-multiline-calibration)| -|[compressed sensing: a discrete optimization approach](https://arxiv.org/abs/2306.04647)|[discretecompressedsensing.jl](https://github.com/nicholasjohnson2020/discretecompressedsensing.jl)| -|[iot data trust evaluation via machine learning](https://arxiv.org/abs/2308.11638)|[iot_datatrust_rwi](https://github.com/tim-tadj/iot_datatrust_rwi)| -|[optimal linear precoder design for mimo-ofdm integrated sensing and communications based on bayesian cram\'er-rao bound](https://arxiv.org/abs/2308.12106)|[isac-mimo-ofdm-wf](https://github.com/xinyanglii/isac-mimo-ofdm-wf)| -|[system identification using the signed cumulative distribution transform in structural health monitoring applications](https://arxiv.org/abs/2308.12259)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| +|date|paper|code| +|---|---|---| +|2308.11638|[iot data trust evaluation via machine learning](https://arxiv.org/abs/2308.11638)|[iot_datatrust_rwi](https://github.com/tim-tadj/iot_datatrust_rwi)| +|2308.12106|[optimal linear precoder design for mimo-ofdm integrated sensing and communications based on bayesian cram\'er-rao bound](https://arxiv.org/abs/2308.12106)|[isac-mimo-ofdm-wf](https://github.com/xinyanglii/isac-mimo-ofdm-wf)| +|2308.12259|[system identification using the signed cumulative distribution transform in structural health monitoring applications](https://arxiv.org/abs/2308.12259)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| ## 2023-08-23 -|paper|code| -|---|---| -|[learning to learn graph topologies](https://arxiv.org/abs/2110.09807)|[l2g-neurips2021](https://github.com/xpuoxford/l2g-neurips2021)| -|[tightly integrated motion classification and state estimation in foot-mounted navigation systems](https://arxiv.org/abs/2305.09363)|[filterbanks](https://gitlab.liu.se/open-shoe/filterbanks)| -|[graph neural network-enhanced expectation propagation algorithm for mimo turbo receivers](https://arxiv.org/abs/2308.11335)|[GNN-enhanced-EP-for-Turbo-MIMO](https://github.com/STARainZ/GNN-enhanced-EP-for-Turbo-MIMO)| -|[information content and maximum entropy of compartmental systems in equilibrium](https://arxiv.org/abs/2308.10956)|[entropy_and_complexity_in_eq](https://github.com/goujou/entropy_and_complexity_in_eq)| +|date|paper|code| +|---|---|---| +|2308.11335|[graph neural network-enhanced expectation propagation algorithm for mimo turbo receivers](https://arxiv.org/abs/2308.11335)|[GNN-enhanced-EP-for-Turbo-MIMO](https://github.com/STARainZ/GNN-enhanced-EP-for-Turbo-MIMO)| +|2308.10956|[information content and maximum entropy of compartmental systems in equilibrium](https://arxiv.org/abs/2308.10956)|[entropy_and_complexity_in_eq](https://github.com/goujou/entropy_and_complexity_in_eq)| ## 2023-08-22 -|paper|code| -|---|---| -|[parallel faceted imaging in radio interferometry via proximal splitting (faceted hypersara): ii. code and real data proof of concept](https://arxiv.org/abs/2209.07604)|[faceted-hypersara](https://github.com/basp-group/faceted-hypersara)| -|[a unified multi-task semantic communication system for multimodal data](https://arxiv.org/abs/2209.07689)|[t-udeepsc](https://github.com/zhang-guangyi/t-udeepsc)| -|[graph neural networks on spd manifolds for motor imagery classification: a perspective from the time-frequency analysis](https://arxiv.org/abs/2211.02641)|[Tensor-CSPNet-and-Graph-CSPNet](https://github.com/GeometricBCI/Tensor-CSPNet-and-Graph-CSPNet)| -|[multidimensional graph neural networks for wireless communications](https://arxiv.org/abs/2212.11531)|[mdgnn](https://github.com/lsj-buaa/mdgnn)| -|[entropy estimation via uniformization](https://arxiv.org/abs/2304.09700)|[nfee](https://github.com/ziq-ao/nfee)| -|[learning and communications co-design for remote inference systems: feature length selection and transmission scheduling](https://arxiv.org/abs/2308.10094)|[impact-of-data-freshness-in-learning](https://github.com/kamran0153/impact-of-data-freshness-in-learning)| +|date|paper|code| +|---|---|---| +|2308.10094|[learning and communications co-design for remote inference systems: feature length selection and transmission scheduling](https://arxiv.org/abs/2308.10094)|[impact-of-data-freshness-in-learning](https://github.com/kamran0153/impact-of-data-freshness-in-learning)| ## 2023-08-21 -|paper|code| -|---|---| -|[towards best practice of interpreting deep learning models for eeg-based brain computer interfaces](https://arxiv.org/abs/2202.06948)|[Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI](https://github.com/cuijiancorbin/Towards-Best-Practice-of-Interpreting-Deep-Learning-Models-for-EEG-based-BCI)| -|[remote bio-sensing: open source benchmark framework for fair evaluation of rppg](https://arxiv.org/abs/2307.12644)|[rppg](https://github.com/remotebiosensing/rppg)| -|[swinjscc: taming swin transformer for deep joint source-channel coding](https://arxiv.org/abs/2308.09361)|[swinjscc](https://github.com/semcomm/swinjscc)| +|date|paper|code| +|---|---|---| +|2308.09361|[swinjscc: taming swin transformer for deep joint source-channel coding](https://arxiv.org/abs/2308.09361)|[swinjscc](https://github.com/semcomm/swinjscc)| ## 2023-08-17 -|paper|code| -|---|---| -|[quaternary neural belief propagation decoding of quantum ldpc codes with overcomplete check matrices](https://arxiv.org/abs/2308.08208)|[quantum-neural-bp4-demo](https://github.com/kit-cel/quantum-neural-bp4-demo)| +|date|paper|code| +|---|---|---| +|2308.08208|[quaternary neural belief propagation decoding of quantum ldpc codes with overcomplete check matrices](https://arxiv.org/abs/2308.08208)|[quantum-neural-bp4-demo](https://github.com/kit-cel/quantum-neural-bp4-demo)| ## 2023-08-16 -|paper|code| -|---|---| -|[selective noise suppression methods using random svpwm to shape the noise spectrum of pmsms](https://arxiv.org/abs/2302.08053)|[SNS-in-random-SVPWM](https://github.com/IoaJianWen/SNS-in-random-SVPWM)| -|[rigorous dynamical mean field theory for stochastic gradient descent methods](https://arxiv.org/abs/2210.06591)|[rigorous-dynamical-mean-field-theory](https://github.com/spoc-group/rigorous-dynamical-mean-field-theory)| +|date|paper|code| +|---|---|---| ## 2023-08-15 -|paper|code| -|---|---| -|[can we transfer noise patterns? a multi-environment spectrum analysis model using generated cases](https://arxiv.org/abs/2308.01138)|[cnst](https://github.com/magnomic/cnst)| +|date|paper|code| +|---|---|---| +|2308.01138|[can we transfer noise patterns? a multi-environment spectrum analysis model using generated cases](https://arxiv.org/abs/2308.01138)|[cnst](https://github.com/magnomic/cnst)| ## 2023-08-14 -|paper|code| -|---|---| -|[collaborative learning with a drone orchestrator](https://arxiv.org/abs/2303.02266)|[collaborative-learning-with-a-drone-orchestrator](https://github.com/drmahdiboloursazmashhadi/collaborative-learning-with-a-drone-orchestrator)| -|[a thru-free multiline calibration](https://arxiv.org/abs/2305.03597)|[thru-free-multiline-calibration](https://github.com/ZiadHatab/thru-free-multiline-calibration)| -|[unlocking the diagnostic potential of ecg through knowledge transfer from cardiac mri](https://arxiv.org/abs/2308.05764)|[mmcl-ecg-cmr](https://github.com/oetu/mmcl-ecg-cmr)| -|[a law of data separation in deep learning](https://arxiv.org/abs/2210.17020)|[re-equi-sepa](https://github.com/dadacheng/re-equi-sepa)| +|date|paper|code| +|---|---|---| +|2308.05764|[unlocking the diagnostic potential of ecg through knowledge transfer from cardiac mri](https://arxiv.org/abs/2308.05764)|[mmcl-ecg-cmr](https://github.com/oetu/mmcl-ecg-cmr)| ## 2023-08-11 -|paper|code| -|---|---| -|[cosys-airsim: a real-time simulation framework expanded for complex industrial applications](https://arxiv.org/abs/2303.13381)|[Cosys-AirSim](https://github.com/Cosys-Lab/Cosys-AirSim)| -|[deep generative models for unsupervised delamination detection using guided waves](https://arxiv.org/abs/2308.05350)|[anovae-delamshm](https://github.com/mahindrautela/anovae-delamshm)| -|[audioldm 2: learning holistic audio generation with self-supervised pretraining](https://arxiv.org/abs/2308.05734)|[AudioLDM2](https://github.com/haoheliu/AudioLDM2)| -|[information decomposition reveals hidden high-order contributions to temporal irreversibility](https://arxiv.org/abs/2308.05664)|[fastdmf](https://gitlab.com/concog/fastdmf)| +|date|paper|code| +|---|---|---| +|2308.05350|[deep generative models for unsupervised delamination detection using guided waves](https://arxiv.org/abs/2308.05350)|[anovae-delamshm](https://github.com/mahindrautela/anovae-delamshm)| +|2308.05734|[audioldm 2: learning holistic audio generation with self-supervised pretraining](https://arxiv.org/abs/2308.05734)|[AudioLDM2](https://github.com/haoheliu/AudioLDM2)| +|2308.05664|[information decomposition reveals hidden high-order contributions to temporal irreversibility](https://arxiv.org/abs/2308.05664)|[fastdmf](https://gitlab.com/concog/fastdmf)| ## 2023-08-10 -|paper|code| -|---|---| -|[emergence of the svd as an interpretable factorization in deep learning for inverse problems](https://arxiv.org/abs/2301.07820)|[descrambling-nn](https://github.com/shashanksule/descrambling-nn)| -|[low-complexity subspace-descent over symmetric positive definite manifold](https://arxiv.org/abs/2305.02041)|[subspace_descent_over_SPD_manifold](https://github.com/yogeshd-iitk/subspace_descent_over_SPD_manifold)| -|[striking the right balance: three-dimensional ocean sound speed field reconstruction using tensor neural networks](https://arxiv.org/abs/2308.04930)|[tensor-neural-network](https://github.com/oceanstarlab/tensor-neural-network)| +|date|paper|code| +|---|---|---| +|2308.04930|[striking the right balance: three-dimensional ocean sound speed field reconstruction using tensor neural networks](https://arxiv.org/abs/2308.04930)|[tensor-neural-network](https://github.com/oceanstarlab/tensor-neural-network)| ## 2023-08-09 -|paper|code| -|---|---| -|[rtsnet: learning to smooth in partially known state-space models](https://arxiv.org/abs/2110.04717)|[rtsnet_tsp](https://github.com/kalmannet/rtsnet_tsp)| -|[quantum and quantum-inspired stereographic k nearest-neighbour clustering](https://arxiv.org/abs/2308.03949)|[stereographic-quantum-embedding-clustering](https://github.com/alonsoviladomat/stereographic-quantum-embedding-clustering)| +|date|paper|code| +|---|---|---| +|2308.03949|[quantum and quantum-inspired stereographic k nearest-neighbour clustering](https://arxiv.org/abs/2308.03949)|[stereographic-quantum-embedding-clustering](https://github.com/alonsoviladomat/stereographic-quantum-embedding-clustering)| ## 2023-08-08 -|paper|code| -|---|---| -|[l-seqsleepnet: whole-cycle long sequence modelling for automatic sleep staging](https://arxiv.org/abs/2301.03441)|[l-seqsleepnet](https://github.com/pquochuy/l-seqsleepnet)| -|[successive pose estimation and beam tracking for mmwave vehicular communication systems](https://arxiv.org/abs/2307.16117)|[Fast-CFEAR-Radar-Odometry](https://github.com/Cen-Liu/Fast-CFEAR-Radar-Odometry)| -|[branched latent neural operators](https://arxiv.org/abs/2308.02599)|[blno.jl](https://github.com/stanfordcbcl/blno.jl)| -|[k-band: self-supervised mri reconstruction via stochastic gradient descent over k-space subsets](https://arxiv.org/abs/2308.02958)|[k-band](https://github.com/mikgroup/k-band)| +|date|paper|code| +|---|---|---| +|2308.02599|[branched latent neural operators](https://arxiv.org/abs/2308.02599)|[blno.jl](https://github.com/stanfordcbcl/blno.jl)| +|2308.02958|[k-band: self-supervised mri reconstruction via stochastic gradient descent over k-space subsets](https://arxiv.org/abs/2308.02958)|[k-band](https://github.com/mikgroup/k-band)| ## 2023-08-07 -|paper|code| -|---|---| -|[motion-robust free-running cardiovascular mri](https://arxiv.org/abs/2308.02088)|[motion-robust-CMR](https://github.com/syedmurtazaarshad/motion-robust-CMR)| -|[design space exploration on efficient and accurate human pose estimation from sparse imu-sensing](https://arxiv.org/abs/2308.02397)|[dse-sparse-imu](https://github.com/itiv-kit/dse-sparse-imu)| -|[differentiable adaptive short-time fourier transform with respect to the window length](https://arxiv.org/abs/2308.02418)|[dstft](https://github.com/maxime-leiber/dstft)| -|[multimodal indoor localisation in parkinson's disease for detecting medication use: observational pilot study in a free-living setting](https://arxiv.org/abs/2308.02419)|[Multihead-Dual-Convolutional-Self-Attention](https://github.com/ferdianjovan/Multihead-Dual-Convolutional-Self-Attention)| -|[differentiable short-time fourier transform with respect to the hop length](https://arxiv.org/abs/2308.02421)|[dstft](https://github.com/maxime-leiber/dstft)| -|[hypertension detection from high-dimensional representation of photoplethysmogram signals](https://arxiv.org/abs/2308.02425)|[hypertension_ppg](https://github.com/navidhasanzadeh/hypertension_ppg)| -|[contrastive self-supervised learning based approach for patient similarity: a case study on atrial fibrillation detection from ppg signal](https://arxiv.org/abs/2308.02433)|[simsig](https://github.com/subangkar/simsig)| +|date|paper|code| +|---|---|---| +|2308.02088|[motion-robust free-running cardiovascular mri](https://arxiv.org/abs/2308.02088)|[motion-robust-CMR](https://github.com/syedmurtazaarshad/motion-robust-CMR)| +|2308.02397|[design space exploration on efficient and accurate human pose estimation from sparse imu-sensing](https://arxiv.org/abs/2308.02397)|[dse-sparse-imu](https://github.com/itiv-kit/dse-sparse-imu)| +|2308.02418|[differentiable adaptive short-time fourier transform with respect to the window length](https://arxiv.org/abs/2308.02418)|[dstft](https://github.com/maxime-leiber/dstft)| +|2308.02419|[multimodal indoor localisation in parkinson's disease for detecting medication use: observational pilot study in a free-living setting](https://arxiv.org/abs/2308.02419)|[Multihead-Dual-Convolutional-Self-Attention](https://github.com/ferdianjovan/Multihead-Dual-Convolutional-Self-Attention)| +|2308.02421|[differentiable short-time fourier transform with respect to the hop length](https://arxiv.org/abs/2308.02421)|[dstft](https://github.com/maxime-leiber/dstft)| +|2308.02425|[hypertension detection from high-dimensional representation of photoplethysmogram signals](https://arxiv.org/abs/2308.02425)|[hypertension_ppg](https://github.com/navidhasanzadeh/hypertension_ppg)| +|2308.02433|[contrastive self-supervised learning based approach for patient similarity: a case study on atrial fibrillation detection from ppg signal](https://arxiv.org/abs/2308.02433)|[simsig](https://github.com/subangkar/simsig)| ## 2023-08-03 -|paper|code| -|---|---| -|[bayesian algorithms for kronecker-structured sparse vector recovery with application to irs-mimo channel estimation](https://arxiv.org/abs/2307.14719)|[journalkrosbl](https://github.com/yanbinhe/journalkrosbl)| -|[can we transfer noise patterns? an multi-environment spectrum analysis model using generated cases](https://arxiv.org/abs/2308.01138)|[cnst](https://github.com/magnomic/cnst)| -|[llms4ol: large language models for ontology learning](https://arxiv.org/abs/2307.16648)|[llms4ol](https://github.com/hamedbabaei/llms4ol)| +|date|paper|code| +|---|---|---| +|2308.01138|[can we transfer noise patterns? an multi-environment spectrum analysis model using generated cases](https://arxiv.org/abs/2308.01138)|[cnst](https://github.com/magnomic/cnst)| ## 2023-08-02 -|paper|code| -|---|---| -|[an integrated multi-time-scale modeling for solar irradiance forecasting using deep learning](https://arxiv.org/abs/1905.02616)|[LSTM_Solar_Forecasting](https://github.com/sakshi-mishra/LSTM_Solar_Forecasting)| -|[vit2eeg: leveraging hybrid pretrained vision transformers for eeg data](https://arxiv.org/abs/2308.00454)|[eegeyenet-vit](https://github.com/ruiqirichard/eegeyenet-vit)| -|[data augmentation of bridging the delay gap for dl-based massive mimo csi feedback](https://arxiv.org/abs/2308.00478)|[crnetaug](https://github.com/zhanghy23/crnetaug)| -|[nystr\"om $m$-hilbert-schmidt independence criterion](https://arxiv.org/abs/2302.09930)|[nystroem-mhsic](https://github.com/flopska/nystroem-mhsic)| +|date|paper|code| +|---|---|---| +|2308.00454|[vit2eeg: leveraging hybrid pretrained vision transformers for eeg data](https://arxiv.org/abs/2308.00454)|[eegeyenet-vit](https://github.com/ruiqirichard/eegeyenet-vit)| +|2308.00478|[data augmentation of bridging the delay gap for dl-based massive mimo csi feedback](https://arxiv.org/abs/2308.00478)|[crnetaug](https://github.com/zhanghy23/crnetaug)| ## 2023-08-01 -|paper|code| -|---|---| -|[load modulation for backscatter communication: channel capacity and near-capacity schemes](https://arxiv.org/abs/2207.08100)|[backscatteratcapacity](https://github.com/grdu/backscatteratcapacity)| -|[matnilm: multi-appliance-task non-intrusive load monitoring with limited labeled data](https://arxiv.org/abs/2307.14778)|[matnilm](https://github.com/jxiong22/matnilm)| -|[ultrasound image reconstruction with denoising diffusion restoration models](https://arxiv.org/abs/2307.15990)|[drus-v1](https://github.com/yuxin-zhang-jasmine/drus-v1)| -|[rcs-yolo: a fast and high-accuracy object detector for brain tumor detection](https://arxiv.org/abs/2307.16412)|[rcs-yolo](https://github.com/mkang315/rcs-yolo)| -|[the representation jensen-shannon divergence](https://arxiv.org/abs/2305.16446)|[representationjsd](https://github.com/uk-cliplab/representationjsd)| -|[spherical and hyperbolic toric topology-based codes on graph embedding for ising mrf models: classical and quantum topology machine learning](https://arxiv.org/abs/2307.15778)|[Topology-Signal-Processing](https://github.com/Lcrypto/Topology-Signal-Processing)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/09.md b/archives/2023/09.md index e9574677..053def42 100644 --- a/archives/2023/09.md +++ b/archives/2023/09.md @@ -1,174 +1,125 @@ # September 2023 Archive ## 2023-09-29 -|paper|code| -|---|---| -|[motion-robust free-running cardiovascular mri](https://arxiv.org/abs/2308.02088)|[motion-robust-CMR](https://github.com/syedmurtazaarshad/motion-robust-CMR)| -|[optimal receive filter design for misaligned over-the-air computation](https://arxiv.org/abs/2309.16033)|[filteraircomp](https://github.com/henrikhellstrom93/filteraircomp)| -|[set learning for accurate and calibrated models](https://arxiv.org/abs/2307.02245)|[oko](https://github.com/lukasmut/oko)| -|[geometry of sensitivity: twice sampling and hybrid clipping in differential privacy with optimal gaussian noise and application to deep learning](https://arxiv.org/abs/2309.02672)|[twice_sampling_and_hybrid_clipping](https://github.com/hanshen-xiao/twice_sampling_and_hybrid_clipping)| -|[efficient computation of the quantum rate-distortion function](https://arxiv.org/abs/2309.15919)|[efficient-qrd](https://github.com/kerry-he/efficient-qrd)| +|date|paper|code| +|---|---|---| +|2309.16033|[optimal receive filter design for misaligned over-the-air computation](https://arxiv.org/abs/2309.16033)|[filteraircomp](https://github.com/henrikhellstrom93/filteraircomp)| +|2309.02672|[geometry of sensitivity: twice sampling and hybrid clipping in differential privacy with optimal gaussian noise and application to deep learning](https://arxiv.org/abs/2309.02672)|[twice_sampling_and_hybrid_clipping](https://github.com/hanshen-xiao/twice_sampling_and_hybrid_clipping)| +|2309.15919|[efficient computation of the quantum rate-distortion function](https://arxiv.org/abs/2309.15919)|[efficient-qrd](https://github.com/kerry-he/efficient-qrd)| ## 2023-09-28 -|paper|code| -|---|---| -|[data-driven identification of parametric governing equations of dynamical systems using the signed cumulative distribution transform](https://arxiv.org/abs/2308.12259)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| -|[fully adaptive time-varying wave-shape model: applications in biomedical signal processing](https://arxiv.org/abs/2309.15211)|[tvwse](https://github.com/joaquinr-uner/tvwse)| -|[scaling representation learning from ubiquitous ecg with state-space models](https://arxiv.org/abs/2309.15292)|[tiles_ecg_model](https://github.com/klean2050/tiles_ecg_model)| -|[investigating the changes in bold responses during viewing of images with varied complexity: an fmri time-series based analysis on human vision](https://arxiv.org/abs/2309.15495)|[fmri-time-series-classification](https://github.com/naveen7102/fmri-time-series-classification)| +|date|paper|code| +|---|---|---| +|2309.15211|[fully adaptive time-varying wave-shape model: applications in biomedical signal processing](https://arxiv.org/abs/2309.15211)|[tvwse](https://github.com/joaquinr-uner/tvwse)| +|2309.15292|[scaling representation learning from ubiquitous ecg with state-space models](https://arxiv.org/abs/2309.15292)|[tiles_ecg_model](https://github.com/klean2050/tiles_ecg_model)| +|2309.15495|[investigating the changes in bold responses during viewing of images with varied complexity: an fmri time-series based analysis on human vision](https://arxiv.org/abs/2309.15495)|[fmri-time-series-classification](https://github.com/naveen7102/fmri-time-series-classification)| ## 2023-09-27 -|paper|code| -|---|---| -|[joint communication and computation framework for goal-oriented semantic communication with distortion rate resilience](https://arxiv.org/abs/2309.14587)|[drgo-semcom](https://github.com/skyd-semantic/drgo-semcom)| +|date|paper|code| +|---|---|---| +|2309.14587|[joint communication and computation framework for goal-oriented semantic communication with distortion rate resilience](https://arxiv.org/abs/2309.14587)|[drgo-semcom](https://github.com/skyd-semantic/drgo-semcom)| ## 2023-09-26 -|paper|code| -|---|---| -|[a time-causal and time-recursive scale-covariant scale-space representation of temporal signals and past time](https://arxiv.org/abs/2202.09209)|[pytempscsp](https://github.com/tonylindeberg/pytempscsp)| -|[toward reliable signals decoding for electroencephalogram: a benchmark study to eegnex](https://arxiv.org/abs/2207.12369)|[eegnex](https://github.com/chenxiachan/eegnex)| -|[mm-fi: multi-modal non-intrusive 4d human dataset for versatile wireless sensing](https://arxiv.org/abs/2305.10345)|[mmfi_dataset](https://github.com/ybhbingo/mmfi_dataset)| -|[ecg-qa: a comprehensive question answering dataset combined with electrocardiogram](https://arxiv.org/abs/2306.15681)|[ecg-qa](https://github.com/jwoo5/ecg-qa)| -|[quantum and quantum-inspired stereographic k nearest-neighbour clustering](https://arxiv.org/abs/2308.03949)|[stereographic-quantum-embedding-clustering](https://github.com/alonsoviladomat/stereographic-quantum-embedding-clustering)| -|[functional graph contrastive learning of hyperscanning eeg reveals emotional contagion evoked by stereotype-based stressors](https://arxiv.org/abs/2308.13546)|[Functional-Graph-Contrastive-Learning-of-Hyperscanning-EEG](https://github.com/Maxwell-Wong/Functional-Graph-Contrastive-Learning-of-Hyperscanning-EEG)| -|[structure-preserving transformers for sequences of spd matrices](https://arxiv.org/abs/2309.07579)|[spdtransnet](https://github.com/mathieuseraphim/spdtransnet)| -|[bgf-yolo: enhanced yolov8 with multiscale attentional feature fusion for brain tumor detection](https://arxiv.org/abs/2309.12585)|[bgf-yolo](https://github.com/mkang315/bgf-yolo)| -|[finding order in chaos: a novel data augmentation method for time series in contrastive learning](https://arxiv.org/abs/2309.13439)|[Finding_Order_in_Chaos](https://github.com/eth-siplab/Finding_Order_in_Chaos)| -|[dnn-danm: a high-accuracy two-dimensional doa estimation method using practical ris](https://arxiv.org/abs/2309.13856)|[dnn-danm](https://github.com/chenpengseu/dnn-danm)| -|[single-antenna jammers in mimo-ofdm can resemble multi-antenna jammers](https://arxiv.org/abs/2309.14059)|[ofdm-jammer](https://github.com/iip-group/ofdm-jammer)| -|[partition and code: learning how to compress graphs](https://arxiv.org/abs/2107.01952)|[PnC](https://github.com/gbouritsas/PnC)| -|[a truly concurrent semantics for reversible ccs](https://arxiv.org/abs/2309.14011)|[reversible-ccs-as-nets](https://github.com/hmelgra/reversible-ccs-as-nets)| +|date|paper|code| +|---|---|---| +|2309.07579|[structure-preserving transformers for sequences of spd matrices](https://arxiv.org/abs/2309.07579)|[spdtransnet](https://github.com/mathieuseraphim/spdtransnet)| +|2309.12585|[bgf-yolo: enhanced yolov8 with multiscale attentional feature fusion for brain tumor detection](https://arxiv.org/abs/2309.12585)|[bgf-yolo](https://github.com/mkang315/bgf-yolo)| +|2309.13439|[finding order in chaos: a novel data augmentation method for time series in contrastive learning](https://arxiv.org/abs/2309.13439)|[Finding_Order_in_Chaos](https://github.com/eth-siplab/Finding_Order_in_Chaos)| +|2309.13856|[dnn-danm: a high-accuracy two-dimensional doa estimation method using practical ris](https://arxiv.org/abs/2309.13856)|[dnn-danm](https://github.com/chenpengseu/dnn-danm)| +|2309.14059|[single-antenna jammers in mimo-ofdm can resemble multi-antenna jammers](https://arxiv.org/abs/2309.14059)|[ofdm-jammer](https://github.com/iip-group/ofdm-jammer)| +|2309.14011|[a truly concurrent semantics for reversible ccs](https://arxiv.org/abs/2309.14011)|[reversible-ccs-as-nets](https://github.com/hmelgra/reversible-ccs-as-nets)| ## 2023-09-22 -|paper|code| -|---|---| -|[deep sound-field denoiser: optically-measured sound-field denoising using deep neural network](https://arxiv.org/abs/2304.14923)|[deep-sound-field-denoiser](https://github.com/nttcslab/deep-sound-field-denoiser)| -|[an f-ratio-based method for estimating the number of active sources in meg](https://arxiv.org/abs/2306.05892)|[fratio-based-method-for-source-enumeration](https://github.com/amita-giri/fratio-based-method-for-source-enumeration)| -|[limitations in odour recognition and generalisation in a neuromorphic olfactory circuit](https://arxiv.org/abs/2309.11555)|[eplnetwork_imamcleland2020](https://github.com/biomachinelearning/eplnetwork_imamcleland2020)| -|[a class-weighted supervised contrastive learning long-tailed bearing fault diagnosis approach using quadratic neural network](https://arxiv.org/abs/2309.11717)|[CCQNet](https://github.com/yuweien1120/CCQNet)| -|[dictionary attack on imu-based gait authentication](https://arxiv.org/abs/2309.11766)|[dictionaryattackonimugait](https://github.com/rajeshjnu2006/dictionaryattackonimugait)| -|[multimodal transformers for wireless communications: a case study in beam prediction](https://arxiv.org/abs/2309.11811)|[deepsense6g_tii](https://github.com/itu-ai-ml-in-5g-challenge/deepsense6g_tii)| -|[statistical mechanics of the maximum-average submatrix problem](https://arxiv.org/abs/2303.05237)|[Maximum-Average-Submatrix](https://github.com/SPOC-group/Maximum-Average-Submatrix)| -|[quantum conformal prediction for reliable uncertainty quantification in quantum machine learning](https://arxiv.org/abs/2304.03398)|[quantum-cp](https://github.com/kclip/quantum-cp)| +|date|paper|code| +|---|---|---| +|2309.11555|[limitations in odour recognition and generalisation in a neuromorphic olfactory circuit](https://arxiv.org/abs/2309.11555)|[eplnetwork_imamcleland2020](https://github.com/biomachinelearning/eplnetwork_imamcleland2020)| +|2309.11717|[a class-weighted supervised contrastive learning long-tailed bearing fault diagnosis approach using quadratic neural network](https://arxiv.org/abs/2309.11717)|[CCQNet](https://github.com/yuweien1120/CCQNet)| +|2309.11766|[dictionary attack on imu-based gait authentication](https://arxiv.org/abs/2309.11766)|[dictionaryattackonimugait](https://github.com/rajeshjnu2006/dictionaryattackonimugait)| +|2309.11811|[multimodal transformers for wireless communications: a case study in beam prediction](https://arxiv.org/abs/2309.11811)|[deepsense6g_tii](https://github.com/itu-ai-ml-in-5g-challenge/deepsense6g_tii)| ## 2023-09-21 -|paper|code| -|---|---| -|[online learning of the transfer matrix of dynamic scattering media: wavefront shaping meets multidimensional time series](https://arxiv.org/abs/2210.04033)|[online_learning_tm](https://github.com/labogigan/online_learning_tm)| -|[on the formation of min-weight codewords of polar/pac codes and its applications](https://arxiv.org/abs/2111.08843)|[Error-Coefficient-reduced-Polar-PAC-Codes](https://github.com/mohammad-rowshan/Error-Coefficient-reduced-Polar-PAC-Codes)| -|[towards disentangling information paths with coded resnext](https://arxiv.org/abs/2202.05343)|[coded-resnext](https://github.com/avranasa/coded-resnext)| -|[stein variational guided model predictive path integral control: proposal and experiments with fast maneuvering vehicles](https://arxiv.org/abs/2309.11040)|[proj-svg_mppi](https://github.com/kohonda/proj-svg_mppi)| +|date|paper|code| +|---|---|---| +|2309.11040|[stein variational guided model predictive path integral control: proposal and experiments with fast maneuvering vehicles](https://arxiv.org/abs/2309.11040)|[proj-svg_mppi](https://github.com/kohonda/proj-svg_mppi)| ## 2023-09-20 -|paper|code| -|---|---| -|[trajectory pmb filters for extended object tracking using belief propagation](https://arxiv.org/abs/2207.10164)|[trajectory-pmb-eot-bp](https://github.com/yuhsuansia/trajectory-pmb-eot-bp)| -|[electrocardioguard: preventing patient misidentification in electrocardiogram databases through neural networks](https://arxiv.org/abs/2306.06196)|[electrocardioguard](https://github.com/captaintrojan/electrocardioguard)| -|[a new method of modeling the multi-stage decision-making process of crt using machine learning with uncertainty quantification](https://arxiv.org/abs/2309.08415)|[crt_multistageml_uncertainty](https://github.com/miilab-mtu/crt_multistageml_uncertainty)| -|[mixed graph signal analysis of joint image denoising / interpolation](https://arxiv.org/abs/2309.10114)|[icassp24-joint](https://github.com/sybernix/icassp24-joint)| -|[unsupervised speech enhancement with diffusion-based generative models](https://arxiv.org/abs/2309.10450)|[sgmse](https://github.com/sp-uhh/sgmse)| +|date|paper|code| +|---|---|---| +|2309.08415|[a new method of modeling the multi-stage decision-making process of crt using machine learning with uncertainty quantification](https://arxiv.org/abs/2309.08415)|[crt_multistageml_uncertainty](https://github.com/miilab-mtu/crt_multistageml_uncertainty)| +|2309.10114|[mixed graph signal analysis of joint image denoising / interpolation](https://arxiv.org/abs/2309.10114)|[icassp24-joint](https://github.com/sybernix/icassp24-joint)| +|2309.10450|[unsupervised speech enhancement with diffusion-based generative models](https://arxiv.org/abs/2309.10450)|[sgmse](https://github.com/sp-uhh/sgmse)| ## 2023-09-19 -|paper|code| -|---|---| -|[frequency estimation using complex-valued shifted window transformer](https://arxiv.org/abs/2309.09352)|[spectral-super-resolution-swin](https://github.com/josiahwsmith10/spectral-super-resolution-swin)| -|[scaling the time and fourier domains to align periodically and their convolution](https://arxiv.org/abs/2309.09645)|[fxt](https://github.com/flatmax/fxt)| -|[vontss: vmf based semi-supervised neural topic modeling with optimal transport](https://arxiv.org/abs/2307.01226)|[vONTSS](https://github.com/xuweijieshuai/vONTSS)| +|date|paper|code| +|---|---|---| +|2309.09352|[frequency estimation using complex-valued shifted window transformer](https://arxiv.org/abs/2309.09352)|[spectral-super-resolution-swin](https://github.com/josiahwsmith10/spectral-super-resolution-swin)| +|2309.09645|[scaling the time and fourier domains to align periodically and their convolution](https://arxiv.org/abs/2309.09645)|[fxt](https://github.com/flatmax/fxt)| ## 2023-09-18 -|paper|code| -|---|---| -|[validation of the reference impedance in multiline calibration with stepped impedance standards](https://arxiv.org/abs/2209.09163)|[verification-multiline-trl-calibration](https://github.com/ZiadHatab/verification-multiline-trl-calibration)| -|[closed loop bci system for cybathlon 2020](https://arxiv.org/abs/2212.04172)|[GoPar](https://github.com/kolcs/GoPar)| -|[structure-preserving transformers for sequences of spd matrices](https://arxiv.org/abs/2309.07579)|[spdtransnet](https://github.com/mathieuseraphim/spdtransnet)| -|[transmusic: a transformer-aided subspace method for doa estimation with low-resolution adcs](https://arxiv.org/abs/2309.08174)|[transformer_music](https://github.com/jijunkai/transformer_music)| -|[gaussian processes with linear multiple kernel: spectrum design and distributed learning for multi-dimensional data](https://arxiv.org/abs/2309.08201)|[distributed-gsm](https://github.com/richardcsuwandi/distributed-gsm)| -|[deep nonnegative matrix factorization with beta divergences](https://arxiv.org/abs/2309.08249)|[deep-kl-nmf-public](https://github.com/vleplat/deep-kl-nmf-public)| -|[the multi-cluster fluctuating two-ray fading model](https://arxiv.org/abs/2212.02448)|[mftr-fading-channel-model](https://github.com/josedavidvega/mftr-fading-channel-model)| +|date|paper|code| +|---|---|---| +|2309.07579|[structure-preserving transformers for sequences of spd matrices](https://arxiv.org/abs/2309.07579)|[spdtransnet](https://github.com/mathieuseraphim/spdtransnet)| +|2309.08174|[transmusic: a transformer-aided subspace method for doa estimation with low-resolution adcs](https://arxiv.org/abs/2309.08174)|[transformer_music](https://github.com/jijunkai/transformer_music)| +|2309.08201|[gaussian processes with linear multiple kernel: spectrum design and distributed learning for multi-dimensional data](https://arxiv.org/abs/2309.08201)|[distributed-gsm](https://github.com/richardcsuwandi/distributed-gsm)| +|2309.08249|[deep nonnegative matrix factorization with beta divergences](https://arxiv.org/abs/2309.08249)|[deep-kl-nmf-public](https://github.com/vleplat/deep-kl-nmf-public)| ## 2023-09-15 -|paper|code| -|---|---| -|[toward reliable signals decoding for electroencephalogram: a benchmark study to eegnex](https://arxiv.org/abs/2207.12369)|[eegnex](https://github.com/chenxiachan/eegnex)| -|[adaptive kalmannet: data-driven kalman filter with fast adaptation](https://arxiv.org/abs/2309.07016)|[adaptive-knet-icassp24](https://github.com/kalmannet/adaptive-knet-icassp24)| -|[self-supervised blind source separation via multi-encoder autoencoders](https://arxiv.org/abs/2309.07138)|[self-supervised-bss-via-multi-encoder-ae](https://github.com/webstah/self-supervised-bss-via-multi-encoder-ae)| -|[pypvroof: a python package for extracting the characteristics of rooftop pv installations using remote sensing data](https://arxiv.org/abs/2309.07143)|[pypvroof](https://github.com/gabrielkasmi/pypvroof)| -|[a strong and simple deep learning baseline for bci mi decoding](https://arxiv.org/abs/2309.07159)|[eegsimpleconv](https://github.com/elouayas/eegsimpleconv)| -|[predicting survival time of ball bearings in the presence of censoring](https://arxiv.org/abs/2309.07188)|[ball-bearing-survival](https://github.com/thecml/ball-bearing-survival)| -|[a densenet-based method for decoding auditory spatial attention with eeg](https://arxiv.org/abs/2309.07690)|[asad_densenet](https://github.com/xuxiran/asad_densenet)| +|date|paper|code| +|---|---|---| +|2309.07016|[adaptive kalmannet: data-driven kalman filter with fast adaptation](https://arxiv.org/abs/2309.07016)|[adaptive-knet-icassp24](https://github.com/kalmannet/adaptive-knet-icassp24)| +|2309.07138|[self-supervised blind source separation via multi-encoder autoencoders](https://arxiv.org/abs/2309.07138)|[self-supervised-bss-via-multi-encoder-ae](https://github.com/webstah/self-supervised-bss-via-multi-encoder-ae)| +|2309.07143|[pypvroof: a python package for extracting the characteristics of rooftop pv installations using remote sensing data](https://arxiv.org/abs/2309.07143)|[pypvroof](https://github.com/gabrielkasmi/pypvroof)| +|2309.07159|[a strong and simple deep learning baseline for bci mi decoding](https://arxiv.org/abs/2309.07159)|[eegsimpleconv](https://github.com/elouayas/eegsimpleconv)| +|2309.07188|[predicting survival time of ball bearings in the presence of censoring](https://arxiv.org/abs/2309.07188)|[ball-bearing-survival](https://github.com/thecml/ball-bearing-survival)| +|2309.07690|[a densenet-based method for decoding auditory spatial attention with eeg](https://arxiv.org/abs/2309.07690)|[asad_densenet](https://github.com/xuxiran/asad_densenet)| ## 2023-09-14 -|paper|code| -|---|---| -|[is channel estimation necessary to select phase-shifts for ris-assisted massive mimo?](https://arxiv.org/abs/2106.09770)|[ris-massive-mimo](https://github.com/emilbjornson/ris-massive-mimo)| -|[a spectral analysis of graph neural networks on dense and sparse graphs](https://arxiv.org/abs/2211.03231)|[gnn_community_detection](https://github.com/nhuang37/gnn_community_detection)| -|[nuv-doa: nuv prior-based bayesian sparse reconstruction with spatial filtering for super-resolution doa estimation](https://arxiv.org/abs/2309.03114)|[ICASSP24-NUV-DoA](https://github.com/MengyuanZha0/ICASSP24-NUV-DoA)| -|[bayesian topology inference on partially known networks from input-output pairs](https://arxiv.org/abs/2309.06532)|[inference_langevin](https://github.com/tenceto/inference_langevin)| -|[a worker-task specialization model for crowdsourcing: efficient inference and fundamental limits](https://arxiv.org/abs/2111.12550)|[dtype](https://github.com/iids88/dtype)| -|[multiple-access channel coding with non-signaling correlations](https://arxiv.org/abs/2206.10968)|[mac_ns_lp](https://github.com/pferme/mac_ns_lp)| +|date|paper|code| +|---|---|---| +|2309.03114|[nuv-doa: nuv prior-based bayesian sparse reconstruction with spatial filtering for super-resolution doa estimation](https://arxiv.org/abs/2309.03114)|[ICASSP24-NUV-DoA](https://github.com/MengyuanZha0/ICASSP24-NUV-DoA)| +|2309.06532|[bayesian topology inference on partially known networks from input-output pairs](https://arxiv.org/abs/2309.06532)|[inference_langevin](https://github.com/tenceto/inference_langevin)| ## 2023-09-13 -|paper|code| -|---|---| -|[task-oriented communication for multi-device cooperative edge inference](https://arxiv.org/abs/2109.00172)|[vddib-sr](https://github.com/shaojiawei07/vddib-sr)| -|[reinforcement learning for supply chain attacks against frequency and voltage control](https://arxiv.org/abs/2309.05814)|[rl-cps-attacks](https://github.com/amrmsab/rl-cps-attacks)| -|[concurrent composition for interactive differential privacy with adaptive privacy-loss parameters](https://arxiv.org/abs/2309.05901)|[concurrent-composition](https://github.com/concurrent-composition/concurrent-composition)| -|[chebyshev particles](https://arxiv.org/abs/2309.06373)|[chebyshevparticles](https://github.com/986876245/chebyshevparticles)| +|date|paper|code| +|---|---|---| +|2309.05814|[reinforcement learning for supply chain attacks against frequency and voltage control](https://arxiv.org/abs/2309.05814)|[rl-cps-attacks](https://github.com/amrmsab/rl-cps-attacks)| +|2309.05901|[concurrent composition for interactive differential privacy with adaptive privacy-loss parameters](https://arxiv.org/abs/2309.05901)|[concurrent-composition](https://github.com/concurrent-composition/concurrent-composition)| +|2309.06373|[chebyshev particles](https://arxiv.org/abs/2309.06373)|[chebyshevparticles](https://github.com/986876245/chebyshevparticles)| ## 2023-09-12 -|paper|code| -|---|---| -|[hermes: hybrid error-corrector model with inclusion of external signals for nonstationary fashion time series](https://arxiv.org/abs/2202.03224)|[hermes](https://github.com/etidav/hermes)| -|[efficient and scalable parametric high-order portfolios design via the skew-t distribution](https://arxiv.org/abs/2206.02412)|[highOrderPortfolios](https://github.com/dppalomar/highOrderPortfolios)| -|[efficient ecg-based atrial fibrillation detection via parameterised hypercomplex neural networks](https://arxiv.org/abs/2211.02678)|[hypercomplexecg](https://github.com/leibniz-future-lab/hypercomplexecg)| -|[task-oriented communication for edge video analytics](https://arxiv.org/abs/2211.14049)|[tocom-tem](https://github.com/shaojiawei07/tocom-tem)| -|[physics-informed neural networks for prognostics and health management of lithium-ion batteries](https://arxiv.org/abs/2301.00776)|[PINN-Battery-Prognostics](https://github.com/WenPengfei0823/PINN-Battery-Prognostics)| -|[audioldm: text-to-audio generation with latent diffusion models](https://arxiv.org/abs/2301.12503)|[AudioLDM](https://github.com/haoheliu/AudioLDM)| -|[deep metric learning for the hemodynamics inference with electrocardiogram signals](https://arxiv.org/abs/2308.04650)|[ssldml](https://github.com/mandiehyewon/ssldml)| -|[audioldm 2: learning holistic audio generation with self-supervised pretraining](https://arxiv.org/abs/2308.05734)|[AudioLDM2](https://github.com/haoheliu/AudioLDM2)| -|[ecg-based estimation of respiratory modulation of av nodal conduction during atrial fibrillation](https://arxiv.org/abs/2309.05458)|[ecg-based_estimation_of_respiratory_modulation_of_av_nodal_conduction_during_atrial_fibrillation](https://github.com/plappertf/ecg-based_estimation_of_respiratory_modulation_of_av_nodal_conduction_during_atrial_fibrillation)| -|[the information geometry of umap](https://arxiv.org/abs/2309.01237)|[info-geometry-umap](https://github.com/sashakolpakov/info-geometry-umap)| -|[perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning](https://arxiv.org/abs/2309.04626)|[paq](https://github.com/austinxu87/paq)| +|date|paper|code| +|---|---|---| +|2309.05458|[ecg-based estimation of respiratory modulation of av nodal conduction during atrial fibrillation](https://arxiv.org/abs/2309.05458)|[ecg-based_estimation_of_respiratory_modulation_of_av_nodal_conduction_during_atrial_fibrillation](https://github.com/plappertf/ecg-based_estimation_of_respiratory_modulation_of_av_nodal_conduction_during_atrial_fibrillation)| +|2309.01237|[the information geometry of umap](https://arxiv.org/abs/2309.01237)|[info-geometry-umap](https://github.com/sashakolpakov/info-geometry-umap)| +|2309.04626|[perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning](https://arxiv.org/abs/2309.04626)|[paq](https://github.com/austinxu87/paq)| ## 2023-09-11 -|paper|code| -|---|---| -|[data-driven classification of low-power communication signals by an unauthenticated user using a software-defined radio](https://arxiv.org/abs/2309.04088)|[jammingsdr](https://github.com/minds-code/jammingsdr)| -|[prista-net: deep iterative shrinkage thresholding network for coded diffraction patterns phase retrieval](https://arxiv.org/abs/2309.04171)|[prista-net](https://github.com/liuaxou/prista-net)| +|date|paper|code| +|---|---|---| +|2309.04088|[data-driven classification of low-power communication signals by an unauthenticated user using a software-defined radio](https://arxiv.org/abs/2309.04088)|[jammingsdr](https://github.com/minds-code/jammingsdr)| +|2309.04171|[prista-net: deep iterative shrinkage thresholding network for coded diffraction patterns phase retrieval](https://arxiv.org/abs/2309.04171)|[prista-net](https://github.com/liuaxou/prista-net)| ## 2023-09-08 -|paper|code| -|---|---| -|[watch this space: securing satellite communication through resilient transmitter fingerprinting](https://arxiv.org/abs/2305.06947)|[SatIQ](https://github.com/ssloxford/SatIQ)| -|[dynamic causal graph convolutional network for traffic prediction](https://arxiv.org/abs/2306.07019)|[DCGCN](https://github.com/MonBG/DCGCN)| +|date|paper|code| +|---|---|---| ## 2023-09-07 -|paper|code| -|---|---| -|[load modulation for backscatter communication: channel capacity and near-capacity schemes](https://arxiv.org/abs/2207.08100)|[backscatteratcapacity](https://github.com/grdu/backscatteratcapacity)| -|[manifold filter-combine networks](https://arxiv.org/abs/2307.04056)|[mfcn](https://github.com/krishnaswamylab/mfcn)| -|[distributed variational inference for online supervised learning](https://arxiv.org/abs/2309.02606)|[distributed-mapping](https://github.com/pptx/distributed-mapping)| -|[symmetric-reciprocal-match method for vector network analyzer calibration](https://arxiv.org/abs/2309.02886)|[srm-calibration](https://github.com/ZiadHatab/srm-calibration)| -|[uncertainty quantification in deep learning based kalman filters](https://arxiv.org/abs/2309.03058)|[Uncertainty-extraction-in-Model-Based-DL](https://github.com/yonatandn/Uncertainty-extraction-in-Model-Based-DL)| -|[spherical and hyperbolic toric topology-based codes on graph embedding for ising mrf models: classical and quantum topology machine learning](https://arxiv.org/abs/2307.15778)|[classical-and-quantum-topology-ml-toric-spherical](https://github.com/lcrypto/classical-and-quantum-topology-ml-toric-spherical)| +|date|paper|code| +|---|---|---| +|2309.02606|[distributed variational inference for online supervised learning](https://arxiv.org/abs/2309.02606)|[distributed-mapping](https://github.com/pptx/distributed-mapping)| +|2309.02886|[symmetric-reciprocal-match method for vector network analyzer calibration](https://arxiv.org/abs/2309.02886)|[srm-calibration](https://github.com/ZiadHatab/srm-calibration)| +|2309.03058|[uncertainty quantification in deep learning based kalman filters](https://arxiv.org/abs/2309.03058)|[Uncertainty-extraction-in-Model-Based-DL](https://github.com/yonatandn/Uncertainty-extraction-in-Model-Based-DL)| ## 2023-09-06 -|paper|code| -|---|---| -|[generalized minimum error entropy for adaptive filtering](https://arxiv.org/abs/2109.03463)|[Generalized-minimum-error-entropy-for-robust-learning](https://github.com/Asmallorange123/Generalized-minimum-error-entropy-for-robust-learning)| -|[towards efficient modeling and inference in multi-dimensional gaussian process state-space models](https://arxiv.org/abs/2309.01074)|[gpssmproj](https://github.com/zhidilin/gpssmproj)| +|date|paper|code| +|---|---|---| +|2309.01074|[towards efficient modeling and inference in multi-dimensional gaussian process state-space models](https://arxiv.org/abs/2309.01074)|[gpssmproj](https://github.com/zhidilin/gpssmproj)| ## 2023-09-04 -|paper|code| -|---|---| -|[validation of the reference impedance in multiline calibration with stepped impedance standards](https://arxiv.org/abs/2209.09163)|[verification-multiline-trl-calibration](https://github.com/ZiadHatab/verification-multiline-trl-calibration)| -|[neural augmented kalman filtering with bollinger bands for pairs trading](https://arxiv.org/abs/2210.15448)|[kalmanbot_icassp23](https://github.com/kalmannet/kalmanbot_icassp23)| -|[from prediction markets to interpretable collective intelligence](https://arxiv.org/abs/2204.13424)|[collective-intelligence-research](https://github.com/nicknick85/collective-intelligence-research)| +|date|paper|code| +|---|---|---| ## 2023-09-01 -|paper|code| -|---|---| -|[principled pruning of bayesian neural networks through variational free energy minimization](https://arxiv.org/abs/2210.09134)|[principledpruningbnn](https://github.com/biaslab/principledpruningbnn)| -|[phonmatchnet: phoneme-guided zero-shot keyword spotting for user-defined keywords](https://arxiv.org/abs/2308.16511)|[phonmatchnet](https://github.com/ncsoft/phonmatchnet)| -|[time-varying quasi-closed-phase analysis for accurate formant tracking in speech signals](https://arxiv.org/abs/2308.16540)|[ftrack](https://github.com/njaygowda/ftrack)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/10.md b/archives/2023/10.md index 7ec665aa..8df2e13f 100644 --- a/archives/2023/10.md +++ b/archives/2023/10.md @@ -1,175 +1,125 @@ # October 2023 Archive ## 2023-10-31 -|paper|code| -|---|---| -|[ipdp: on partial dependence plots in dynamic modeling scenarios](https://arxiv.org/abs/2306.07775)|[ipdp-on-partial-dependence-plots-in-dynamic-modeling-scenarios](https://github.com/mmschlk/ipdp-on-partial-dependence-plots-in-dynamic-modeling-scenarios)| -|[optimal status updates for minimizing age of correlated information in iot networks with energy harvesting sensors](https://arxiv.org/abs/2310.19216)|[RSS_algorithm](https://github.com/CXU-NWAFU/RSS_algorithm)| -|[kernelized cumulants: beyond kernel mean embeddings](https://arxiv.org/abs/2301.12466)|[kernelized-cumulants](https://github.com/patricbonnier/kernelized-cumulants)| -|[quantifying & modeling multimodal interactions: an information decomposition framework](https://arxiv.org/abs/2302.12247)|[pid](https://github.com/pliang279/pid)| -|[compression with bayesian implicit neural representations](https://arxiv.org/abs/2305.19185)|[combiner](https://github.com/cambridge-mlg/combiner)| -|[exact optimality of communication-privacy-utility tradeoffs in distributed mean estimation](https://arxiv.org/abs/2306.04924)|[rrsc](https://github.com/BerivanIsik/rrsc)| -|[boosting learning for ldpc codes to improve the error-floor performance](https://arxiv.org/abs/2310.07194)|[ldpc_error_floor](https://github.com/ghy1228/ldpc_error_floor)| -|[estimating the rate-distortion function by wasserstein gradient descent](https://arxiv.org/abs/2310.18908)|[wgd](https://github.com/yiboyang/wgd)| -|[learn to categorize or categorize to learn? self-coding for generalized category discovery](https://arxiv.org/abs/2310.19776)|[infosieve](https://github.com/sarahrastegar/infosieve)| +|date|paper|code| +|---|---|---| +|2310.19216|[optimal status updates for minimizing age of correlated information in iot networks with energy harvesting sensors](https://arxiv.org/abs/2310.19216)|[RSS_algorithm](https://github.com/CXU-NWAFU/RSS_algorithm)| +|2310.07194|[boosting learning for ldpc codes to improve the error-floor performance](https://arxiv.org/abs/2310.07194)|[ldpc_error_floor](https://github.com/ghy1228/ldpc_error_floor)| +|2310.18908|[estimating the rate-distortion function by wasserstein gradient descent](https://arxiv.org/abs/2310.18908)|[wgd](https://github.com/yiboyang/wgd)| +|2310.19776|[learn to categorize or categorize to learn? self-coding for generalized category discovery](https://arxiv.org/abs/2310.19776)|[infosieve](https://github.com/sarahrastegar/infosieve)| ## 2023-10-30 -|paper|code| -|---|---| -|[novel models for multiple dependent heteroskedastic time series](https://arxiv.org/abs/2310.17760)|[stat40710](https://github.com/13204942/stat40710)| +|date|paper|code| +|---|---|---| +|2310.17760|[novel models for multiple dependent heteroskedastic time series](https://arxiv.org/abs/2310.17760)|[stat40710](https://github.com/13204942/stat40710)| ## 2023-10-27 -|paper|code| -|---|---| -|[statistical component separation for targeted signal recovery in noisy mixtures](https://arxiv.org/abs/2306.15012)|[stat_comp_sep](https://github.com/bregaldo/stat_comp_sep)| -|[path weight sampling: exact monte carlo computation of the mutual information between stochastic trajectories](https://arxiv.org/abs/2203.03461)|[pathweightsampling.jl](https://github.com/manuel-rhdt/pathweightsampling.jl)| -|[a neural collapse perspective on feature evolution in graph neural networks](https://arxiv.org/abs/2307.01951)|[gnn_collapse](https://github.com/kvignesh1420/gnn_collapse)| +|date|paper|code| +|---|---|---| ## 2023-10-26 -|paper|code| -|---|---| -|[learning bilinear models of actuated koopman generators from partially-observed trajectories](https://arxiv.org/abs/2209.09977)|[koopmangeneratorem](https://github.com/samotto1/koopmangeneratorem)| +|date|paper|code| +|---|---|---| ## 2023-10-25 -|paper|code| -|---|---| -|[incremental measurement of structural entropy for dynamic graphs](https://arxiv.org/abs/2207.12653)|[incre-se](https://github.com/yangrunze1013/incre-se)| +|date|paper|code| +|---|---|---| ## 2023-10-24 -|paper|code| -|---|---| -|[gasper: graph signal processing in r](https://arxiv.org/abs/2007.10642)|[SGWT-SURE](https://github.com/fabnavarro/SGWT-SURE)| -|[riscatter: unifying backscatter communication and reconfigurable intelligent surface](https://arxiv.org/abs/2212.09121)|[riscatter](https://github.com/snowztail/riscatter)| -|[learning informative representation for fairness-aware multivariate time-series forecasting: a group-based perspective](https://arxiv.org/abs/2301.11535)|[fairfor](https://github.com/huihevv/fairfor)| -|[distributed variational inference for online supervised learning](https://arxiv.org/abs/2309.02606)|[distributed-mapping](https://github.com/pptx/distributed-mapping)| -|[learning state-augmented policies for information routing in communication networks](https://arxiv.org/abs/2310.00248)|[state-augmeted-information-routing](https://github.com/sourajitdas/state-augmeted-information-routing)| -|[federated learning compression designed for lightweight communications](https://arxiv.org/abs/2310.14693)|[fl_exps](https://github.com/lgrativol/fl_exps)| -|[quantum conformal prediction for reliable uncertainty quantification in quantum machine learning](https://arxiv.org/abs/2304.03398)|[quantum-cp](https://github.com/kclip/quantum-cp)| -|[vontss: vmf based semi-supervised neural topic modeling with optimal transport](https://arxiv.org/abs/2307.01226)|[vONTSS](https://github.com/xuweijieshuai/vONTSS)| -|[teleqna: a benchmark dataset to assess large language models telecommunications knowledge](https://arxiv.org/abs/2310.15051)|[teleqna](https://github.com/netop-team/teleqna)| +|date|paper|code| +|---|---|---| +|2310.00248|[learning state-augmented policies for information routing in communication networks](https://arxiv.org/abs/2310.00248)|[state-augmeted-information-routing](https://github.com/sourajitdas/state-augmeted-information-routing)| +|2310.14693|[federated learning compression designed for lightweight communications](https://arxiv.org/abs/2310.14693)|[fl_exps](https://github.com/lgrativol/fl_exps)| +|2310.15051|[teleqna: a benchmark dataset to assess large language models telecommunications knowledge](https://arxiv.org/abs/2310.15051)|[teleqna](https://github.com/netop-team/teleqna)| ## 2023-10-23 -|paper|code| -|---|---| -|[equivariant bootstrapping for uncertainty quantification in imaging inverse problems](https://arxiv.org/abs/2310.11838)|[equivariant_bootstrap](https://github.com/tachella/equivariant_bootstrap)| -|[a lego-brick approach to coding for network communication](https://arxiv.org/abs/2211.07208)|[lego-brick](https://github.com/nadimgh/lego-brick)| +|date|paper|code| +|---|---|---| +|2310.11838|[equivariant bootstrapping for uncertainty quantification in imaging inverse problems](https://arxiv.org/abs/2310.11838)|[equivariant_bootstrap](https://github.com/tachella/equivariant_bootstrap)| ## 2023-10-20 -|paper|code| -|---|---| -|[mutual information-based integrated sensing and communications: a wmmse framework](https://arxiv.org/abs/2310.12686)|[MI-based-WMMSE-ISAC-algorithm](https://github.com/ROCASSO/MI-based-WMMSE-ISAC-algorithm)| -|[semantic: semantic interference cancellation towards 6g wireless communications](https://arxiv.org/abs/2310.12768)|[SemantIC](https://github.com/linwest/SemantIC)| +|date|paper|code| +|---|---|---| +|2310.12686|[mutual information-based integrated sensing and communications: a wmmse framework](https://arxiv.org/abs/2310.12686)|[MI-based-WMMSE-ISAC-algorithm](https://github.com/ROCASSO/MI-based-WMMSE-ISAC-algorithm)| +|2310.12768|[semantic: semantic interference cancellation towards 6g wireless communications](https://arxiv.org/abs/2310.12768)|[SemantIC](https://github.com/linwest/SemantIC)| ## 2023-10-19 -|paper|code| -|---|---| -|[compression with bayesian implicit neural representations](https://arxiv.org/abs/2305.19185)|[combiner](https://github.com/cambridge-mlg/combiner)| -|[perceptual measurements, distances and metrics](https://arxiv.org/abs/2310.11759)|[perceptual_metric](https://github.com/jonathanvacher/perceptual_metric)| +|date|paper|code| +|---|---|---| +|2310.11759|[perceptual measurements, distances and metrics](https://arxiv.org/abs/2310.11759)|[perceptual_metric](https://github.com/jonathanvacher/perceptual_metric)| ## 2023-10-18 -|paper|code| -|---|---| -|[removing structured noise with diffusion models](https://arxiv.org/abs/2302.05290)|[joint-diffusion](https://github.com/tristan-deep/joint-diffusion)| -|[correlative information maximization: a biologically plausible approach to supervised deep neural networks without weight symmetry](https://arxiv.org/abs/2306.04810)|[Supervised-CorInfoMax](https://github.com/BariscanBozkurt/Supervised-CorInfoMax)| +|date|paper|code| +|---|---|---| ## 2023-10-17 -|paper|code| -|---|---| -|[unique sparse decomposition of low rank matrices](https://arxiv.org/abs/2106.07736)|[Unique_Fac_of_Low_Rank](https://github.com/Jindiande/Unique_Fac_of_Low_Rank)| -|[semi-supervised end-to-end learning for integrated sensing and communications](https://arxiv.org/abs/2310.09940)|[sslisac](https://github.com/josemateosramos/sslisac)| -|[autodeconj: a gpu accelerated imagej plugin for 3d light field deconvolution with optimal iteration numbers predicting](https://arxiv.org/abs/2208.11422)|[autodeconj](https://github.com/onetism/autodeconj)| -|[beyond normal: on the evaluation of mutual information estimators](https://arxiv.org/abs/2306.11078)|[bmi](https://github.com/cbg-ethz/bmi)| -|[the mixtures and the neural critics: on the pointwise mutual information profiles of fine distributions](https://arxiv.org/abs/2310.10240)|[bmi](https://github.com/cbg-ethz/bmi)| +|date|paper|code| +|---|---|---| +|2310.09940|[semi-supervised end-to-end learning for integrated sensing and communications](https://arxiv.org/abs/2310.09940)|[sslisac](https://github.com/josemateosramos/sslisac)| +|2310.10240|[the mixtures and the neural critics: on the pointwise mutual information profiles of fine distributions](https://arxiv.org/abs/2310.10240)|[bmi](https://github.com/cbg-ethz/bmi)| ## 2023-10-16 -|paper|code| -|---|---| -|[learning rl-policies for joint beamforming without exploration: a batch constrained off-policy approach](https://arxiv.org/abs/2310.08660)|[safe-rl-deployment-for-5g](https://github.com/heasung-kim/safe-rl-deployment-for-5g)| -|[multi-sensor multi-scan radar sensing of multiple extended targets](https://arxiv.org/abs/2310.09011)|[di-gsncp-radar-sensing](https://github.com/martin497/di-gsncp-radar-sensing)| -|[revisiting minimum description length complexity in overparameterized models](https://arxiv.org/abs/2006.10189)|[mdl-complexity](https://github.com/csinva/mdl-complexity)| -|[task-aware distributed source coding under dynamic bandwidth](https://arxiv.org/abs/2305.15523)|[task-aware-distributed-source-coding](https://github.com/utaustin-swarmlab/task-aware-distributed-source-coding)| +|date|paper|code| +|---|---|---| +|2310.08660|[learning rl-policies for joint beamforming without exploration: a batch constrained off-policy approach](https://arxiv.org/abs/2310.08660)|[safe-rl-deployment-for-5g](https://github.com/heasung-kim/safe-rl-deployment-for-5g)| +|2310.09011|[multi-sensor multi-scan radar sensing of multiple extended targets](https://arxiv.org/abs/2310.09011)|[di-gsncp-radar-sensing](https://github.com/martin497/di-gsncp-radar-sensing)| ## 2023-10-13 -|paper|code| -|---|---| -|[semantic-forward relaying: a novel framework towards 6g cooperative communications](https://arxiv.org/abs/2310.07987)|[Semantic_Forward](https://github.com/linwest/Semantic_Forward)| -|[interpretable diffusion via information decomposition](https://arxiv.org/abs/2310.07972)|[info-decomp](https://github.com/kxh001/info-decomp)| -|[fast search method for large polarization kernels](https://arxiv.org/abs/2310.08369)|[kernelbruteforcer](https://github.com/gtrofimiuk/kernelbruteforcer)| +|date|paper|code| +|---|---|---| +|2310.07987|[semantic-forward relaying: a novel framework towards 6g cooperative communications](https://arxiv.org/abs/2310.07987)|[Semantic_Forward](https://github.com/linwest/Semantic_Forward)| +|2310.07972|[interpretable diffusion via information decomposition](https://arxiv.org/abs/2310.07972)|[info-decomp](https://github.com/kxh001/info-decomp)| +|2310.08369|[fast search method for large polarization kernels](https://arxiv.org/abs/2310.08369)|[kernelbruteforcer](https://github.com/gtrofimiuk/kernelbruteforcer)| ## 2023-10-12 -|paper|code| -|---|---| -|[multi-kernel correntropy-based orientation estimation of imus: gradient descent methods](https://arxiv.org/abs/2304.06548)|[mc_gd_imu](https://github.com/lsl-zsj/mc_gd_imu)| -|[ecg-qa: a comprehensive question answering dataset combined with electrocardiogram](https://arxiv.org/abs/2306.15681)|[ecg-qa](https://github.com/jwoo5/ecg-qa)| -|[reconfigurable intelligent surfaces-enabled intra-cell pilot reuse in massive mimo systems](https://arxiv.org/abs/2310.06975)|[ris-pilot-reuse](https://github.com/josecarlos-marinello/ris-pilot-reuse)| -|[brain age revisited: investigating the state vs. trait hypotheses of eeg-derived brain-age dynamics with deep learning](https://arxiv.org/abs/2310.07029)|[eeg-brain-age](https://github.com/gemeinl/eeg-brain-age)| -|[uncovering ecg changes during healthy aging using explainable ai](https://arxiv.org/abs/2310.07463)|[ecg-aging](https://github.com/ai4healthuol/ecg-aging)| -|[boosting learning for ldpc codes to improve the error-floor performance](https://arxiv.org/abs/2310.07194)|[ldpc_error_floor](https://github.com/ghy1228/ldpc_error_floor)| -|[functional renormalization group for signal detection and stochastic ergodicity breaking](https://arxiv.org/abs/2310.07499)|[stochastic-signal-detection](https://github.com/thesfinox/stochastic-signal-detection)| +|date|paper|code| +|---|---|---| +|2310.06975|[reconfigurable intelligent surfaces-enabled intra-cell pilot reuse in massive mimo systems](https://arxiv.org/abs/2310.06975)|[ris-pilot-reuse](https://github.com/josecarlos-marinello/ris-pilot-reuse)| +|2310.07029|[brain age revisited: investigating the state vs. trait hypotheses of eeg-derived brain-age dynamics with deep learning](https://arxiv.org/abs/2310.07029)|[eeg-brain-age](https://github.com/gemeinl/eeg-brain-age)| +|2310.07463|[uncovering ecg changes during healthy aging using explainable ai](https://arxiv.org/abs/2310.07463)|[ecg-aging](https://github.com/ai4healthuol/ecg-aging)| +|2310.07194|[boosting learning for ldpc codes to improve the error-floor performance](https://arxiv.org/abs/2310.07194)|[ldpc_error_floor](https://github.com/ghy1228/ldpc_error_floor)| +|2310.07499|[functional renormalization group for signal detection and stochastic ergodicity breaking](https://arxiv.org/abs/2310.07499)|[stochastic-signal-detection](https://github.com/thesfinox/stochastic-signal-detection)| ## 2023-10-11 -|paper|code| -|---|---| -|[tiny-ppg: a lightweight deep neural network for real-time detection of motion artifacts in photoplethysmogram signals on edge devices](https://arxiv.org/abs/2305.03308)|[tiny-ppg](https://github.com/sztu-wearable/tiny-ppg)| -|[branched latent neural maps](https://arxiv.org/abs/2308.02599)|[blnm.jl](https://github.com/stanfordcbcl/blnm.jl)| -|[isac 4d imaging system based on 5g downlink millimeter wave signal](https://arxiv.org/abs/2310.06401)|[ISAC_4D_IMaging](https://github.com/MrHaobolu/ISAC_4D_IMaging)| -|[s4sleep: elucidating the design space of deep-learning-based sleep stage classification models](https://arxiv.org/abs/2310.06715)|[s4sleep](https://github.com/ai4healthuol/s4sleep)| +|date|paper|code| +|---|---|---| +|2310.06401|[isac 4d imaging system based on 5g downlink millimeter wave signal](https://arxiv.org/abs/2310.06401)|[ISAC_4D_IMaging](https://github.com/MrHaobolu/ISAC_4D_IMaging)| +|2310.06715|[s4sleep: elucidating the design space of deep-learning-based sleep stage classification models](https://arxiv.org/abs/2310.06715)|[s4sleep](https://github.com/ai4healthuol/s4sleep)| ## 2023-10-10 -|paper|code| -|---|---| -|[neural vocoder is all you need for speech super-resolution](https://arxiv.org/abs/2203.14941)|[ssr_eval](https://github.com/haoheliu/ssr_eval)| -|[voicefixer: a unified framework for high-fidelity speech restoration](https://arxiv.org/abs/2204.05841)|[voicefixer](https://github.com/haoheliu/voicefixer)| -|[distributed deep joint source-channel coding over a multiple access channel](https://arxiv.org/abs/2211.09920)|[deepjscc-noma](https://github.com/ipc-lab/deepjscc-noma)| -|[ontology-aware learning and evaluation for audio tagging](https://arxiv.org/abs/2211.12195)|[ontology-aware-audio-tagging](https://github.com/haoheliu/ontology-aware-audio-tagging)| -|[the first cadenza signal processing challenge: improving music for those with a hearing loss](https://arxiv.org/abs/2310.05799)|[task1](https://github.com/claritychallenge/clarity/tree/main/recipes/cad1/task1)| -|[estimating conditional mutual information for dynamic feature selection](https://arxiv.org/abs/2306.03301)|[dime](https://github.com/suinleelab/dime)| +|date|paper|code| +|---|---|---| +|2310.05799|[the first cadenza signal processing challenge: improving music for those with a hearing loss](https://arxiv.org/abs/2310.05799)|[task1](https://github.com/claritychallenge/clarity/tree/main/recipes/cad1/task1)| ## 2023-10-09 -|paper|code| -|---|---| -|[link scheduling using graph neural networks](https://arxiv.org/abs/2109.05536)|[distgcn](https://github.com/zhongyuanzhao/distgcn)| -|[a comprehensive indoor environment dataset from single-family houses in the us](https://arxiv.org/abs/2310.03771)|[bdl_data_1](https://github.com/anik801/bdl_data_1)| +|date|paper|code| +|---|---|---| +|2310.03771|[a comprehensive indoor environment dataset from single-family houses in the us](https://arxiv.org/abs/2310.03771)|[bdl_data_1](https://github.com/anik801/bdl_data_1)| ## 2023-10-06 -|paper|code| -|---|---| -|[accoustate: auto-annotation of imu-generated activity signatures under smart infrastructure](https://arxiv.org/abs/2112.06651)|[acconotate](https://github.com/stilllearningsoumya/acconotate)| -|[conditional generative models for simulation of emg during naturalistic movements](https://arxiv.org/abs/2211.01856)|[biomime](https://github.com/shihan-ma/biomime)| -|[learning and communications co-design for remote inference systems: feature length selection and transmission scheduling](https://arxiv.org/abs/2308.10094)|[impact-of-data-freshness-in-learning](https://github.com/kamran0153/impact-of-data-freshness-in-learning)| -|[procedural text mining with large language models](https://arxiv.org/abs/2310.03376)|[proc-tm](https://github.com/jd-coderepos/proc-tm)| +|date|paper|code| +|---|---|---| +|2310.03376|[procedural text mining with large language models](https://arxiv.org/abs/2310.03376)|[proc-tm](https://github.com/jd-coderepos/proc-tm)| ## 2023-10-05 -|paper|code| -|---|---| -|[path weight sampling: exact monte carlo computation of the mutual information between stochastic trajectories](https://arxiv.org/abs/2203.03461)|[pathweightsampling.jl](https://github.com/manuel-rhdt/pathweightsampling.jl)| -|[on the financial consequences of simplified battery sizing models without considering operational details](https://arxiv.org/abs/2310.02494)|[community-battery-sizing-study](https://github.com/nam-dinh-codes/community-battery-sizing-study)| -|[local max-entropy and free energy principles, belief diffusions and their singularities](https://arxiv.org/abs/2310.02946)|[topos](https://github.com/opeltre/topos)| +|date|paper|code| +|---|---|---| +|2310.02494|[on the financial consequences of simplified battery sizing models without considering operational details](https://arxiv.org/abs/2310.02494)|[community-battery-sizing-study](https://github.com/nam-dinh-codes/community-battery-sizing-study)| +|2310.02946|[local max-entropy and free energy principles, belief diffusions and their singularities](https://arxiv.org/abs/2310.02946)|[topos](https://github.com/opeltre/topos)| ## 2023-10-04 -|paper|code| -|---|---| -|[maximum likelihood based phase-retrieval using fresnel propagation forward models with optional constraints](https://arxiv.org/abs/2305.00334)|[phasetorch](https://github.com/phasetorch/phasetorch)| -|[rcs-yolo: a fast and high-accuracy object detector for brain tumor detection](https://arxiv.org/abs/2307.16412)|[rcs-yolo](https://github.com/mkang315/rcs-yolo)| -|[multi-static isac in cell-free massive mimo: precoder design and privacy assessment](https://arxiv.org/abs/2309.13368)|[globecom2023](https://github.com/isabella-gomes/globecom2023)| -|[the representation jensen-shannon divergence](https://arxiv.org/abs/2305.16446)|[representationjsd](https://github.com/uk-cliplab/representationjsd)| +|date|paper|code| +|---|---|---| ## 2023-10-03 -|paper|code| -|---|---| -|[short-length ssvep data extension by a novel generative adversarial networks based framework](https://arxiv.org/abs/2301.05599)|[tegan](https://github.com/yudongpan/tegan)| -|[branched latent neural maps](https://arxiv.org/abs/2308.02599)|[blnm.jl](https://github.com/stanfordcbcl/blnm.jl)| -|[learning state-augmented policies for information routing in communication networks](https://arxiv.org/abs/2310.00248)|[state-augmeted-information-routing](https://github.com/sourajitdas/state-augmeted-information-routing)| -|[an efficient algorithm for clustered multi-task compressive sensing](https://arxiv.org/abs/2310.00420)|[multics](https://github.com/al5250/multics)| -|[revisiting minimum description length complexity in overparameterized models](https://arxiv.org/abs/2006.10189)|[mdl-complexity](https://github.com/csinva/mdl-complexity)| -|[minimising the expected posterior entropy yields optimal summary statistics](https://arxiv.org/abs/2206.02340)|[summaries](https://github.com/tillahoffmann/summaries)| -|[task-aware distributed source coding under dynamic bandwidth](https://arxiv.org/abs/2305.15523)|[task-aware-distributed-source-coding](https://github.com/utaustin-swarmlab/task-aware-distributed-source-coding)| -|[age of information in slotted aloha with energy harvesting](https://arxiv.org/abs/2310.00348)|[aoi_slottedaloha_energyharvesting](https://github.com/khachoang1412/aoi_slottedaloha_energyharvesting)| -|[mining java memory errors using subjective interesting subgroups with hierarchical targets](https://arxiv.org/abs/2310.00781)|[sca-miner](https://github.com/remilyoucef/sca-miner)| +|date|paper|code| +|---|---|---| +|2310.00248|[learning state-augmented policies for information routing in communication networks](https://arxiv.org/abs/2310.00248)|[state-augmeted-information-routing](https://github.com/sourajitdas/state-augmeted-information-routing)| +|2310.00420|[an efficient algorithm for clustered multi-task compressive sensing](https://arxiv.org/abs/2310.00420)|[multics](https://github.com/al5250/multics)| +|2310.00348|[age of information in slotted aloha with energy harvesting](https://arxiv.org/abs/2310.00348)|[aoi_slottedaloha_energyharvesting](https://github.com/khachoang1412/aoi_slottedaloha_energyharvesting)| +|2310.00781|[mining java memory errors using subjective interesting subgroups with hierarchical targets](https://arxiv.org/abs/2310.00781)|[sca-miner](https://github.com/remilyoucef/sca-miner)| ## 2023-10-02 -|paper|code| -|---|---| -|[accelerated motion correction with deep generative diffusion models](https://arxiv.org/abs/2211.00199)|[motion_score_mri](https://github.com/utcsilab/motion_score_mri)| -|[learning large-scale mtp$_2$ gaussian graphical models via bridge-block decomposition](https://arxiv.org/abs/2309.13405)|[mtp2-bbd](https://github.com/xiwen1997/mtp2-bbd)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/11.md b/archives/2023/11.md index f589696a..958d75c5 100644 --- a/archives/2023/11.md +++ b/archives/2023/11.md @@ -1,153 +1,112 @@ # November 2023 Archive ## 2023-11-30 -|paper|code| -|---|---| -|[zero-shot self-supervised learning for mri reconstruction](https://arxiv.org/abs/2102.07737)|[ZS-SSL](https://github.com/byaman14/ZS-SSL)| -|[fast and expressive gesture recognition using a combination-homomorphic electromyogram encoder](https://arxiv.org/abs/2311.14675)|[com-hom-emg](https://github.com/nik-sm/com-hom-emg)| -|[rigorous dynamical mean field theory for stochastic gradient descent methods](https://arxiv.org/abs/2210.06591)|[rigorous-dynamical-mean-field-theory](https://github.com/spoc-group/rigorous-dynamical-mean-field-theory)| -|[quantifying the redundancy between prosody and text](https://arxiv.org/abs/2311.17233)|[quantifying-redundancy](https://github.com/lu-wo/quantifying-redundancy)| +|date|paper|code| +|---|---|---| +|2311.14675|[fast and expressive gesture recognition using a combination-homomorphic electromyogram encoder](https://arxiv.org/abs/2311.14675)|[com-hom-emg](https://github.com/nik-sm/com-hom-emg)| +|2311.17233|[quantifying the redundancy between prosody and text](https://arxiv.org/abs/2311.17233)|[quantifying-redundancy](https://github.com/lu-wo/quantifying-redundancy)| ## 2023-11-29 -|paper|code| -|---|---| -|[foundations of user-centric cell-free massive mimo](https://arxiv.org/abs/2108.02541)|[cell-free-book](https://github.com/emilbjornson/cell-free-book)| +|date|paper|code| +|---|---|---| ## 2023-11-28 -|paper|code| -|---|---| -|[towards interpretable sleep stage classification using cross-modal transformers](https://arxiv.org/abs/2208.06991)|[cross-modal-transformer](https://github.com/jathurshan0330/cross-modal-transformer)| -|[a distributed block-split gibbs sampler with hypergraph structure for high-dimensional inverse problems](https://arxiv.org/abs/2210.02341)|[dsgs](https://gitlab.cristal.univ-lille.fr/pthouven/dsgs)| -|[optimal discrete beamforming of ris-aided wireless communications: an inner product maximization approach](https://arxiv.org/abs/2211.04167)|[RIS_Optimization](https://github.com/RujingXiong/RIS_Optimization)| -|[data augmentation for generating synthetic electrogastrogram time series](https://arxiv.org/abs/2303.02408)|[syegg](https://github.com/nadicasm/syegg)| -|[deda: deep directed accumulator](https://arxiv.org/abs/2303.08434)|[deda](https://github.com/tinymilky/deda)| -|[robust joint estimation of galaxy redshift and spectral templates using online dictionary learning](https://arxiv.org/abs/2311.14812)|[bryanetal2023](https://github.com/hyperspectraldictionarylearning/bryanetal2023)| -|[mpcnn: a novel matrix profile approach for cnn-based sleep apnea classification](https://arxiv.org/abs/2311.15041)|[mpcnn-sleep-apnea](https://github.com/vinuni-vishc/mpcnn-sleep-apnea)| -|[learning multi-frequency partial correlation graphs](https://arxiv.org/abs/2311.15756)|[bspcg](https://github.com/officiallydac/bspcg)| -|[autoregressive language models for estimating the entropy of epic ehr audit logs](https://arxiv.org/abs/2311.06401)|[audit-log-lm](https://github.com/bcwarner/audit-log-lm)| +|date|paper|code| +|---|---|---| +|2311.14812|[robust joint estimation of galaxy redshift and spectral templates using online dictionary learning](https://arxiv.org/abs/2311.14812)|[bryanetal2023](https://github.com/hyperspectraldictionarylearning/bryanetal2023)| +|2311.15041|[mpcnn: a novel matrix profile approach for cnn-based sleep apnea classification](https://arxiv.org/abs/2311.15041)|[mpcnn-sleep-apnea](https://github.com/vinuni-vishc/mpcnn-sleep-apnea)| +|2311.15756|[learning multi-frequency partial correlation graphs](https://arxiv.org/abs/2311.15756)|[bspcg](https://github.com/officiallydac/bspcg)| +|2311.06401|[autoregressive language models for estimating the entropy of epic ehr audit logs](https://arxiv.org/abs/2311.06401)|[audit-log-lm](https://github.com/bcwarner/audit-log-lm)| ## 2023-11-27 -|paper|code| -|---|---| -|[non-stationary transformers: exploring the stationarity in time series forecasting](https://arxiv.org/abs/2205.14415)|[Nonstationary_Transformers](https://github.com/thuml/Nonstationary_Transformers)| -|[single-shot quantum signal processing interferometry](https://arxiv.org/abs/2311.13703)|[qsp-interferometry](https://github.com/yuanliu1/qsp-interferometry)| -|[windformer:bi-directional long-distance spatio-temporal network for wind speed prediction](https://arxiv.org/abs/2311.14316)|[windformer](https://github.com/szwszwszw123/windformer)| -|[kernel-based tests for likelihood-free hypothesis testing](https://arxiv.org/abs/2308.09043)|[lfi](https://github.com/sr-11/lfi)| +|date|paper|code| +|---|---|---| +|2311.13703|[single-shot quantum signal processing interferometry](https://arxiv.org/abs/2311.13703)|[qsp-interferometry](https://github.com/yuanliu1/qsp-interferometry)| +|2311.14316|[windformer:bi-directional long-distance spatio-temporal network for wind speed prediction](https://arxiv.org/abs/2311.14316)|[windformer](https://github.com/szwszwszw123/windformer)| ## 2023-11-23 -|paper|code| -|---|---| -|[high-power and safe rf wireless charging: cautious deployment and operation](https://arxiv.org/abs/2311.12809)|[high_power_and_safe_wpt](https://github.com/onel2428/high_power_and_safe_wpt)| -|[applying dimensionality reduction as precursor to lstm-cnn models for classifying imagery and motor signals in ecog-based bcis](https://arxiv.org/abs/2311.13507)|[dim-reduction-with-cnn-lstm](https://github.com/bafanas/dim-reduction-with-cnn-lstm)| +|date|paper|code| +|---|---|---| +|2311.12809|[high-power and safe rf wireless charging: cautious deployment and operation](https://arxiv.org/abs/2311.12809)|[high_power_and_safe_wpt](https://github.com/onel2428/high_power_and_safe_wpt)| +|2311.13507|[applying dimensionality reduction as precursor to lstm-cnn models for classifying imagery and motor signals in ecog-based bcis](https://arxiv.org/abs/2311.13507)|[dim-reduction-with-cnn-lstm](https://github.com/bafanas/dim-reduction-with-cnn-lstm)| ## 2023-11-22 -|paper|code| -|---|---| -|[ssvep-dan: a data alignment network for ssvep-based brain computer interfaces](https://arxiv.org/abs/2311.12666)|[ssvep-dan](https://github.com/cecnl/ssvep-dan)| +|date|paper|code| +|---|---|---| +|2311.12666|[ssvep-dan: a data alignment network for ssvep-based brain computer interfaces](https://arxiv.org/abs/2311.12666)|[ssvep-dan](https://github.com/cecnl/ssvep-dan)| ## 2023-11-21 -|paper|code| -|---|---| -|[rtsnet: learning to smooth in partially known state-space models](https://arxiv.org/abs/2110.04717)|[rtsnet_tsp](https://github.com/kalmannet/rtsnet_tsp)| -|[hkf: hierarchical kalman filtering with online learned evolution priors for adaptive ecg denoising](https://arxiv.org/abs/2210.12807)|[hkf_icassp23](https://github.com/kalmannet/hkf_icassp23)| -|[outage performance and novel loss function for an ml-assisted resource allocation: an exact analytical framework](https://arxiv.org/abs/2305.09739)|[greedy-resource-allocation-outage-classification](https://github.com/ml4comms/greedy-resource-allocation-outage-classification)| -|[source-free domain adaptation for ssvep-based brain-computer interfaces](https://arxiv.org/abs/2305.17403)|[sfda-ssvep-bci](https://github.com/osmanberke/sfda-ssvep-bci)| -|[estimation of entropy-regularized optimal transport maps between non-compactly supported measures](https://arxiv.org/abs/2311.11934)|[entropic-map](https://github.com/mattwerenski/entropic-map)| +|date|paper|code| +|---|---|---| +|2311.11934|[estimation of entropy-regularized optimal transport maps between non-compactly supported measures](https://arxiv.org/abs/2311.11934)|[entropic-map](https://github.com/mattwerenski/entropic-map)| ## 2023-11-20 -|paper|code| -|---|---| -|[modeling and correcting bias in sequential evaluation](https://arxiv.org/abs/2205.01607)|[sequential-bias](https://github.com/jingyanw/sequential-bias)| -|[temporally causal discovery tests for discrete time series and neural spike trains](https://arxiv.org/abs/2305.14131)|[github_temporal_causality](https://github.com/andreas947/github_temporal_causality)| +|date|paper|code| +|---|---|---| ## 2023-11-17 -|paper|code| -|---|---| -|[learning to reconstruct signals from binary measurements](https://arxiv.org/abs/2303.08691)|[ssbm](https://github.com/tachella/ssbm)| +|date|paper|code| +|---|---|---| ## 2023-11-16 -|paper|code| -|---|---| -|[data-driven identification of parametric governing equations of dynamical systems using the signed cumulative distribution transform](https://arxiv.org/abs/2308.12259)|[PyTransKit](https://github.com/rohdelab/PyTransKit)| -|[topology of surface electromyogram signals: hand gesture decoding on riemannian manifolds](https://arxiv.org/abs/2311.08548)|[geometryofsemg](https://github.com/harshavardhanatg/geometryofsemg)| +|date|paper|code| +|---|---|---| +|2311.08548|[topology of surface electromyogram signals: hand gesture decoding on riemannian manifolds](https://arxiv.org/abs/2311.08548)|[geometryofsemg](https://github.com/harshavardhanatg/geometryofsemg)| ## 2023-11-15 -|paper|code| -|---|---| -|[cslp-ae: a contrastive split-latent permutation autoencoder framework for zero-shot electroencephalography signal conversion](https://arxiv.org/abs/2311.07788)|[cslp-ae](https://github.com/andersxa/cslp-ae)| +|date|paper|code| +|---|---|---| +|2311.07788|[cslp-ae: a contrastive split-latent permutation autoencoder framework for zero-shot electroencephalography signal conversion](https://arxiv.org/abs/2311.07788)|[cslp-ae](https://github.com/andersxa/cslp-ae)| ## 2023-11-14 -|paper|code| -|---|---| -|[signal2image modules in deep neural networks for eeg classification](https://arxiv.org/abs/1904.13216)|[signal2image-modules-in-deep-neural-networks-for-eeg-classification](https://github.com/pbizopoulos/signal2image-modules-in-deep-neural-networks-for-eeg-classification)| -|[data-driven denoising of stationary accelerometer signals](https://arxiv.org/abs/2206.05937)|[MEMS-IMU-Denoising](https://github.com/ansfl/MEMS-IMU-Denoising)| -|[hkf: hierarchical kalman filtering with online learned evolution priors for adaptive ecg denoising](https://arxiv.org/abs/2210.12807)|[hkf_icassp23](https://github.com/kalmannet/hkf_icassp23)| -|[convolutional monge mapping normalization for learning on sleep data](https://arxiv.org/abs/2305.18831)|[convolutional-monge-mapping-normalization](https://github.com/pythonot/convolutional-monge-mapping-normalization)| -|[alpcah: sample-wise heteroscedastic pca with tail singular value regularization](https://arxiv.org/abs/2307.02745)|[alpcah](https://github.com/javiersc1/alpcah)| -|[successive linear approximation vbi for joint sparse signal recovery and dynamic grid parameters estimation](https://arxiv.org/abs/2307.09149)|[sla-vbi](https://github.com/zju-xwk/sla-vbi)| -|[learning rl-policies for joint beamforming without exploration: a batch constrained off-policy approach](https://arxiv.org/abs/2310.08660)|[safe-rl-deployment-for-5g](https://github.com/heasung-kim/safe-rl-deployment-for-5g)| -|[chatgpt in the context of precision agriculture data analytics](https://arxiv.org/abs/2311.06390)|[chatgpt-in-the-context-of-precision-agriculture-data-analytics](https://github.com/potamitis123/chatgpt-in-the-context-of-precision-agriculture-data-analytics)| -|[caster: a computer-vision-assisted wireless channel simulator for gesture recognition](https://arxiv.org/abs/2311.07169)|[testspectrogram](https://github.com/rzy0901/testspectrogram)| +|date|paper|code| +|---|---|---| +|2311.06390|[chatgpt in the context of precision agriculture data analytics](https://arxiv.org/abs/2311.06390)|[chatgpt-in-the-context-of-precision-agriculture-data-analytics](https://github.com/potamitis123/chatgpt-in-the-context-of-precision-agriculture-data-analytics)| +|2311.07169|[caster: a computer-vision-assisted wireless channel simulator for gesture recognition](https://arxiv.org/abs/2311.07169)|[testspectrogram](https://github.com/rzy0901/testspectrogram)| ## 2023-11-13 -|paper|code| -|---|---| -|[abs+ polar codes: exploiting more linear transforms on adjacent bits](https://arxiv.org/abs/2209.02461)|[abs-polar](https://github.com/plumjelly/abs-polar)| -|[in-context learning for mimo equalization using transformer-based sequence models](https://arxiv.org/abs/2311.06101)|[icl-equalization](https://github.com/kclip/icl-equalization)| +|date|paper|code| +|---|---|---| +|2311.06101|[in-context learning for mimo equalization using transformer-based sequence models](https://arxiv.org/abs/2311.06101)|[icl-equalization](https://github.com/kclip/icl-equalization)| ## 2023-11-10 -|paper|code| -|---|---| -|[principled pruning of bayesian neural networks through variational free energy minimization](https://arxiv.org/abs/2210.09134)|[principledpruningbnn](https://github.com/biaslab/principledpruningbnn)| -|[spectral cross-domain neural network with soft-adaptive threshold spectral enhancement](https://arxiv.org/abs/2301.10171)|[scdnn-ts](https://github.com/dl-wg/scdnn-ts)| -|[pay less but get more: a dual-attention-based channel estimation network for massive mimo systems with low-density pilots](https://arxiv.org/abs/2303.00986)|[dacen](https://github.com/bgzhou/dacen)| -|[eeg-dg: a multi-source domain generalization framework for motor imagery eeg classification](https://arxiv.org/abs/2311.05415)|[eeg-dg](https://github.com/xc-zhonghit/eeg-dg)| -|[uncertainty-aware bayes' rule and its applications](https://arxiv.org/abs/2311.05532)|[bayes-rule](https://github.com/spratm-asleaf/bayes-rule)| +|date|paper|code| +|---|---|---| +|2311.05415|[eeg-dg: a multi-source domain generalization framework for motor imagery eeg classification](https://arxiv.org/abs/2311.05415)|[eeg-dg](https://github.com/xc-zhonghit/eeg-dg)| +|2311.05532|[uncertainty-aware bayes' rule and its applications](https://arxiv.org/abs/2311.05532)|[bayes-rule](https://github.com/spratm-asleaf/bayes-rule)| ## 2023-11-09 -|paper|code| -|---|---| -|[exploring best practices for ecg signal processing in machine learning](https://arxiv.org/abs/2311.04229)|[ecg_augmentation](https://github.com/imilas/ecg_augmentation)| -|[discerning and enhancing the weighted sum-rate maximization algorithms in communications](https://arxiv.org/abs/2311.04546)|[ratemax](https://github.com/zepengzhang/ratemax)| +|date|paper|code| +|---|---|---| +|2311.04229|[exploring best practices for ecg signal processing in machine learning](https://arxiv.org/abs/2311.04229)|[ecg_augmentation](https://github.com/imilas/ecg_augmentation)| +|2311.04546|[discerning and enhancing the weighted sum-rate maximization algorithms in communications](https://arxiv.org/abs/2311.04546)|[ratemax](https://github.com/zepengzhang/ratemax)| ## 2023-11-08 -|paper|code| -|---|---| -|[score-based source separation with applications to digital communication signals](https://arxiv.org/abs/2306.14411)|[score_based_source_separation](https://github.com/tkj516/score_based_source_separation)| -|[classification of various types of damages in honeycomb composite sandwich structures using guided wave structural health monitoring](https://arxiv.org/abs/2311.03765)|[damage-classification-using-feature-engineering](https://github.com/shrutisawant099/damage-classification-using-feature-engineering)| -|[the fairness stitch: unveiling the potential of model stitching in neural network de-biasing](https://arxiv.org/abs/2311.03532)|[the_fairness_stitch](https://github.com/modar7/the_fairness_stitch)| +|date|paper|code| +|---|---|---| +|2311.03765|[classification of various types of damages in honeycomb composite sandwich structures using guided wave structural health monitoring](https://arxiv.org/abs/2311.03765)|[damage-classification-using-feature-engineering](https://github.com/shrutisawant099/damage-classification-using-feature-engineering)| +|2311.03532|[the fairness stitch: unveiling the potential of model stitching in neural network de-biasing](https://arxiv.org/abs/2311.03532)|[the_fairness_stitch](https://github.com/modar7/the_fairness_stitch)| ## 2023-11-07 -|paper|code| -|---|---| -|[gacs-korner common information variational autoencoder](https://arxiv.org/abs/2205.12239)|[common-vae](https://github.com/mjkleinman/common-vae)| -|[learn to categorize or categorize to learn? self-coding for generalized category discovery](https://arxiv.org/abs/2310.19776)|[infosieve](https://github.com/sarahrastegar/infosieve)| +|date|paper|code| +|---|---|---| ## 2023-11-06 -|paper|code| -|---|---| -|[vehicular visible light positioning for collision avoidance and platooning: a survey](https://arxiv.org/abs/2010.09858)|[vehicular-vlp-simulations](https://github.com/sonebu/vehicular-vlp-simulations)| +|date|paper|code| +|---|---|---| ## 2023-11-03 -|paper|code| -|---|---| -|[exclusive group lasso for structured variable selection](https://arxiv.org/abs/2108.10284)|[exclusive-lasso](https://github.com/gregdvd/exclusive-lasso)| -|[a ris-based vehicle doa estimation method with integrated sensing and communication system](https://arxiv.org/abs/2204.11626)|[passivedoa-isac-ris](https://github.com/chenpengseu/passivedoa-isac-ris)| -|[representing edge flows on graphs via sparse cell complexes](https://arxiv.org/abs/2309.01632)|[edge-flow-cell-complexes](https://github.com/josefhoppe/edge-flow-cell-complexes)| -|[improving robustness via tilted exponential layer: a communication-theoretic perspective](https://arxiv.org/abs/2311.01047)|[texp_for_robustness](https://github.com/bhagyapuranik/texp_for_robustness)| +|date|paper|code| +|---|---|---| +|2311.01047|[improving robustness via tilted exponential layer: a communication-theoretic perspective](https://arxiv.org/abs/2311.01047)|[texp_for_robustness](https://github.com/bhagyapuranik/texp_for_robustness)| ## 2023-11-02 -|paper|code| -|---|---| -|[robust waveform design for integrated sensing and communication](https://arxiv.org/abs/2311.00071)|[robust-waveform](https://github.com/spratm-asleaf/robust-waveform)| -|[generating hsr bogie vibration signals via pulse voltage-guided conditional diffusion model](https://arxiv.org/abs/2311.00496)|[vgcdm](https://github.com/xuanliu2000/vgcdm)| +|date|paper|code| +|---|---|---| +|2311.00071|[robust waveform design for integrated sensing and communication](https://arxiv.org/abs/2311.00071)|[robust-waveform](https://github.com/spratm-asleaf/robust-waveform)| +|2311.00496|[generating hsr bogie vibration signals via pulse voltage-guided conditional diffusion model](https://arxiv.org/abs/2311.00496)|[vgcdm](https://github.com/xuanliu2000/vgcdm)| ## 2023-11-01 -|paper|code| -|---|---| -|[a multimodal sensing ring for quantification of scratch intensity](https://arxiv.org/abs/2302.03813)|[wearable_scratch_intensity](https://github.com/rchi-lab/wearable_scratch_intensity)| -|[message passing meets graph neural networks: a new paradigm for massive mimo systems](https://arxiv.org/abs/2302.06896)|[amp_gnn](https://github.com/hehengtao/amp_gnn)| -|[on the impact of control signaling in ris-empowered wireless communications](https://arxiv.org/abs/2303.16797)|[ris-control](https://github.com/lostinafro/ris-control)| -|[energy-aware adaptive sampling for self-sustainability in resource-constrained iot devices](https://arxiv.org/abs/2310.20331)|[EcoTrack](https://github.com/ETH-PBL/EcoTrack)| -|[efficient computation of the quantum rate-distortion function](https://arxiv.org/abs/2309.15919)|[efficient-qrd](https://github.com/kerry-he/efficient-qrd)| +|date|paper|code| +|---|---|---| diff --git a/archives/2023/12.md b/archives/2023/12.md index d3ed56f3..8238f0f0 100644 --- a/archives/2023/12.md +++ b/archives/2023/12.md @@ -1,174 +1,131 @@ # December 2023 Archive ## 2023-12-29 -|paper|code| -|---|---| -|[gasper: graph signal processing in r](https://arxiv.org/abs/2007.10642)|[SGWT-SURE](https://github.com/fabnavarro/SGWT-SURE)| -|[robust kalman filters based on the sub-gaussian $\alpha$-stable distribution](https://arxiv.org/abs/2305.07890)|[robust-kalman-filters-based-on-the-sub-gaussian-alpha-stable-distribution](https://github.com/pengchengh/robust-kalman-filters-based-on-the-sub-gaussian-alpha-stable-distribution)| -|[robofisense: attention-based robotic arm activity recognition with wifi sensing](https://arxiv.org/abs/2312.15345)|[robofisense](https://github.com/siamilab/robofisense)| -|[a generalization of the convolution theorem and its connections to non-stationarity and the graph frequency domain](https://arxiv.org/abs/2312.16922)|[genconv](https://github.com/albertonat/genconv)| -|[efficient physics-based learned reconstruction methods for real-time 3d near-field mimo radar imaging](https://arxiv.org/abs/2312.16959)|[efficient-learned-3d-near-field-mimo-imaging](https://github.com/metu-space-lab/efficient-learned-3d-near-field-mimo-imaging)| +|date|paper|code| +|---|---|---| +|2312.15345|[robofisense: attention-based robotic arm activity recognition with wifi sensing](https://arxiv.org/abs/2312.15345)|[robofisense](https://github.com/siamilab/robofisense)| +|2312.16922|[a generalization of the convolution theorem and its connections to non-stationarity and the graph frequency domain](https://arxiv.org/abs/2312.16922)|[genconv](https://github.com/albertonat/genconv)| +|2312.16959|[efficient physics-based learned reconstruction methods for real-time 3d near-field mimo radar imaging](https://arxiv.org/abs/2312.16959)|[efficient-learned-3d-near-field-mimo-imaging](https://github.com/metu-space-lab/efficient-learned-3d-near-field-mimo-imaging)| ## 2023-12-27 -|paper|code| -|---|---| -|[nuv-doa: nuv prior-based bayesian sparse reconstruction with spatial filtering for super-resolution doa estimation](https://arxiv.org/abs/2309.03114)|[ICASSP24-NUV-DoA](https://github.com/MengyuanZha0/ICASSP24-NUV-DoA)| -|[sparsity-aware distributed learning for gaussian processes with linear multiple kernel](https://arxiv.org/abs/2309.08201)|[distributed-gsm](https://github.com/richardcsuwandi/distributed-gsm)| -|[ensemble kalman filtering-aided variational inference for gaussian process state-space models](https://arxiv.org/abs/2312.05910)|[gpssmproj](https://github.com/zhidilin/gpssmproj)| -|[harmonics of learning: universal fourier features emerge in invariant networks](https://arxiv.org/abs/2312.08550)|[spectral-universality](https://github.com/sophiaas/spectral-universality)| -|[a refining underlying information framework for monaural speech enhancement](https://arxiv.org/abs/2312.11201)|[rui_se](https://github.com/caoruitju/rui_se)| -|[robust stochastically-descending unrolled networks](https://arxiv.org/abs/2312.15788)|[unrolledglow](https://github.com/smrhadou/unrolledglow)| +|date|paper|code| +|---|---|---| +|2312.05910|[ensemble kalman filtering-aided variational inference for gaussian process state-space models](https://arxiv.org/abs/2312.05910)|[gpssmproj](https://github.com/zhidilin/gpssmproj)| +|2312.08550|[harmonics of learning: universal fourier features emerge in invariant networks](https://arxiv.org/abs/2312.08550)|[spectral-universality](https://github.com/sophiaas/spectral-universality)| +|2312.11201|[a refining underlying information framework for monaural speech enhancement](https://arxiv.org/abs/2312.11201)|[rui_se](https://github.com/caoruitju/rui_se)| +|2312.15788|[robust stochastically-descending unrolled networks](https://arxiv.org/abs/2312.15788)|[unrolledglow](https://github.com/smrhadou/unrolledglow)| ## 2023-12-25 -|paper|code| -|---|---| -|[geo2sigmap: high-fidelity rf signal mapping using geographic databases](https://arxiv.org/abs/2312.14303)|[geo2sigmap](https://github.com/functions-lab/geo2sigmap)| -|[instantaneous frequency estimation in multicomponent signals in case of interference based on the prony method](https://arxiv.org/abs/2312.14500)|[prony_if_estimation](https://github.com/bdbonnaire/prony_if_estimation)| +|date|paper|code| +|---|---|---| +|2312.14303|[geo2sigmap: high-fidelity rf signal mapping using geographic databases](https://arxiv.org/abs/2312.14303)|[geo2sigmap](https://github.com/functions-lab/geo2sigmap)| +|2312.14500|[instantaneous frequency estimation in multicomponent signals in case of interference based on the prony method](https://arxiv.org/abs/2312.14500)|[prony_if_estimation](https://github.com/bdbonnaire/prony_if_estimation)| ## 2023-12-22 -|paper|code| -|---|---| -|[multimodal brain-computer interface for in-vehicle driver cognitive load measurement: dataset and baselines](https://arxiv.org/abs/2304.04273)|[cl-drive](https://github.com/prithila05/cl-drive)| -|[finding order in chaos: a novel data augmentation method for time series in contrastive learning](https://arxiv.org/abs/2309.13439)|[Finding_Order_in_Chaos](https://github.com/eth-siplab/Finding_Order_in_Chaos)| -|[energy-aware adaptive sampling for self-sustainability in resource-constrained iot devices](https://arxiv.org/abs/2310.20331)|[EcoTrack](https://github.com/ETH-PBL/EcoTrack)| -|[revisiting deep generalized canonical correlation analysis](https://arxiv.org/abs/2312.13455)|[revisiting-dgcca](https://github.com/pariskarakasis/revisiting-dgcca)| -|[angle of arrival and centimeter distance estimation on a smart uwb sensor node](https://arxiv.org/abs/2312.13672)|[uwb_dualantenna_aoa](https://github.com/eth-pbl/uwb_dualantenna_aoa)| -|[leveraging visual supervision for array-based active speaker detection and localization](https://arxiv.org/abs/2312.14021)|[leveraging-visual-supervision-for-array-based-asdl](https://github.com/dberghi/leveraging-visual-supervision-for-array-based-asdl)| -|[bayesian optimized physics-informed neural network for estimating wave propagation velocities](https://arxiv.org/abs/2312.14064)|[bopinn](https://github.com/mahindrautela/bopinn)| -|[bidirectional uwb localization: a review on an elastic positioning scheme for gnss-deprived zones](https://arxiv.org/abs/2302.07706)|[positioning-algorithms-for-uwb-matlab](https://github.com/cliansang/positioning-algorithms-for-uwb-matlab)| +|date|paper|code| +|---|---|---| +|2312.13455|[revisiting deep generalized canonical correlation analysis](https://arxiv.org/abs/2312.13455)|[revisiting-dgcca](https://github.com/pariskarakasis/revisiting-dgcca)| +|2312.13672|[angle of arrival and centimeter distance estimation on a smart uwb sensor node](https://arxiv.org/abs/2312.13672)|[uwb_dualantenna_aoa](https://github.com/eth-pbl/uwb_dualantenna_aoa)| +|2312.14021|[leveraging visual supervision for array-based active speaker detection and localization](https://arxiv.org/abs/2312.14021)|[leveraging-visual-supervision-for-array-based-asdl](https://github.com/dberghi/leveraging-visual-supervision-for-array-based-asdl)| +|2312.14064|[bayesian optimized physics-informed neural network for estimating wave propagation velocities](https://arxiv.org/abs/2312.14064)|[bopinn](https://github.com/mahindrautela/bopinn)| ## 2023-12-21 -|paper|code| -|---|---| -|[calibrating wireless ray tracing for digital twinning using local phase error estimates](https://arxiv.org/abs/2312.12625)|[phase-aware-rt-calibration](https://github.com/kclip/phase-aware-rt-calibration)| -|[energy-efficient spiking neural network equalization for im/dd systems with optimized neural encoding](https://arxiv.org/abs/2312.12909)|[optispike](https://github.com/kit-cel/optispike)| +|date|paper|code| +|---|---|---| +|2312.12625|[calibrating wireless ray tracing for digital twinning using local phase error estimates](https://arxiv.org/abs/2312.12625)|[phase-aware-rt-calibration](https://github.com/kclip/phase-aware-rt-calibration)| +|2312.12909|[energy-efficient spiking neural network equalization for im/dd systems with optimized neural encoding](https://arxiv.org/abs/2312.12909)|[optispike](https://github.com/kit-cel/optispike)| ## 2023-12-20 -|paper|code| -|---|---| -|[grid-free harmonic retrieval and model order selection using deep convolutional neural networks](https://arxiv.org/abs/2211.04846)|[deepest-demo](https://huggingface.co/spaces/EMS-TU-Ilmenau/deepest-demo)| -|[deep plug-and-play prior for multitask channel reconstruction in massive mimo systems](https://arxiv.org/abs/2308.04728)|[pnpmt](https://github.com/wc253/pnpmt)| -|[a study on transferability of deep learning models for network intrusion detection](https://arxiv.org/abs/2312.11550)|[transferability](https://github.com/ghosh64/transferability)| -|[control aspects for using ris in latency-constrained mobile edge computing](https://arxiv.org/abs/2312.12025)|[mec-with-ris-control](https://github.com/victorcroisfelt/mec-with-ris-control)| +|date|paper|code| +|---|---|---| +|2312.11550|[a study on transferability of deep learning models for network intrusion detection](https://arxiv.org/abs/2312.11550)|[transferability](https://github.com/ghosh64/transferability)| +|2312.12025|[control aspects for using ris in latency-constrained mobile edge computing](https://arxiv.org/abs/2312.12025)|[mec-with-ris-control](https://github.com/victorcroisfelt/mec-with-ris-control)| ## 2023-12-19 -|paper|code| -|---|---| -|[morpi: mobile robot pure inertial navigation](https://arxiv.org/abs/2207.02982)|[morpi](https://github.com/ansfl/morpi)| -|[eat-radar: continuous fine-grained intake gesture detection using fmcw radar and 3d temporal convolutional network with attention](https://arxiv.org/abs/2211.04253)|[eat-radar](https://github.com/pituohai/eat-radar)| -|[low-complexity subspace-descent over symmetric positive definite manifold](https://arxiv.org/abs/2305.02041)|[subspace_descent_over_SPD_manifold](https://github.com/yogeshd-iitk/subspace_descent_over_SPD_manifold)| -|[symmetric-reciprocal-match method for vector network analyzer calibration](https://arxiv.org/abs/2309.02886)|[srm-calibration](https://github.com/ZiadHatab/srm-calibration)| -|[channel estimation for quantized systems based on conditionally gaussian latent models](https://arxiv.org/abs/2309.04014)|[quantized_channel_estimation](https://github.com/benediktfesl/quantized_channel_estimation)| -|[a geometry-based stochastic wireless channel model using channel images](https://arxiv.org/abs/2312.06637)|[geostochasticchanmodel](https://github.com/sk8053/geostochasticchanmodel)| -|[tsrnet: simple framework for real-time ecg anomaly detection with multimodal time and spectrogram restoration network](https://arxiv.org/abs/2312.10187)|[tsrnet](https://github.com/uark-aicv/tsrnet)| -|[cardiac and extracardiac discharge diagnosis prediction from emergency department ecgs using deep learning](https://arxiv.org/abs/2312.11050)|[ecg-mimic](https://github.com/ai4healthuol/ecg-mimic)| -|[a refining underlying information framework for speech enhancement](https://arxiv.org/abs/2312.11201)|[rui_se](https://github.com/caoruitju/rui_se)| -|[frequency analysis and filter design for directed graphs with polar decomposition](https://arxiv.org/abs/2312.11421)|[ICASSP2024](https://github.com/semink/ICASSP2024)| -|[wisegrt: dataset for site-specific indoor radio propagation modeling with 3d segmentation and differentiable ray-tracing](https://arxiv.org/abs/2312.11245)|[wisegrt](https://github.com/sunlab-uga/wisegrt)| +|date|paper|code| +|---|---|---| +|2312.06637|[a geometry-based stochastic wireless channel model using channel images](https://arxiv.org/abs/2312.06637)|[geostochasticchanmodel](https://github.com/sk8053/geostochasticchanmodel)| +|2312.10187|[tsrnet: simple framework for real-time ecg anomaly detection with multimodal time and spectrogram restoration network](https://arxiv.org/abs/2312.10187)|[tsrnet](https://github.com/uark-aicv/tsrnet)| +|2312.11050|[cardiac and extracardiac discharge diagnosis prediction from emergency department ecgs using deep learning](https://arxiv.org/abs/2312.11050)|[ecg-mimic](https://github.com/ai4healthuol/ecg-mimic)| +|2312.11201|[a refining underlying information framework for speech enhancement](https://arxiv.org/abs/2312.11201)|[rui_se](https://github.com/caoruitju/rui_se)| +|2312.11421|[frequency analysis and filter design for directed graphs with polar decomposition](https://arxiv.org/abs/2312.11421)|[ICASSP2024](https://github.com/semink/ICASSP2024)| +|2312.11245|[wisegrt: dataset for site-specific indoor radio propagation modeling with 3d segmentation and differentiable ray-tracing](https://arxiv.org/abs/2312.11245)|[wisegrt](https://github.com/sunlab-uga/wisegrt)| ## 2023-12-18 -|paper|code| -|---|---| -|[rtsnet: learning to smooth in partially known state-space models (preprint)](https://arxiv.org/abs/2110.04717)|[rtsnet_tsp](https://github.com/kalmannet/rtsnet_tsp)| -|[approaching globally optimal energy efficiency in interference networks via machine learning](https://arxiv.org/abs/2212.12329)|[ee](https://github.com/bilepeng/ee)| -|[score-based data generation for eeg spatial covariance matrices: towards boosting bci performance](https://arxiv.org/abs/2302.11410)|[Tensor-CSPNet-and-Graph-CSPNet](https://github.com/GeometricBCI/Tensor-CSPNet-and-Graph-CSPNet)| -|[dtp-net: learning to reconstruct eeg signals in time-frequency domain by multi-scale feature reuse](https://arxiv.org/abs/2312.09417)|[eeg-denoise](https://github.com/williamro/eeg-denoise)| -|[multi-stage learning for radar pulse activity segmentation](https://arxiv.org/abs/2312.09489)|[radseg](https://github.com/abcxyzi/radseg)| -|[a novel dual-stream time-frequency contrastive pretext tasks framework for sleep stage classification](https://arxiv.org/abs/2312.09623)|[dstf-sleepstaging](https://github.com/serg99io/dstf-sleepstaging)| -|[hypergraph-mlp: learning on hypergraphs without message passing](https://arxiv.org/abs/2312.09778)|[hypergraph-mlp](https://github.com/tbh-98/hypergraph-mlp)| -|[probabilistic learning of the purkinje network from the electrocardiogram](https://arxiv.org/abs/2312.09887)|[purkinje-learning](https://github.com/fsahli/purkinje-learning)| -|[risk-aware continuous control with neural contextual bandits](https://arxiv.org/abs/2312.09961)|[risk_aware_contextual_bandit](https://github.com/jaayala/risk_aware_contextual_bandit)| -|[srmac -- smoothed recursive moving average crossover for real-time systolic peak detection in photoplethysmography](https://arxiv.org/abs/2312.10013)|[SRMAC_peak_detector](https://github.com/GMicro-uPPG/SRMAC_peak_detector)| -|[understanding probe behaviors through variational bounds of mutual information](https://arxiv.org/abs/2312.10019)|[information_probing](https://github.com/juice500ml/information_probing)| +|date|paper|code| +|---|---|---| +|2312.09417|[dtp-net: learning to reconstruct eeg signals in time-frequency domain by multi-scale feature reuse](https://arxiv.org/abs/2312.09417)|[eeg-denoise](https://github.com/williamro/eeg-denoise)| +|2312.09489|[multi-stage learning for radar pulse activity segmentation](https://arxiv.org/abs/2312.09489)|[radseg](https://github.com/abcxyzi/radseg)| +|2312.09623|[a novel dual-stream time-frequency contrastive pretext tasks framework for sleep stage classification](https://arxiv.org/abs/2312.09623)|[dstf-sleepstaging](https://github.com/serg99io/dstf-sleepstaging)| +|2312.09778|[hypergraph-mlp: learning on hypergraphs without message passing](https://arxiv.org/abs/2312.09778)|[hypergraph-mlp](https://github.com/tbh-98/hypergraph-mlp)| +|2312.09887|[probabilistic learning of the purkinje network from the electrocardiogram](https://arxiv.org/abs/2312.09887)|[purkinje-learning](https://github.com/fsahli/purkinje-learning)| +|2312.09961|[risk-aware continuous control with neural contextual bandits](https://arxiv.org/abs/2312.09961)|[risk_aware_contextual_bandit](https://github.com/jaayala/risk_aware_contextual_bandit)| +|2312.10013|[srmac -- smoothed recursive moving average crossover for real-time systolic peak detection in photoplethysmography](https://arxiv.org/abs/2312.10013)|[SRMAC_peak_detector](https://github.com/GMicro-uPPG/SRMAC_peak_detector)| +|2312.10019|[understanding probe behaviors through variational bounds of mutual information](https://arxiv.org/abs/2312.10019)|[information_probing](https://github.com/juice500ml/information_probing)| ## 2023-12-15 -|paper|code| -|---|---| -|[qcm-sgm+: improved quantized compressed sensing with score-based generative models](https://arxiv.org/abs/2302.00919)|[qcs-sgm-plus](https://github.com/mengxiangming/qcs-sgm-plus)| -|[multi-task learning for radar signal characterisation](https://arxiv.org/abs/2306.13105)|[radchar](https://github.com/abcxyzi/radchar)| -|[structure-preserving transformers for sequences of spd matrices](https://arxiv.org/abs/2309.07579)|[spdtransnet](https://github.com/mathieuseraphim/spdtransnet)| -|[score-based diffusion priors for multi-target detection](https://arxiv.org/abs/2312.08500)|[2d-mtd_diffusion](https://github.com/zabatani/2d-mtd_diffusion)| -|[simulation-based evaluation of indoor positioning systems in connected aircraft cabins](https://arxiv.org/abs/2312.08765)|[ewgt_2023](https://github.com/paulschwarzbach/ewgt_2023)| +|date|paper|code| +|---|---|---| +|2312.08500|[score-based diffusion priors for multi-target detection](https://arxiv.org/abs/2312.08500)|[2d-mtd_diffusion](https://github.com/zabatani/2d-mtd_diffusion)| +|2312.08765|[simulation-based evaluation of indoor positioning systems in connected aircraft cabins](https://arxiv.org/abs/2312.08765)|[ewgt_2023](https://github.com/paulschwarzbach/ewgt_2023)| ## 2023-12-14 -|paper|code| -|---|---| -|[fast variational block-sparse bayesian learning](https://arxiv.org/abs/2306.00442)|[fast-variational-block-sparse-bayesian-learning](https://gitlab.com/jmoederl/fast-variational-block-sparse-bayesian-learning)| -|[annotating sleep states in children from wrist-worn accelerometer data using machine learning](https://arxiv.org/abs/2312.07561)|[ece381k-applied-ml-project](https://github.com/ss26/ece381k-applied-ml-project)| -|[towards a geometric understanding of spatio temporal graph convolution networks](https://arxiv.org/abs/2312.07777)|[stg-gradcam](https://github.com/daspraty/stg-gradcam)| -|[robust mri reconstruction by smoothed unrolling (smug)](https://arxiv.org/abs/2312.07784)|[smug_journal](https://github.com/sjames40/smug_journal)| -|[learning to transmit with provable guarantees in wireless federated learning](https://arxiv.org/abs/2304.09329)|[wirelessfl-pdg](https://github.com/bl166/wirelessfl-pdg)| +|date|paper|code| +|---|---|---| +|2312.07561|[annotating sleep states in children from wrist-worn accelerometer data using machine learning](https://arxiv.org/abs/2312.07561)|[ece381k-applied-ml-project](https://github.com/ss26/ece381k-applied-ml-project)| +|2312.07777|[towards a geometric understanding of spatio temporal graph convolution networks](https://arxiv.org/abs/2312.07777)|[stg-gradcam](https://github.com/daspraty/stg-gradcam)| +|2312.07784|[robust mri reconstruction by smoothed unrolling (smug)](https://arxiv.org/abs/2312.07784)|[smug_journal](https://github.com/sjames40/smug_journal)| ## 2023-12-13 -|paper|code| -|---|---| -|[early stopping for deep image prior](https://arxiv.org/abs/2112.06074)|[early_stopping_for_dip](https://github.com/sun-umn/early_stopping_for_dip)| -|[decentralized state estimation in a dimension-reduced linear regression](https://arxiv.org/abs/2210.06947)|[dtt](https://gitlab.com/robinforsling/dtt)| -|[balancing summarization and change detection in graph streams](https://arxiv.org/abs/2311.18694)|[bsc](https://github.com/s-fuku/bsc)| +|date|paper|code| +|---|---|---| ## 2023-12-12 -|paper|code| -|---|---| -|[binary spatial random field reconstruction from non-gaussian inhomogeneous time-series observations](https://arxiv.org/abs/2204.03343)|[WarpedGaussianProcesses](https://github.com/ShunanSheng/WarpedGaussianProcesses)| -|[domain invariant representation learning and sleep dynamics modeling for automatic sleep staging](https://arxiv.org/abs/2312.03196)|[dream](https://github.com/yeon-lab/dream)| -|[simpsi: a simple strategy to preserve spectral information in time series data augmentation](https://arxiv.org/abs/2312.05790)|[simpsi](https://github.com/hyun-ryu/simpsi)| -|[ensemble kalman filtering-aided variational inference for gaussian process state-space models](https://arxiv.org/abs/2312.05910)|[gpssmproj](https://github.com/zhidilin/gpssmproj)| -|[asf-yolo: a novel yolo model with attentional scale sequence fusion for cell instance segmentation](https://arxiv.org/abs/2312.06458)|[asf-yolo](https://github.com/mkang315/asf-yolo)| -|[robust graph neural network based on graph denoising](https://arxiv.org/abs/2312.06557)|[robust_gnn](https://github.com/vmtenorio/robust_gnn)| -|[a geometry-based stochastic wireless channel model using channel images](https://arxiv.org/abs/2312.06637)|[geostochasticchanmodel](https://github.com/sk8053/geostochasticchanmodel)| -|[quantifying & modeling multimodal interactions: an information decomposition framework](https://arxiv.org/abs/2302.12247)|[pid](https://github.com/pliang279/pid)| +|date|paper|code| +|---|---|---| +|2312.03196|[domain invariant representation learning and sleep dynamics modeling for automatic sleep staging](https://arxiv.org/abs/2312.03196)|[dream](https://github.com/yeon-lab/dream)| +|2312.05790|[simpsi: a simple strategy to preserve spectral information in time series data augmentation](https://arxiv.org/abs/2312.05790)|[simpsi](https://github.com/hyun-ryu/simpsi)| +|2312.05910|[ensemble kalman filtering-aided variational inference for gaussian process state-space models](https://arxiv.org/abs/2312.05910)|[gpssmproj](https://github.com/zhidilin/gpssmproj)| +|2312.06458|[asf-yolo: a novel yolo model with attentional scale sequence fusion for cell instance segmentation](https://arxiv.org/abs/2312.06458)|[asf-yolo](https://github.com/mkang315/asf-yolo)| +|2312.06557|[robust graph neural network based on graph denoising](https://arxiv.org/abs/2312.06557)|[robust_gnn](https://github.com/vmtenorio/robust_gnn)| +|2312.06637|[a geometry-based stochastic wireless channel model using channel images](https://arxiv.org/abs/2312.06637)|[geostochasticchanmodel](https://github.com/sk8053/geostochasticchanmodel)| ## 2023-12-11 -|paper|code| -|---|---| -|[robust single-shot 3d fluorescence imaging in scattering media with a simulator-trained neural network](https://arxiv.org/abs/2303.12573)|[sbrnet](https://github.com/bu-cisl/sbrnet)| -|[assessing neural network representations during training using noise-resilient diffusion spectral entropy](https://arxiv.org/abs/2312.04823)|[DiffusionSpectralEntropy](https://github.com/ChenLiu-1996/DiffusionSpectralEntropy)| -|[on the regret of online coded caching](https://arxiv.org/abs/2312.05003)|[onlinecodedcaching](https://github.com/sheelfshah/onlinecodedcaching)| +|date|paper|code| +|---|---|---| +|2312.04823|[assessing neural network representations during training using noise-resilient diffusion spectral entropy](https://arxiv.org/abs/2312.04823)|[DiffusionSpectralEntropy](https://github.com/ChenLiu-1996/DiffusionSpectralEntropy)| +|2312.05003|[on the regret of online coded caching](https://arxiv.org/abs/2312.05003)|[onlinecodedcaching](https://github.com/sheelfshah/onlinecodedcaching)| ## 2023-12-08 -|paper|code| -|---|---| -|[neural network based generation of a 1-dimensional stochastic field with turbulent velocity statistics](https://arxiv.org/abs/2211.11580)|[nn-turb](https://github.com/cgranerob/nn-turb)| -|[low-complexity subspace-descent over symmetric positive definite manifold](https://arxiv.org/abs/2305.02041)|[subspace_descent_over_SPD_manifold](https://github.com/yogeshd-iitk/subspace_descent_over_SPD_manifold)| -|[a scalable and generalizable pathloss map prediction](https://arxiv.org/abs/2312.03950)|[pmnet](https://github.com/abman23/pmnet)| +|date|paper|code| +|---|---|---| +|2312.03950|[a scalable and generalizable pathloss map prediction](https://arxiv.org/abs/2312.03950)|[pmnet](https://github.com/abman23/pmnet)| ## 2023-12-07 -|paper|code| -|---|---| -|[vicious classifiers: data reconstruction attack at inference time](https://arxiv.org/abs/2212.04223)|[vicious-classifiers](https://github.com/mmalekzadeh/vicious-classifiers)| -|[functional renormalization group for signal detection and stochastic ergodicity breaking](https://arxiv.org/abs/2310.07499)|[stochastic-signal-detection](https://github.com/thesfinox/stochastic-signal-detection)| +|date|paper|code| +|---|---|---| ## 2023-12-06 -|paper|code| -|---|---| -|[distributed two-tier drl framework for cell-free network: association, beamforming and power allocation](https://arxiv.org/abs/2303.12479)|[dhdrl](https://github.com/kiven-ykw/dhdrl)| -|[spectral temporal graph neural network for massive mimo csi prediction](https://arxiv.org/abs/2312.02159)|[csi-prediction](https://github.com/sharanmourya/csi-prediction)| -|[faultformer: transformer-based prediction of bearing faults](https://arxiv.org/abs/2312.02380)|[faultformer](https://github.com/anthonyzhou-1/faultformer)| -|[mains: a magnetic field aided inertial navigation system for indoor positioning](https://arxiv.org/abs/2312.02599)|[mainsvsmagekf](https://github.com/huang-chuan/mainsvsmagekf)| +|date|paper|code| +|---|---|---| +|2312.02159|[spectral temporal graph neural network for massive mimo csi prediction](https://arxiv.org/abs/2312.02159)|[csi-prediction](https://github.com/sharanmourya/csi-prediction)| +|2312.02380|[faultformer: transformer-based prediction of bearing faults](https://arxiv.org/abs/2312.02380)|[faultformer](https://github.com/anthonyzhou-1/faultformer)| +|2312.02599|[mains: a magnetic field aided inertial navigation system for indoor positioning](https://arxiv.org/abs/2312.02599)|[mainsvsmagekf](https://github.com/huang-chuan/mainsvsmagekf)| ## 2023-12-05 -|paper|code| -|---|---| -|[w-transformers : a wavelet-based transformer framework for univariate time series forecasting](https://arxiv.org/abs/2209.03945)|[w-transformer](https://github.com/capwidow/w-transformer)| -|[ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices](https://arxiv.org/abs/2209.15146)|[stress](https://github.com/xalentis/stress)| -|[a generalized bandsplit neural network for cinematic audio source separation](https://arxiv.org/abs/2309.02539)|[bandit](https://github.com/karnwatcharasupat/bandit)| -|[fast and robust sparsity-aware block diagonal representation](https://arxiv.org/abs/2312.01137)|[frs-bdr](https://github.com/a-tastan/frs-bdr)| -|[towards decentralized task offloading and resource allocation in user-centric mobile edge computing](https://arxiv.org/abs/2312.01499)|[ucmec-mmwave-fronthaul](https://github.com/qlt315/ucmec-mmwave-fronthaul)| -|[augmenting channel charting with classical wireless source localization techniques](https://arxiv.org/abs/2312.01968)|[toa-aoa-augmented-channelcharting](https://github.com/jeija/toa-aoa-augmented-channelcharting)| -|[model-free learning of two-stage beamformers for passive irs-aided network design](https://arxiv.org/abs/2304.11464)|[zosga-irs](https://github.com/hassaanhashmi/zosga-irs)| +|date|paper|code| +|---|---|---| +|2312.01137|[fast and robust sparsity-aware block diagonal representation](https://arxiv.org/abs/2312.01137)|[frs-bdr](https://github.com/a-tastan/frs-bdr)| +|2312.01499|[towards decentralized task offloading and resource allocation in user-centric mobile edge computing](https://arxiv.org/abs/2312.01499)|[ucmec-mmwave-fronthaul](https://github.com/qlt315/ucmec-mmwave-fronthaul)| +|2312.01968|[augmenting channel charting with classical wireless source localization techniques](https://arxiv.org/abs/2312.01968)|[toa-aoa-augmented-channelcharting](https://github.com/jeija/toa-aoa-augmented-channelcharting)| ## 2023-12-04 -|paper|code| -|---|---| -|[deepjscc-l++: robust and bandwidth-adaptive wireless image transmission](https://arxiv.org/abs/2305.13161)|[deepjscc-lplusplus](https://github.com/aprilbian/deepjscc-lplusplus)| -|[isac 4d imaging system based on 5g downlink millimeter wave signal](https://arxiv.org/abs/2310.06401)|[ISAC_4D_IMaging](https://github.com/MrHaobolu/ISAC_4D_IMaging)| -|[classification utility, fairness, and compactness via tunable information bottleneck and r\'enyi measures](https://arxiv.org/abs/2206.10043)|[rfib-code](https://github.com/agronowski/rfib-code)| -|[message-passing on hypergraphs: detectability, phase transitions and higher-order information](https://arxiv.org/abs/2312.00708)|[hypergraph-message-passing](https://github.com/nickruggeri/hypergraph-message-passing)| -|[algebra of nonlocal boxes and the collapse of communication complexity](https://arxiv.org/abs/2312.00725)|[algebra-of-boxes-code](https://github.com/pierre-botteron/algebra-of-boxes-code)| +|date|paper|code| +|---|---|---| +|2312.00708|[message-passing on hypergraphs: detectability, phase transitions and higher-order information](https://arxiv.org/abs/2312.00708)|[hypergraph-message-passing](https://github.com/nickruggeri/hypergraph-message-passing)| +|2312.00725|[algebra of nonlocal boxes and the collapse of communication complexity](https://arxiv.org/abs/2312.00725)|[algebra-of-boxes-code](https://github.com/pierre-botteron/algebra-of-boxes-code)| ## 2023-12-01 -|paper|code| -|---|---| -|[2d signal estimation for sparse distributed target photon counting data](https://arxiv.org/abs/2311.18037)|[signal-estimation-sparse-data](https://github.com/ncar/signal-estimation-sparse-data)| -|[balancing summarization and change detection in graph streams](https://arxiv.org/abs/2311.18694)|[bsc](https://github.com/s-fuku/bsc)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/01.md b/archives/2024/01.md index 03f33347..165b32e8 100644 --- a/archives/2024/01.md +++ b/archives/2024/01.md @@ -1,193 +1,136 @@ # January 2024 Archive ## 2024-01-31 -|paper|code| -|---|---| -|[enn: a neural network with dct adaptive activation functions](https://arxiv.org/abs/2307.00673)|[enn](https://github.com/marcmartinezgost/enn)| -|[mt-hccar: multi-task deep learning with hierarchical classification and attention-based regression for cloud property retrieval](https://arxiv.org/abs/2401.16520)|[mt-hccar](https://github.com/ai-4-atmosphere-remote-sensing/mt-hccar)| -|[a fully differentiable model for unsupervised singing voice separation](https://arxiv.org/abs/2401.16837)|[umss_icassp](https://github.com/pierrechouteau/umss_icassp)| -|[channel characterization of uav-ris-aided systems with adaptive phase-shift configuration](https://arxiv.org/abs/2401.17180)|[uav-ris-blockage](https://github.com/thanhluannguyen/uav-ris-blockage)| -|[unrestricted error-type codebook generation for error correction code in dna storage inspired by nlp](https://arxiv.org/abs/2401.15915)|[code_generation_for_dna_storage](https://github.com/ylu1997/code_generation_for_dna_storage)| -|[large language model evaluation via matrix entropy](https://arxiv.org/abs/2401.17139)|[matrix-entropy](https://github.com/waltonfuture/matrix-entropy)| +|date|paper|code| +|---|---|---| +|2401.16520|[mt-hccar: multi-task deep learning with hierarchical classification and attention-based regression for cloud property retrieval](https://arxiv.org/abs/2401.16520)|[mt-hccar](https://github.com/ai-4-atmosphere-remote-sensing/mt-hccar)| +|2401.16837|[a fully differentiable model for unsupervised singing voice separation](https://arxiv.org/abs/2401.16837)|[umss_icassp](https://github.com/pierrechouteau/umss_icassp)| +|2401.17180|[channel characterization of uav-ris-aided systems with adaptive phase-shift configuration](https://arxiv.org/abs/2401.17180)|[uav-ris-blockage](https://github.com/thanhluannguyen/uav-ris-blockage)| +|2401.15915|[unrestricted error-type codebook generation for error correction code in dna storage inspired by nlp](https://arxiv.org/abs/2401.15915)|[code_generation_for_dna_storage](https://github.com/ylu1997/code_generation_for_dna_storage)| +|2401.17139|[large language model evaluation via matrix entropy](https://arxiv.org/abs/2401.17139)|[matrix-entropy](https://github.com/waltonfuture/matrix-entropy)| ## 2024-01-30 -|paper|code| -|---|---| -|[cell-free massive mimo in o-ran: energy-aware joint orchestration of cloud, fronthaul, and radio resources](https://arxiv.org/abs/2301.06166)|[o-ran-cell-free](https://github.com/ozlemtugfedemir/o-ran-cell-free)| -|[task-oriented communication with out-of-distribution detection: an information bottleneck framework](https://arxiv.org/abs/2305.12423)|[VCCIB](https://github.com/hlidmhkust/VCCIB)| -|[generalizable sleep staging via multi-level domain alignment](https://arxiv.org/abs/2401.05363)|[sleepdg](https://github.com/wjq-learning/sleepdg)| -|[biodiffusion: a versatile diffusion model for biomedical signal synthesis](https://arxiv.org/abs/2401.10282)|[biodiffusion](https://github.com/imics-lab/biodiffusion)| -|[effective communication with dynamic feature compression](https://arxiv.org/abs/2401.16236)|[tmlcn_code](https://github.com/pietro-talli/tmlcn_code)| +|date|paper|code| +|---|---|---| +|2401.05363|[generalizable sleep staging via multi-level domain alignment](https://arxiv.org/abs/2401.05363)|[sleepdg](https://github.com/wjq-learning/sleepdg)| +|2401.10282|[biodiffusion: a versatile diffusion model for biomedical signal synthesis](https://arxiv.org/abs/2401.10282)|[biodiffusion](https://github.com/imics-lab/biodiffusion)| +|2401.16236|[effective communication with dynamic feature compression](https://arxiv.org/abs/2401.16236)|[tmlcn_code](https://github.com/pietro-talli/tmlcn_code)| ## 2024-01-26 -|paper|code| -|---|---| -|[a strong and simple deep learning baseline for bci mi decoding](https://arxiv.org/abs/2309.07159)|[eegsimpleconv](https://github.com/elouayas/eegsimpleconv)| -|[energy-efficient power allocation in cell-free massive mimo via graph neural networks](https://arxiv.org/abs/2401.14281)|[ee_cell_free](https://gitlab.com/ichbinram/ee_cell_free)| -|[rotation invariant quantization for model compression](https://arxiv.org/abs/2303.03106)|[riq](https://github.com/ehaleva/riq)| +|date|paper|code| +|---|---|---| +|2401.14281|[energy-efficient power allocation in cell-free massive mimo via graph neural networks](https://arxiv.org/abs/2401.14281)|[ee_cell_free](https://gitlab.com/ichbinram/ee_cell_free)| ## 2024-01-25 -|paper|code| -|---|---| -|[data-driven estimation of capacity upper bounds](https://arxiv.org/abs/2205.06471)|[upper_capacity_bounds](https://github.com/chaeger/upper_capacity_bounds)| -|[opendpd: an open-source end-to-end learning & benchmarking framework for wideband power amplifier modeling and digital pre-distortion](https://arxiv.org/abs/2401.08318)|[opendpd](https://github.com/lab-emi/opendpd)| -|[a generalized multiscale bundle-based hyperspectral sparse unmixing algorithm](https://arxiv.org/abs/2401.13161)|[gmbua](https://github.com/lucayress/gmbua)| -|[diffusion model based posterior sampling for noisy linear inverse problems](https://arxiv.org/abs/2211.12343)|[dmps](https://github.com/mengxiangming/dmps)| +|date|paper|code| +|---|---|---| +|2401.08318|[opendpd: an open-source end-to-end learning & benchmarking framework for wideband power amplifier modeling and digital pre-distortion](https://arxiv.org/abs/2401.08318)|[opendpd](https://github.com/lab-emi/opendpd)| +|2401.13161|[a generalized multiscale bundle-based hyperspectral sparse unmixing algorithm](https://arxiv.org/abs/2401.13161)|[gmbua](https://github.com/lucayress/gmbua)| ## 2024-01-24 -|paper|code| -|---|---| -|[afs-bm: enhancing model performance through adaptive feature selection with binary masking](https://arxiv.org/abs/2401.11250)|[afs_bm-algorithm](https://github.com/yigitturali/afs_bm-algorithm)| -|[towards adaptive subspace detection in heterogeneous environment](https://arxiv.org/abs/2401.12469)|[heterogeneous_detector](https://github.com/arekavandi/heterogeneous_detector)| -|[a review of deep learning methods for photoplethysmography data](https://arxiv.org/abs/2401.12783)|[dl_ppg_review](https://github.com/ngk03/dl_ppg_review)| -|[entanglement purification with quantum ldpc codes and iterative decoding](https://arxiv.org/abs/2210.14143)|[ghz_distillation_qec](https://github.com/nrenga/ghz_distillation_qec)| -|[statistical mechanics of the maximum-average submatrix problem](https://arxiv.org/abs/2303.05237)|[Maximum-Average-Submatrix](https://github.com/SPOC-group/Maximum-Average-Submatrix)| -|[multi-sources information fusion learning for multi-points nlos localization](https://arxiv.org/abs/2401.12538)|[AMDNloc](https://github.com/Horizontal666/AMDNloc)| +|date|paper|code| +|---|---|---| +|2401.11250|[afs-bm: enhancing model performance through adaptive feature selection with binary masking](https://arxiv.org/abs/2401.11250)|[afs_bm-algorithm](https://github.com/yigitturali/afs_bm-algorithm)| +|2401.12469|[towards adaptive subspace detection in heterogeneous environment](https://arxiv.org/abs/2401.12469)|[heterogeneous_detector](https://github.com/arekavandi/heterogeneous_detector)| +|2401.12783|[a review of deep learning methods for photoplethysmography data](https://arxiv.org/abs/2401.12783)|[dl_ppg_review](https://github.com/ngk03/dl_ppg_review)| +|2401.12538|[multi-sources information fusion learning for multi-points nlos localization](https://arxiv.org/abs/2401.12538)|[AMDNloc](https://github.com/Horizontal666/AMDNloc)| ## 2024-01-23 -|paper|code| -|---|---| -|[the icanclean algorithm: how to remove artifacts using reference noise recordings](https://arxiv.org/abs/2201.11798)|[iCanClean](https://github.com/downeyryanj/iCanClean)| -|[the manifold scattering transform for high-dimensional point cloud data](https://arxiv.org/abs/2206.10078)|[pointcloud_scattering](https://github.com/steachhr/pointcloud_scattering)| -|[identifying tbi physiological states by clustering multivariate clinical time-series data](https://arxiv.org/abs/2303.13024)|[slac-time](https://github.com/vsubbian/slac-time)| -|[modulate your spectrum in self-supervised learning](https://arxiv.org/abs/2305.16789)|[intl](https://github.com/winci-ai/intl)| -|[congestion-aware distributed task offloading in wireless multi-hop networks using graph neural networks](https://arxiv.org/abs/2312.02471)|[multihop-offload](https://github.com/zhongyuanzhao/multihop-offload)| -|[fully differentiable ray tracing via discontinuity smoothing for radio network optimization](https://arxiv.org/abs/2401.11882)|[differt2d](https://github.com/jeertmans/differt2d)| -|[nlcg-net: a model-based zero-shot learning framework for undersampled quantitative mri reconstruction](https://arxiv.org/abs/2401.12004)|[NLCG-Net](https://github.com/Xinrui-Jiang/NLCG-Net)| -|[cone-restricted information theory](https://arxiv.org/abs/2206.04300)|[conerestrictedinformationtheory](https://github.com/chitambarlab/conerestrictedinformationtheory)| -|[in-context learning for mimo equalization using transformer-based sequence models](https://arxiv.org/abs/2311.06101)|[icl-equalization](https://github.com/kclip/icl-equalization)| -|[deep learning-based adaptive joint source-channel coding using hypernetworks](https://arxiv.org/abs/2401.11155)|[hyper-ajscc](https://github.com/songjiexie/hyper-ajscc)| +|date|paper|code| +|---|---|---| +|2401.11882|[fully differentiable ray tracing via discontinuity smoothing for radio network optimization](https://arxiv.org/abs/2401.11882)|[differt2d](https://github.com/jeertmans/differt2d)| +|2401.12004|[nlcg-net: a model-based zero-shot learning framework for undersampled quantitative mri reconstruction](https://arxiv.org/abs/2401.12004)|[NLCG-Net](https://github.com/Xinrui-Jiang/NLCG-Net)| +|2401.11155|[deep learning-based adaptive joint source-channel coding using hypernetworks](https://arxiv.org/abs/2401.11155)|[hyper-ajscc](https://github.com/songjiexie/hyper-ajscc)| ## 2024-01-22 -|paper|code| -|---|---| -|[group-level brain decoding with deep learning](https://arxiv.org/abs/2205.14102)|[meg-group-decode](https://github.com/ricsinaruto/meg-group-decode)| -|[mutual information-based integrated sensing and communications: a wmmse framework](https://arxiv.org/abs/2310.12686)|[MI-based-WMMSE-ISAC-algorithm](https://github.com/ROCASSO/MI-based-WMMSE-ISAC-algorithm)| -|[chaotic properties of an fir filtered h\'enon map](https://arxiv.org/abs/2401.10281)|[chaotic-properties-of-an-fir-filtered-henon-map](https://github.com/vinicius-s-borges/chaotic-properties-of-an-fir-filtered-henon-map)| -|[biodiffusion: a versatile diffusion model for biomedical signal synthesis](https://arxiv.org/abs/2401.10282)|[biodiffusion](https://github.com/imics-lab/biodiffusion)| -|[window stacking meta-models for clinical eeg classification](https://arxiv.org/abs/2401.10283)|[eegscopeandarbitration](https://github.com/zhuyixuan1997/eegscopeandarbitration)| -|[morpheusnet: resource efficient sleep stage classifier for embedded on-line systems](https://arxiv.org/abs/2401.10284)|[morphuesnet](https://github.com/ali77sina/morphuesnet)| -|[learning non-myopic power allocation in constrained scenarios](https://arxiv.org/abs/2401.10297)|[nmpa](https://github.com/archo48/nmpa)| -|[attentive fusion: a transformer-based approach to multimodal hate speech detection](https://arxiv.org/abs/2401.10653)|[hate-speech-identification](https://github.com/atanumandal0491/hate-speech-identification)| -|[a novel maximum-entropy-driven technique for low-rank orthogonal nonnegative matrix factorization with $\ell_0$-norm sparsity constraint](https://arxiv.org/abs/2210.02672)|[mep-orthogonal-nmf](https://github.com/salar96/mep-orthogonal-nmf)| +|date|paper|code| +|---|---|---| +|2401.10281|[chaotic properties of an fir filtered h\'enon map](https://arxiv.org/abs/2401.10281)|[chaotic-properties-of-an-fir-filtered-henon-map](https://github.com/vinicius-s-borges/chaotic-properties-of-an-fir-filtered-henon-map)| +|2401.10282|[biodiffusion: a versatile diffusion model for biomedical signal synthesis](https://arxiv.org/abs/2401.10282)|[biodiffusion](https://github.com/imics-lab/biodiffusion)| +|2401.10283|[window stacking meta-models for clinical eeg classification](https://arxiv.org/abs/2401.10283)|[eegscopeandarbitration](https://github.com/zhuyixuan1997/eegscopeandarbitration)| +|2401.10284|[morpheusnet: resource efficient sleep stage classifier for embedded on-line systems](https://arxiv.org/abs/2401.10284)|[morphuesnet](https://github.com/ali77sina/morphuesnet)| +|2401.10297|[learning non-myopic power allocation in constrained scenarios](https://arxiv.org/abs/2401.10297)|[nmpa](https://github.com/archo48/nmpa)| +|2401.10653|[attentive fusion: a transformer-based approach to multimodal hate speech detection](https://arxiv.org/abs/2401.10653)|[hate-speech-identification](https://github.com/atanumandal0491/hate-speech-identification)| ## 2024-01-19 -|paper|code| -|---|---| -|[learning to extract distributed polarization sensing data from noisy jones matrices](https://arxiv.org/abs/2401.09917)|[physics-based-distributed-polarization-sensing](https://github.com/mohammadfarsi1994/physics-based-distributed-polarization-sensing)| -|[pac codes: sequential decoding vs list decoding](https://arxiv.org/abs/2002.06805)|[List-Decoding-for-Polar-and-PAC-Codes](https://github.com/mohammad-rowshan/List-Decoding-for-Polar-and-PAC-Codes)| -|[recovering simultaneously structured data via non-convex iteratively reweighted least squares](https://arxiv.org/abs/2306.04961)|[simirls](https://github.com/ckuemmerle/simirls)| -|[learn to categorize or categorize to learn? self-coding for generalized category discovery](https://arxiv.org/abs/2310.19776)|[infosieve](https://github.com/sarahrastegar/infosieve)| +|date|paper|code| +|---|---|---| +|2401.09917|[learning to extract distributed polarization sensing data from noisy jones matrices](https://arxiv.org/abs/2401.09917)|[physics-based-distributed-polarization-sensing](https://github.com/mohammadfarsi1994/physics-based-distributed-polarization-sensing)| ## 2024-01-18 -|paper|code| -|---|---| -|[a comparative study of deep learning and iterative algorithms for joint channel estimation and signal detection](https://arxiv.org/abs/2303.03678)|[mimo_jcesd](https://github.com/j991222/mimo_jcesd)| -|[score-based source separation with applications to digital communication signals](https://arxiv.org/abs/2306.14411)|[score_based_source_separation](https://github.com/tkj516/score_based_source_separation)| -|[a densenet-based method for decoding auditory spatial attention with eeg](https://arxiv.org/abs/2309.07690)|[asad_densenet](https://github.com/xuxiran/asad_densenet)| -|[neural network equalizers and successive interference cancellation for bandlimited channels with a nonlinearity](https://arxiv.org/abs/2401.09217)|[nn-mi](https://github.com/dplabst/nn-mi)| -|[entanglement purification with quantum ldpc codes and iterative decoding](https://arxiv.org/abs/2210.14143)|[ghz_distillation_qec](https://github.com/nrenga/ghz_distillation_qec)| -|[greedy poisson rejection sampling](https://arxiv.org/abs/2305.15313)|[greedy-poisson-rejection-sampling](https://github.com/gergely-flamich/greedy-poisson-rejection-sampling)| -|[algebra of nonlocal boxes and the collapse of communication complexity](https://arxiv.org/abs/2312.00725)|[algebra-of-boxes-code](https://github.com/pierre-botteron/algebra-of-boxes-code)| -|[bayes conditional distribution estimation for knowledge distillation based on conditional mutual information](https://arxiv.org/abs/2401.08732)|[iclrmcmi](https://github.com/iclr2024mcmi/iclrmcmi)| +|date|paper|code| +|---|---|---| +|2401.09217|[neural network equalizers and successive interference cancellation for bandlimited channels with a nonlinearity](https://arxiv.org/abs/2401.09217)|[nn-mi](https://github.com/dplabst/nn-mi)| +|2401.08732|[bayes conditional distribution estimation for knowledge distillation based on conditional mutual information](https://arxiv.org/abs/2401.08732)|[iclrmcmi](https://github.com/iclr2024mcmi/iclrmcmi)| ## 2024-01-17 -|paper|code| -|---|---| -|[resource-efficient separation transformer](https://arxiv.org/abs/2206.09507)|[speechbrain](https://github.com/speechbrain/speechbrain)| -|[optimal discrete beamforming of ris-aided wireless communications: an inner product maximization approach](https://arxiv.org/abs/2211.04167)|[RIS_Optimization](https://github.com/RujingXiong/RIS_Optimization)| -|[ensemble kalman filtering meets gaussian process ssm for non-mean-field and online inference](https://arxiv.org/abs/2312.05910)|[gpssmproj](https://github.com/zhidilin/gpssmproj)| -|[frequency analysis and filter design for directed graphs with polar decomposition](https://arxiv.org/abs/2312.11421)|[ICASSP2024](https://github.com/semink/ICASSP2024)| -|[unsupervised harmonic parameter estimation using differentiable dsp and spectral optimal transport](https://arxiv.org/abs/2312.14507)|[1d-spectral-optimal-transport](https://github.com/bernardo-torres/1d-spectral-optimal-transport)| -|[iterative regularization with k-support norm: an important complement to sparse recovery](https://arxiv.org/abs/2401.05394)|[irksn_aaai2024](https://github.com/wdevazelhes/irksn_aaai2024)| -|[remaining useful life prediction for aircraft engines using lstm](https://arxiv.org/abs/2401.07590)|[rul-prediction](https://github.com/aneesperingal/rul-prediction)| -|[calibration of an ska-low prototype station using holographic techniques](https://arxiv.org/abs/2401.08039)|[zenodo.8237885](https://zenodo.org/record/zenodo.8237885)| -|[opendpd: an open-source end-to-end learning & benchmarking framework for wideband power amplifier modeling and digital pre-distortion](https://arxiv.org/abs/2401.08318)|[opendpd](https://github.com/lab-emi/opendpd)| -|[reliability and latency analysis for wireless communication systems with a secret-key budget](https://arxiv.org/abs/2304.02538)|[secret-key-budget-ruin](https://github.com/klb2/secret-key-budget-ruin)| +|date|paper|code| +|---|---|---| +|2401.05394|[iterative regularization with k-support norm: an important complement to sparse recovery](https://arxiv.org/abs/2401.05394)|[irksn_aaai2024](https://github.com/wdevazelhes/irksn_aaai2024)| +|2401.07590|[remaining useful life prediction for aircraft engines using lstm](https://arxiv.org/abs/2401.07590)|[rul-prediction](https://github.com/aneesperingal/rul-prediction)| +|2401.08039|[calibration of an ska-low prototype station using holographic techniques](https://arxiv.org/abs/2401.08039)|[zenodo.8237885](https://zenodo.org/record/zenodo.8237885)| +|2401.08318|[opendpd: an open-source end-to-end learning & benchmarking framework for wideband power amplifier modeling and digital pre-distortion](https://arxiv.org/abs/2401.08318)|[opendpd](https://github.com/lab-emi/opendpd)| ## 2024-01-15 -|paper|code| -|---|---| -|[robust peak detection for holter ecgs by self-organized operational neural networks](https://arxiv.org/abs/2110.02381)|[r-peak-detection-1d-selfonn](https://github.com/muzairzahid/r-peak-detection-1d-selfonn)| -|[learning temporal resolution in spectrogram for audio classification](https://arxiv.org/abs/2210.01719)|[diffres-python](https://github.com/haoheliu/diffres-python)| -|[emergency response person localization and vital sign estimation using a semi-autonomous robot mounted sfcw radar](https://arxiv.org/abs/2305.15795)|[radar-vitals-estimation](https://github.com/schrchr/radar-vitals-estimation)| -|[semantic-forward relaying: a novel framework towards 6g cooperative communications](https://arxiv.org/abs/2310.07987)|[Semantic_Forward](https://github.com/linwest/Semantic_Forward)| -|[generalizable sleep staging via multi-level domain alignment](https://arxiv.org/abs/2401.05363)|[sleepdg](https://github.com/wjq-learning/sleepdg)| -|[block majorization minimization with extrapolation and application to $\beta$-nmf](https://arxiv.org/abs/2401.06646)|[bmme](https://github.com/vleplat/bmme)| +|date|paper|code| +|---|---|---| +|2401.05363|[generalizable sleep staging via multi-level domain alignment](https://arxiv.org/abs/2401.05363)|[sleepdg](https://github.com/wjq-learning/sleepdg)| +|2401.06646|[block majorization minimization with extrapolation and application to $\beta$-nmf](https://arxiv.org/abs/2401.06646)|[bmme](https://github.com/vleplat/bmme)| ## 2024-01-12 -|paper|code| -|---|---| -|[task-oriented communication with out-of-distribution detection: an information bottleneck framework](https://arxiv.org/abs/2305.12423)|[VCCIB](https://github.com/hlidmhkust/VCCIB)| -|[online action recognition for human risk prediction with anticipated haptic alert via wearables](https://arxiv.org/abs/2401.05365)|[paper_guo_2023_humanoids_lifting_risk_prediction](https://github.com/ami-iit/paper_guo_2023_humanoids_lifting_risk_prediction)| -|[adf & transapp: a transformer-based framework for appliance detection using smart meter consumption series](https://arxiv.org/abs/2401.05381)|[transapp](https://github.com/adrienpetralia/transapp)| -|[selfeeg: a python library for self-supervised learning in electroencephalography](https://arxiv.org/abs/2401.05405)|[selfeeg](https://github.com/medmaxlab/selfeeg)| -|[rfrl gym: a reinforcement learning testbed for cognitive radio applications](https://arxiv.org/abs/2401.05406)|[rfrl-gym](https://github.com/vtnsisdd/rfrl-gym)| -|[seamless and multi-resolution energy forecasting](https://arxiv.org/abs/2401.05413)|[multiresolutionforecasting](https://github.com/willwang1113/multiresolutionforecasting)| -|[pulsatiomech: an open-source matlab toolbox for seismocardiography signal processing](https://arxiv.org/abs/2401.05480)|[scg_master_toolbox](https://github.com/nzavanelli/scg_master_toolbox)| -|[weiss-weinstein bound of frequency estimation error for very weak gnss signals](https://arxiv.org/abs/2401.05606)|[WWB](https://github.com/TMBOC/WWB)| +|date|paper|code| +|---|---|---| +|2401.05365|[online action recognition for human risk prediction with anticipated haptic alert via wearables](https://arxiv.org/abs/2401.05365)|[paper_guo_2023_humanoids_lifting_risk_prediction](https://github.com/ami-iit/paper_guo_2023_humanoids_lifting_risk_prediction)| +|2401.05381|[adf & transapp: a transformer-based framework for appliance detection using smart meter consumption series](https://arxiv.org/abs/2401.05381)|[transapp](https://github.com/adrienpetralia/transapp)| +|2401.05405|[selfeeg: a python library for self-supervised learning in electroencephalography](https://arxiv.org/abs/2401.05405)|[selfeeg](https://github.com/medmaxlab/selfeeg)| +|2401.05406|[rfrl gym: a reinforcement learning testbed for cognitive radio applications](https://arxiv.org/abs/2401.05406)|[rfrl-gym](https://github.com/vtnsisdd/rfrl-gym)| +|2401.05413|[seamless and multi-resolution energy forecasting](https://arxiv.org/abs/2401.05413)|[multiresolutionforecasting](https://github.com/willwang1113/multiresolutionforecasting)| +|2401.05480|[pulsatiomech: an open-source matlab toolbox for seismocardiography signal processing](https://arxiv.org/abs/2401.05480)|[scg_master_toolbox](https://github.com/nzavanelli/scg_master_toolbox)| +|2401.05606|[weiss-weinstein bound of frequency estimation error for very weak gnss signals](https://arxiv.org/abs/2401.05606)|[WWB](https://github.com/TMBOC/WWB)| ## 2024-01-11 -|paper|code| -|---|---| -|[on the salient limitations of the methods of assembly theory and their classification of molecular biosignatures](https://arxiv.org/abs/2210.00901)|[mscomplexity](https://github.com/abicumaran/mscomplexity)| -|[in search of maximum non-overlapping codes](https://arxiv.org/abs/2307.12593)|[nono-codes](https://github.com/magdevska/nono-codes)| +|date|paper|code| +|---|---|---| ## 2024-01-10 -|paper|code| -|---|---| -|[adaptive kalmannet: data-driven kalman filter with fast adaptation](https://arxiv.org/abs/2309.07016)|[adaptive-knet-icassp24](https://github.com/kalmannet/adaptive-knet-icassp24)| -|[online test-time adaptation of spatial-temporal traffic flow forecasting](https://arxiv.org/abs/2401.04148)|[adcsd](https://github.com/pengxin-guo/adcsd)| +|date|paper|code| +|---|---|---| +|2401.04148|[online test-time adaptation of spatial-temporal traffic flow forecasting](https://arxiv.org/abs/2401.04148)|[adcsd](https://github.com/pengxin-guo/adcsd)| ## 2024-01-09 -|paper|code| -|---|---| -|[qcm-sgm+: improved quantized compressed sensing with score-based generative models](https://arxiv.org/abs/2302.00919)|[qcs-sgm-plus](https://github.com/mengxiangming/qcs-sgm-plus)| -|[calibration-free online test-time adaptation for electroencephalography motor imagery decoding](https://arxiv.org/abs/2311.18520)|[eeg-otta](https://github.com/martinwimpff/eeg-otta)| -|[faultformer: pretraining transformers for adaptable bearing fault classification](https://arxiv.org/abs/2312.02380)|[faultformer](https://github.com/anthonyzhou-1/faultformer)| -|[ensemble kalman filtering meets gaussian process ssm for non-mean-field and online inference](https://arxiv.org/abs/2312.05910)|[gpssmproj](https://github.com/zhidilin/gpssmproj)| -|[improving transferability of network intrusion detection in a federated learning setup](https://arxiv.org/abs/2401.03560)|[transferability](https://github.com/ghosh64/transferability)| -|[ddd: a perceptually superior low-response-time dnn-based declipper](https://arxiv.org/abs/2401.03650)|[ddd](https://github.com/stet-stet/ddd)| -|[lofi user scheduling for multiuser mimo wireless systems](https://arxiv.org/abs/2401.04077)|[lofi-user-scheduling](https://github.com/iip-group/lofi-user-scheduling)| +|date|paper|code| +|---|---|---| +|2401.03560|[improving transferability of network intrusion detection in a federated learning setup](https://arxiv.org/abs/2401.03560)|[transferability](https://github.com/ghosh64/transferability)| +|2401.03650|[ddd: a perceptually superior low-response-time dnn-based declipper](https://arxiv.org/abs/2401.03650)|[ddd](https://github.com/stet-stet/ddd)| +|2401.04077|[lofi user scheduling for multiuser mimo wireless systems](https://arxiv.org/abs/2401.04077)|[lofi-user-scheduling](https://github.com/iip-group/lofi-user-scheduling)| ## 2024-01-08 -|paper|code| -|---|---| -|[channel estimation in underdetermined systems utilizing variational autoencoders](https://arxiv.org/abs/2309.08411)|[vae-est-ud](https://github.com/baurmichael/vae-est-ud)| -|[a geometry-based stochastic wireless channel model using channel images](https://arxiv.org/abs/2312.06637)|[geostochasticchanmodel](https://github.com/sk8053/geostochasticchanmodel)| -|[geo2sigmap: high-fidelity rf signal mapping using geographic databases](https://arxiv.org/abs/2312.14303)|[geo2sigmap](https://github.com/functions-lab/geo2sigmap)| +|date|paper|code| +|---|---|---| ## 2024-01-05 -|paper|code| -|---|---| -|[multi-device task-oriented communication via maximal coding rate reduction](https://arxiv.org/abs/2309.02888)|[taskcommmcr2](https://github.com/chang-cai/taskcommmcr2)| -|[transmusic: a transformer-aided subspace method for doa estimation with low-resolution adcs](https://arxiv.org/abs/2309.08174)|[transformer_music](https://github.com/jijunkai/transformer_music)| -|[multi-agent context learning strategy for interference-aware beam allocation in mmwave vehicular communications](https://arxiv.org/abs/2401.02323)|[beam-analysis](https://github.com/cfoh/beam-analysis)| +|date|paper|code| +|---|---|---| +|2401.02323|[multi-agent context learning strategy for interference-aware beam allocation in mmwave vehicular communications](https://arxiv.org/abs/2401.02323)|[beam-analysis](https://github.com/cfoh/beam-analysis)| ## 2024-01-04 -|paper|code| -|---|---| -|[near-field velocity sensing and predictive beamforming](https://arxiv.org/abs/2311.09888)|[near-field-velocity-sensing-and-predictive-beamforming](https://github.com/zhaolin820/near-field-velocity-sensing-and-predictive-beamforming)| -|[physics-informed appliance signatures generator for energy disaggregation](https://arxiv.org/abs/2401.01828)|[edframe](https://github.com/arx7ti/edframe)| -|[an experimental sorting method for improving metagenomic data encoding](https://arxiv.org/abs/2401.01786)|[mizar](https://github.com/cobilab/mizar)| -|[concurrent brainstorming & hypothesis satisfying: an iterative framework for enhanced retrieval-augmented generation (r2cbr3h-sr)](https://arxiv.org/abs/2401.01835)|[r2cbr3h-sr](https://github.com/arash-shahmansoori/r2cbr3h-sr)| +|date|paper|code| +|---|---|---| +|2401.01828|[physics-informed appliance signatures generator for energy disaggregation](https://arxiv.org/abs/2401.01828)|[edframe](https://github.com/arx7ti/edframe)| +|2401.01786|[an experimental sorting method for improving metagenomic data encoding](https://arxiv.org/abs/2401.01786)|[mizar](https://github.com/cobilab/mizar)| +|2401.01835|[concurrent brainstorming & hypothesis satisfying: an iterative framework for enhanced retrieval-augmented generation (r2cbr3h-sr)](https://arxiv.org/abs/2401.01835)|[r2cbr3h-sr](https://github.com/arash-shahmansoori/r2cbr3h-sr)| ## 2024-01-03 -|paper|code| -|---|---| -|[data-adaptive graph framelets with generalized vanishing moments for graph signal processing](https://arxiv.org/abs/2309.03537)|[graph-involved-frame](https://github.com/zrgcityu/graph-involved-frame)| -|[$f$-divergence based classification: beyond the use of cross-entropy](https://arxiv.org/abs/2401.01268)|[discriminative-classification-fdiv](https://github.com/tonellolab/discriminative-classification-fdiv)| -|[families of costs with zero and nonnegative mtw tensor in optimal transport](https://arxiv.org/abs/2401.00953)|[regularmtw](https://github.com/dnguyend/regularmtw)| +|date|paper|code| +|---|---|---| +|2401.01268|[$f$-divergence based classification: beyond the use of cross-entropy](https://arxiv.org/abs/2401.01268)|[discriminative-classification-fdiv](https://github.com/tonellolab/discriminative-classification-fdiv)| +|2401.00953|[families of costs with zero and nonnegative mtw tensor in optimal transport](https://arxiv.org/abs/2401.00953)|[regularmtw](https://github.com/dnguyend/regularmtw)| ## 2024-01-02 -|paper|code| -|---|---| -|[dictionary attack on imu-based gait authentication](https://arxiv.org/abs/2309.11766)|[dictionaryattackonimugait](https://github.com/rajeshjnu2006/dictionaryattackonimugait)| -|[wisegrt: dataset for site-specific indoor radio propagation modeling with 3d segmentation and differentiable ray-tracing](https://arxiv.org/abs/2312.11245)|[wisegrt](https://github.com/sunlab-uga/wisegrt)| +|date|paper|code| +|---|---|---| ## 2024-01-01 -|paper|code| -|---|---| -|[a declarative goal-oriented framework for smart environments with lpaas](https://arxiv.org/abs/2106.13083)|[Solomon](https://github.com/di-unipi-socc/Solomon)| -|[bayesian topology inference on partially known networks from input-output pairs](https://arxiv.org/abs/2309.06532)|[inference_langevin](https://github.com/tenceto/inference_langevin)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/02.md b/archives/2024/02.md index 0bb6d52b..4b0c0526 100644 --- a/archives/2024/02.md +++ b/archives/2024/02.md @@ -1,170 +1,125 @@ # February 2024 Archive ## 2024-02-29 -|paper|code| -|---|---| -|[eeg2rep: enhancing self-supervised eeg representation through informative masked inputs](https://arxiv.org/abs/2402.17772)|[eeg2rep](https://github.com/navidfoumani/eeg2rep)| -|[extended kalman filter -- koopman operator for tractable stochastic optimal control](https://arxiv.org/abs/2402.18554)|[linearizing-uncertainty-for-control](https://github.com/msramada/linearizing-uncertainty-for-control)| -|[on the computational entanglement of distant features in adversarial machine learning](https://arxiv.org/abs/2309.15669)|[adversary-example-through-relativity](https://github.com/yenlunglai/adversary-example-through-relativity)| +|date|paper|code| +|---|---|---| +|2402.17772|[eeg2rep: enhancing self-supervised eeg representation through informative masked inputs](https://arxiv.org/abs/2402.17772)|[eeg2rep](https://github.com/navidfoumani/eeg2rep)| +|2402.18554|[extended kalman filter -- koopman operator for tractable stochastic optimal control](https://arxiv.org/abs/2402.18554)|[linearizing-uncertainty-for-control](https://github.com/msramada/linearizing-uncertainty-for-control)| ## 2024-02-28 -|paper|code| -|---|---| -|[multi-kernel correntropy-based orientation estimation of imus: gradient descent methods](https://arxiv.org/abs/2304.06548)|[mc_gd_imu](https://github.com/lsl-zsj/mc_gd_imu)| -|[hrtf upsampling with a generative adversarial network using a gnomonic equiangular projection](https://arxiv.org/abs/2306.05812)|[hrtf-upsampling-with-a-generative-adversarial-network-using-a-gnomonic-equiangular-projection](https://github.com/ahogg/hrtf-upsampling-with-a-generative-adversarial-network-using-a-gnomonic-equiangular-projection)| -|[distributed deep joint source-channel coding with decoder-only side information](https://arxiv.org/abs/2310.04311)|[deepjscc-wz](https://github.com/ipc-lab/deepjscc-wz)| -|[computation rate maximization for wireless powered edge computing with multi-user cooperation](https://arxiv.org/abs/2402.16866)|[wptmec](https://github.com/cpngroup/wptmec)| +|date|paper|code| +|---|---|---| +|2402.16866|[computation rate maximization for wireless powered edge computing with multi-user cooperation](https://arxiv.org/abs/2402.16866)|[wptmec](https://github.com/cpngroup/wptmec)| ## 2024-02-27 -|paper|code| -|---|---| -|[a complex quasi-newton proximal method for image reconstruction in compressed sensing mri](https://arxiv.org/abs/2303.02586)|[cqnpcs_mrireco](https://github.com/hongtao-argmin/cqnpcs_mrireco)| -|[semi-supervised end-to-end learning for integrated sensing and communications](https://arxiv.org/abs/2310.09940)|[sslisac](https://github.com/josemateosramos/sslisac)| -|[deep, convergent, unrolled half-quadratic splitting for image deconvolution](https://arxiv.org/abs/2402.12872)|[decun](https://github.com/6zhc/decun)| -|[flexible robust beamforming for multibeam satellite downlink using reinforcement learning](https://arxiv.org/abs/2402.16563)|[2310_beamforming_learner_2](https://github.com/steffengra/2310_beamforming_learner_2)| -|[bagged deep image prior for recovering images in the presence of speckle noise](https://arxiv.org/abs/2402.15635)|[Bagged-DIP-Speckle](https://github.com/Computational-Imaging-RU/Bagged-DIP-Speckle)| +|date|paper|code| +|---|---|---| +|2402.12872|[deep, convergent, unrolled half-quadratic splitting for image deconvolution](https://arxiv.org/abs/2402.12872)|[decun](https://github.com/6zhc/decun)| +|2402.16563|[flexible robust beamforming for multibeam satellite downlink using reinforcement learning](https://arxiv.org/abs/2402.16563)|[2310_beamforming_learner_2](https://github.com/steffengra/2310_beamforming_learner_2)| +|2402.15635|[bagged deep image prior for recovering images in the presence of speckle noise](https://arxiv.org/abs/2402.15635)|[Bagged-DIP-Speckle](https://github.com/Computational-Imaging-RU/Bagged-DIP-Speckle)| ## 2024-02-26 -|paper|code| -|---|---| -|[cell-free isac mimo systems: joint sensing and communication beamforming](https://arxiv.org/abs/2301.11328)|[Cell-free-ISAC-beamforming](https://github.com/umut-demirhan/Cell-free-ISAC-beamforming)| -|[a hybrid quantum-classical approach based on the hadamard transform for the convolutional layer](https://arxiv.org/abs/2305.17510)|[icml2023-ht](https://github.com/phy710/icml2023-ht)| -|[reconfigurable intelligent surfaces-enabled intra-cell pilot reuse in massive mimo systems](https://arxiv.org/abs/2310.06975)|[ris-pilot-reuse](https://github.com/josecarlos-marinello/ris-pilot-reuse)| -|[sdemg: score-based diffusion model for surface electromyographic signal denoising](https://arxiv.org/abs/2402.03808)|[sdemg](https://github.com/tonyliu0910/sdemg)| -|[szcore: a seizure community open-source research evaluation framework for the validation of eeg-based automated seizure detection algorithms](https://arxiv.org/abs/2402.13005)|[epilepsy2bids](https://github.com/esl-epfl/epilepsy2bids)| -|[a conversational brain-artificial intelligence interface](https://arxiv.org/abs/2402.15011)|[eegchat](https://github.com/akmeunier/eegchat)| +|date|paper|code| +|---|---|---| +|2402.03808|[sdemg: score-based diffusion model for surface electromyographic signal denoising](https://arxiv.org/abs/2402.03808)|[sdemg](https://github.com/tonyliu0910/sdemg)| +|2402.13005|[szcore: a seizure community open-source research evaluation framework for the validation of eeg-based automated seizure detection algorithms](https://arxiv.org/abs/2402.13005)|[epilepsy2bids](https://github.com/esl-epfl/epilepsy2bids)| +|2402.15011|[a conversational brain-artificial intelligence interface](https://arxiv.org/abs/2402.15011)|[eegchat](https://github.com/akmeunier/eegchat)| ## 2024-02-23 -|paper|code| -|---|---| -|[approximate message passing with rigorous guarantees for pooled data and quantitative group testing](https://arxiv.org/abs/2309.15507)|[amp_pooled_qgt](https://github.com/pablopasc/amp_pooled_qgt)| -|[brant-2: foundation model for brain signals](https://arxiv.org/abs/2402.10251)|[brant-2](https://github.com/yzz673/brant-2)| -|[random forests for detecting weak signals and extracting physical information: a case study of magnetic navigation](https://arxiv.org/abs/2402.14131)|[magnav](https://github.com/aminmoradixl/magnav)| -|[gdtm: an indoor geospatial tracking dataset with distributed multimodal sensors](https://arxiv.org/abs/2402.14136)|[gdtm](https://github.com/nesl/gdtm)| -|[semantic-preserving image coding based on conditional diffusion models](https://arxiv.org/abs/2310.15737)|[spic](https://github.com/frapez1/spic)| -|[dynamic multi-network mining of tensor time series](https://arxiv.org/abs/2402.11773)|[dmm](https://github.com/koheiobata/dmm)| +|date|paper|code| +|---|---|---| +|2402.10251|[brant-2: foundation model for brain signals](https://arxiv.org/abs/2402.10251)|[brant-2](https://github.com/yzz673/brant-2)| +|2402.14131|[random forests for detecting weak signals and extracting physical information: a case study of magnetic navigation](https://arxiv.org/abs/2402.14131)|[magnav](https://github.com/aminmoradixl/magnav)| +|2402.14136|[gdtm: an indoor geospatial tracking dataset with distributed multimodal sensors](https://arxiv.org/abs/2402.14136)|[gdtm](https://github.com/nesl/gdtm)| +|2402.11773|[dynamic multi-network mining of tensor time series](https://arxiv.org/abs/2402.11773)|[dmm](https://github.com/koheiobata/dmm)| ## 2024-02-22 -|paper|code| -|---|---| -|[ris-admm: a ris and admm-based passive and sparse sensing method with interference removal](https://arxiv.org/abs/2206.06172)|[ris-admm](https://github.com/chenpengseu/ris-admm)| -|[motor imagery decoding using ensemble curriculum learning and collaborative training](https://arxiv.org/abs/2211.11460)|[ensemble-mi](https://github.com/gzoumpourlis/ensemble-mi)| -|[a new method of modeling the multi-stage decision-making process of crt using machine learning with uncertainty quantification](https://arxiv.org/abs/2309.08415)|[crt_multistageml_uncertainty](https://github.com/miilab-mtu/crt_multistageml_uncertainty)| -|[diffplf: a conditional diffusion model for probabilistic forecasting of ev charging load](https://arxiv.org/abs/2402.13548)|[DiffPLF](https://github.com/LSY-Cython/DiffPLF)| -|[interpretable diffusion via information decomposition](https://arxiv.org/abs/2310.07972)|[info-decomp](https://github.com/kxh001/info-decomp)| -|[comparing comparators in generalization bounds](https://arxiv.org/abs/2310.10534)|[comparing-comparators](https://github.com/fredrikhellstrom/comparing-comparators)| -|[treet: transfer entropy estimation via transformer](https://arxiv.org/abs/2402.06919)|[treet](https://github.com/omerlux/treet)| +|date|paper|code| +|---|---|---| +|2402.13548|[diffplf: a conditional diffusion model for probabilistic forecasting of ev charging load](https://arxiv.org/abs/2402.13548)|[DiffPLF](https://github.com/LSY-Cython/DiffPLF)| +|2402.06919|[treet: transfer entropy estimation via transformer](https://arxiv.org/abs/2402.06919)|[treet](https://github.com/omerlux/treet)| ## 2024-02-21 -|paper|code| -|---|---| -|[beyond diagonal reconfigurable intelligent surfaces utilizing graph theory: modeling, architecture design, and optimization](https://arxiv.org/abs/2305.05013)|[bdris-utilizing-graph-theory](https://github.com/matteonerini/bdris-utilizing-graph-theory)| -|[on the impact of mutual coupling on ris-assisted channel estimation](https://arxiv.org/abs/2309.04990)|[communication](https://github.com/zpinjun/communication)| -|[learning transfer operators by kernel density estimation](https://arxiv.org/abs/2210.03124)|[fpoperatorde](https://github.com/sudamphy/fpoperatorde)| +|date|paper|code| +|---|---|---| ## 2024-02-20 -|paper|code| -|---|---| -|[deep, deep learning with bart](https://arxiv.org/abs/2202.14005)|[deep-deep-learning-with-bart](https://github.com/mrirecon/deep-deep-learning-with-bart)| -|[apsense: data-driven algorithm in ppg-based sleep apnea sensing](https://arxiv.org/abs/2306.10863)|[apsense](https://github.com/iobt-vistec/apsense)| -|[iterative regularization with k-support norm: an important complement to sparse recovery](https://arxiv.org/abs/2401.05394)|[irksn_aaai2024](https://github.com/wdevazelhes/irksn_aaai2024)| -|[integrating pre-trained language model with physical layer communications](https://arxiv.org/abs/2402.11656)|[on-device-ai-comm](https://github.com/abman23/on-device-ai-comm)| +|date|paper|code| +|---|---|---| +|2402.11656|[integrating pre-trained language model with physical layer communications](https://arxiv.org/abs/2402.11656)|[on-device-ai-comm](https://github.com/abman23/on-device-ai-comm)| ## 2024-02-19 -|paper|code| -|---|---| -|[wimans: a benchmark dataset for wifi-based multi-user activity sensing](https://arxiv.org/abs/2402.09430)|[wimans](https://github.com/huangshk/wimans)| -|[robust beamforming for ris-aided communications: gradient-based manifold meta learning](https://arxiv.org/abs/2402.10626)|[GMML](https://github.com/fenghaozhu/GMML)| -|[reliability and latency analysis for wireless communication systems with a secret-key budget](https://arxiv.org/abs/2304.02538)|[secret-key-budget-ruin](https://github.com/klb2/secret-key-budget-ruin)| -|[towards cohesion-fairness harmony: contrastive regularization in individual fair graph clustering](https://arxiv.org/abs/2402.10756)|[ifairnmtf](https://github.com/siamakghodsi/ifairnmtf)| +|date|paper|code| +|---|---|---| +|2402.09430|[wimans: a benchmark dataset for wifi-based multi-user activity sensing](https://arxiv.org/abs/2402.09430)|[wimans](https://github.com/huangshk/wimans)| +|2402.10626|[robust beamforming for ris-aided communications: gradient-based manifold meta learning](https://arxiv.org/abs/2402.10626)|[GMML](https://github.com/fenghaozhu/GMML)| +|2402.10756|[towards cohesion-fairness harmony: contrastive regularization in individual fair graph clustering](https://arxiv.org/abs/2402.10756)|[ifairnmtf](https://github.com/siamakghodsi/ifairnmtf)| ## 2024-02-16 -|paper|code| -|---|---| -|[outlier-insensitive kalman filtering: theory and applications](https://arxiv.org/abs/2309.09505)|[oikf-nuv](https://github.com/kalmannet/oikf-nuv)| -|[multidimensional gabor-like filters derived from gaussian functions on logarithmic frequency axes](https://arxiv.org/abs/2402.09419)|[gabor-like-filters](https://gitlab.com/eidheim/gabor-like-filters)| -|[improving eeg signal classification accuracy using wasserstein generative adversarial networks](https://arxiv.org/abs/2402.09453)|[eeg-wgan](https://github.com/joshparksj/eeg-wgan)| -|[stein variational guided model predictive path integral control: proposal and experiments with fast maneuvering vehicles](https://arxiv.org/abs/2309.11040)|[proj-svg_mppi](https://github.com/kohonda/proj-svg_mppi)| +|date|paper|code| +|---|---|---| +|2402.09419|[multidimensional gabor-like filters derived from gaussian functions on logarithmic frequency axes](https://arxiv.org/abs/2402.09419)|[gabor-like-filters](https://gitlab.com/eidheim/gabor-like-filters)| +|2402.09453|[improving eeg signal classification accuracy using wasserstein generative adversarial networks](https://arxiv.org/abs/2402.09453)|[eeg-wgan](https://github.com/joshparksj/eeg-wgan)| ## 2024-02-15 -|paper|code| -|---|---| -|[prediction, communication, and computing duration optimization for vr video streaming](https://arxiv.org/abs/1910.13884)|[code4vr-prediction-communication-and-computing](https://github.com/xizhicher/code4vr-prediction-communication-and-computing)| -|[introducing rsess: an open source enumerative sphere shaping implementation coded in rust](https://arxiv.org/abs/2402.08771)|[rsess](https://github.com/kit-cel/rsess)| -|[lightweight deep learning based channel estimation for extremely large-scale massive mimo systems](https://arxiv.org/abs/2402.08916)|[XLCNet](https://github.com/gaoshen90/XLCNet)| +|date|paper|code| +|---|---|---| +|2402.08771|[introducing rsess: an open source enumerative sphere shaping implementation coded in rust](https://arxiv.org/abs/2402.08771)|[rsess](https://github.com/kit-cel/rsess)| +|2402.08916|[lightweight deep learning based channel estimation for extremely large-scale massive mimo systems](https://arxiv.org/abs/2402.08916)|[XLCNet](https://github.com/gaoshen90/XLCNet)| ## 2024-02-14 -|paper|code| -|---|---| -|[compressing sign information in dct-based image coding via deep sign retrieval](https://arxiv.org/abs/2209.10712)|[dsr](https://github.com/ctsutake/dsr)| -|[optimized gradient tracking for decentralized online learning](https://arxiv.org/abs/2306.06375)|[Optimized-Gradient-Tracking](https://github.com/Shivangi-Dubey-Sharma/Optimized-Gradient-Tracking)| -|[self-supervised blind source separation via multi-encoder autoencoders](https://arxiv.org/abs/2309.07138)|[self-supervised-bss-via-multi-encoder-ae](https://github.com/webstah/self-supervised-bss-via-multi-encoder-ae)| -|[leveraging digital cousins for ensemble q-learning in large-scale wireless networks](https://arxiv.org/abs/2402.08022)|[digital-cousins-for-ensemble-q-learning](https://github.com/talhabozkus/digital-cousins-for-ensemble-q-learning)| -|[commodity-specific triads in the dutch inter-industry production network](https://arxiv.org/abs/2305.12179)|[numetris](https://github.com/marsmdk/numetris)| +|date|paper|code| +|---|---|---| +|2402.08022|[leveraging digital cousins for ensemble q-learning in large-scale wireless networks](https://arxiv.org/abs/2402.08022)|[digital-cousins-for-ensemble-q-learning](https://github.com/talhabozkus/digital-cousins-for-ensemble-q-learning)| ## 2024-02-13 -|paper|code| -|---|---| -|[harpa: high-rate phase association with travel time neural fields](https://arxiv.org/abs/2307.07572)|[phase_association](https://github.com/dadacheng/phase_association)| -|[design space exploration on efficient and accurate human pose estimation from sparse imu-sensing](https://arxiv.org/abs/2308.02397)|[dse-sparse-imu](https://github.com/itiv-kit/dse-sparse-imu)| -|[improving robustness via tilted exponential layer: a communication-theoretic perspective](https://arxiv.org/abs/2311.01047)|[texp_for_robustness](https://github.com/bhagyapuranik/texp_for_robustness)| -|[implementation of kalman filter approach for active noise control by using matlab: dynamic noise cancellation](https://arxiv.org/abs/2402.06896)|[kalman_filter_for_anc](https://github.com/shidongyuan/kalman_filter_for_anc)| -|[set learning for accurate and calibrated models](https://arxiv.org/abs/2307.02245)|[oko](https://github.com/lukasmut/oko)| -|[treet: transfer entropy estimation via transformer](https://arxiv.org/abs/2402.06919)|[treet](https://github.com/omerlux/treet)| -|[tighter bounds on the information bottleneck with application to deep learning](https://arxiv.org/abs/2402.07639)|[vub](https://github.com/hopl1t/vub)| +|date|paper|code| +|---|---|---| +|2402.06896|[implementation of kalman filter approach for active noise control by using matlab: dynamic noise cancellation](https://arxiv.org/abs/2402.06896)|[kalman_filter_for_anc](https://github.com/shidongyuan/kalman_filter_for_anc)| +|2402.06919|[treet: transfer entropy estimation via transformer](https://arxiv.org/abs/2402.06919)|[treet](https://github.com/omerlux/treet)| +|2402.07639|[tighter bounds on the information bottleneck with application to deep learning](https://arxiv.org/abs/2402.07639)|[vub](https://github.com/hopl1t/vub)| ## 2024-02-12 -|paper|code| -|---|---| -|[a new inexact proximal linear algorithm with adaptive stopping criteria for robust phase retrieval](https://arxiv.org/abs/2304.12522)|[ipl-code-share](https://github.com/zhengzhongpku/ipl-code-share)| -|[energy-efficient power allocation in cell-free massive mimo via graph neural networks](https://arxiv.org/abs/2401.14281)|[ee_cell_free](https://gitlab.com/ichbinram/ee_cell_free)| -|[checking the sufficiently scattered condition using a global non-convex optimization software](https://arxiv.org/abs/2402.06019)|[check-ssc](https://gitlab.com/ngillis/check-ssc)| +|date|paper|code| +|---|---|---| +|2402.06019|[checking the sufficiently scattered condition using a global non-convex optimization software](https://arxiv.org/abs/2402.06019)|[check-ssc](https://gitlab.com/ngillis/check-ssc)| ## 2024-02-09 -|paper|code| -|---|---| -|[spiking neural networks in the alexiewicz topology: a new perspective on analysis and error bounds](https://arxiv.org/abs/2305.05772)|[alexsnn](https://github.com/lunglmayrmoser/alexsnn)| -|[multi-timescale ensemble q-learning for markov decision process policy optimization](https://arxiv.org/abs/2402.05476)|[tsp_23_supplementary_file](https://github.com/talhabozkus/tsp_23_supplementary_file)| +|date|paper|code| +|---|---|---| +|2402.05476|[multi-timescale ensemble q-learning for markov decision process policy optimization](https://arxiv.org/abs/2402.05476)|[tsp_23_supplementary_file](https://github.com/talhabozkus/tsp_23_supplementary_file)| ## 2024-02-08 -|paper|code| -|---|---| -|[stochastic unrolled federated learning](https://arxiv.org/abs/2305.15371)|[fed-surf](https://github.com/smrhadou/fed-surf)| -|[rscnet: dynamic csi compression for cloud-based wifi sensing](https://arxiv.org/abs/2402.04888)|[rscnet](https://github.com/bornabr/rscnet)| +|date|paper|code| +|---|---|---| +|2402.04888|[rscnet: dynamic csi compression for cloud-based wifi sensing](https://arxiv.org/abs/2402.04888)|[rscnet](https://github.com/bornabr/rscnet)| ## 2024-02-07 -|paper|code| -|---|---| -|[task-oriented communication with out-of-distribution detection: an information bottleneck framework](https://arxiv.org/abs/2305.12423)|[VCCIB](https://github.com/hlidmhkust/VCCIB)| -|[deep nonnegative matrix factorization with beta divergences](https://arxiv.org/abs/2309.08249)|[deep-beta-nmf-public](https://github.com/vleplat/deep-beta-nmf-public)| -|[sdemg: score-based diffusion model for surface electromyographic signal denoising](https://arxiv.org/abs/2402.03808)|[sdemg](https://github.com/tonyliu0910/sdemg)| -|[attention with markov: a framework for principled analysis of transformers via markov chains](https://arxiv.org/abs/2402.04161)|[markov](https://github.com/bond1995/markov)| +|date|paper|code| +|---|---|---| +|2402.03808|[sdemg: score-based diffusion model for surface electromyographic signal denoising](https://arxiv.org/abs/2402.03808)|[sdemg](https://github.com/tonyliu0910/sdemg)| +|2402.04161|[attention with markov: a framework for principled analysis of transformers via markov chains](https://arxiv.org/abs/2402.04161)|[markov](https://github.com/bond1995/markov)| ## 2024-02-06 -|paper|code| -|---|---| -|[on confidence sequences for bounded random processes via universal gambling strategies](https://arxiv.org/abs/2207.12382)|[confidence-sequence-via-gambling](https://github.com/jongharyu/confidence-sequence-via-gambling)| -|[algorithms for computing the free distance of convolutional codes](https://arxiv.org/abs/2402.02982)|[algorithms-for-computing-the-free-distance-of-convolutional-codes](https://github.com/uscpr/algorithms-for-computing-the-free-distance-of-convolutional-codes)| -|[minimum description length and generalization guarantees for representation learning](https://arxiv.org/abs/2402.03254)|[mdl_and_generalization_guarantees_for_representation_learning](https://github.com/piotrkrasnowski/mdl_and_generalization_guarantees_for_representation_learning)| +|date|paper|code| +|---|---|---| +|2402.02982|[algorithms for computing the free distance of convolutional codes](https://arxiv.org/abs/2402.02982)|[algorithms-for-computing-the-free-distance-of-convolutional-codes](https://github.com/uscpr/algorithms-for-computing-the-free-distance-of-convolutional-codes)| +|2402.03254|[minimum description length and generalization guarantees for representation learning](https://arxiv.org/abs/2402.03254)|[mdl_and_generalization_guarantees_for_representation_learning](https://github.com/piotrkrasnowski/mdl_and_generalization_guarantees_for_representation_learning)| ## 2024-02-05 -|paper|code| -|---|---| -|[graph representation learning for contention and interference management in wireless networks](https://arxiv.org/abs/2402.00879)|[ac-grl-wi-fi](https://github.com/zhouyou-gu/ac-grl-wi-fi)| -|[an information-theoretic approach to analyze nlp classification tasks](https://arxiv.org/abs/2402.00978)|[nlp-element-influence](https://github.com/wangluran/nlp-element-influence)| -|[flexible variational information bottleneck: achieving diverse compression with a single training](https://arxiv.org/abs/2402.01238)|[fvib](https://github.com/sotakudo/fvib)| +|date|paper|code| +|---|---|---| +|2402.00879|[graph representation learning for contention and interference management in wireless networks](https://arxiv.org/abs/2402.00879)|[ac-grl-wi-fi](https://github.com/zhouyou-gu/ac-grl-wi-fi)| +|2402.00978|[an information-theoretic approach to analyze nlp classification tasks](https://arxiv.org/abs/2402.00978)|[nlp-element-influence](https://github.com/wangluran/nlp-element-influence)| +|2402.01238|[flexible variational information bottleneck: achieving diverse compression with a single training](https://arxiv.org/abs/2402.01238)|[fvib](https://github.com/sotakudo/fvib)| ## 2024-02-02 -|paper|code| -|---|---| -|[self-supervised speech representation and contextual text embedding for match-mismatch classification with eeg recording](https://arxiv.org/abs/2401.04964)|[eeg-stimulus-match-mismatch](https://github.com/bobwangpku/eeg-stimulus-match-mismatch)| -|[energy-efficient power allocation in cell-free massive mimo via graph neural networks](https://arxiv.org/abs/2401.14281)|[ee_cell_free](https://gitlab.com/ichbinram/ee_cell_free)| -|[online speaker diarization of meetings guided by speech separation](https://arxiv.org/abs/2402.00067)|[sspavaldo](https://github.com/egruttadauria98/sspavaldo)| -|[determination of trace organic contaminant concentration via machine classification of surface-enhanced raman spectra](https://arxiv.org/abs/2402.00197)|[Determination-of-Trace-Organic-Contaminant-Concentration-via-Machine-Classification-of-Raman-Spectra](https://github.com/VishnuJay/Determination-of-Trace-Organic-Contaminant-Concentration-via-Machine-Classification-of-Raman-Spectra)| +|date|paper|code| +|---|---|---| +|2402.00067|[online speaker diarization of meetings guided by speech separation](https://arxiv.org/abs/2402.00067)|[sspavaldo](https://github.com/egruttadauria98/sspavaldo)| +|2402.00197|[determination of trace organic contaminant concentration via machine classification of surface-enhanced raman spectra](https://arxiv.org/abs/2402.00197)|[Determination-of-Trace-Organic-Contaminant-Concentration-via-Machine-Classification-of-Raman-Spectra](https://github.com/VishnuJay/Determination-of-Trace-Organic-Contaminant-Concentration-via-Machine-Classification-of-Raman-Spectra)| ## 2024-02-01 -|paper|code| -|---|---| -|[gaussian adaptive attention is all you need: robust contextual representations across multiple modalities](https://arxiv.org/abs/2401.11143)|[gaussian-adaptive-attention](https://github.com/gioannides/gaussian-adaptive-attention)| -|[an iot system for smart building combining multiple mmwave fmcw radars applied to people counting](https://arxiv.org/abs/2401.17949)|[mmwave_cluster](https://github.com/gtec-udc/mmwave_cluster)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/03.md b/archives/2024/03.md index fa2e1476..06e4e174 100644 --- a/archives/2024/03.md +++ b/archives/2024/03.md @@ -1,180 +1,115 @@ # March 2024 Archive ## 2024-03-29 -|paper|code| -|---|---| -|[efficient deep learning-based estimation of the vital signs on smartphones](https://arxiv.org/abs/2204.08989)|[medvse](https://github.com/mahdifarvardin/medvse)| -|[identifying tbi physiological states by clustering multivariate clinical time-series data](https://arxiv.org/abs/2303.13024)|[slac-time](https://github.com/vsubbian/slac-time)| -|[leveraging variational autoencoders for parameterized mmse estimation](https://arxiv.org/abs/2307.05352)|[vae-estimator](https://github.com/tum-msv/vae-estimator)| -|[channel estimation in underdetermined systems utilizing variational autoencoders](https://arxiv.org/abs/2309.08411)|[vae-est-ud](https://github.com/baurmichael/vae-est-ud)| -|[gan-supervised seismic data reconstruction: an enhanced-learning for improved generalization](https://arxiv.org/abs/2311.10910)|[gan_guided_seismic](https://github.com/paulgoyes/gan_guided_seismic)| -|[brant-2: foundation model for brain signals](https://arxiv.org/abs/2402.10251)|[brant-2](https://github.com/yzz673/brant-2)| -|[deep csi compression for dual-polarized massive mimo channels with disentangled representation learning](https://arxiv.org/abs/2403.19185)|[direnet](https://github.com/seushf/direnet)| -|[toward low-latency iterative decoding of qldpc codes under circuit-level noise](https://arxiv.org/abs/2403.18901)|[slidingwindowdecoder](https://github.com/gongaa/slidingwindowdecoder)| +|date|paper|code| +|---|---|---| +|2403.19185|[deep csi compression for dual-polarized massive mimo channels with disentangled representation learning](https://arxiv.org/abs/2403.19185)|[direnet](https://github.com/seushf/direnet)| +|2403.18901|[toward low-latency iterative decoding of qldpc codes under circuit-level noise](https://arxiv.org/abs/2403.18901)|[slidingwindowdecoder](https://github.com/gongaa/slidingwindowdecoder)| ## 2024-03-28 -|paper|code| -|---|---| -|[high-rate phase association with travel time neural fields](https://arxiv.org/abs/2307.07572)|[phase_association](https://github.com/dadacheng/phase_association)| -|[genet: a graph neural network-based anti-noise task-oriented semantic communication paradigm](https://arxiv.org/abs/2403.18296)|[genet](https://github.com/chunbaobao/genet)| -|[clustering change sign detection by fusing mixture complexity](https://arxiv.org/abs/2403.18269)|[mc-fusion](https://github.com/uraken38/mc-fusion)| +|date|paper|code| +|---|---|---| +|2403.18296|[genet: a graph neural network-based anti-noise task-oriented semantic communication paradigm](https://arxiv.org/abs/2403.18296)|[genet](https://github.com/chunbaobao/genet)| +|2403.18269|[clustering change sign detection by fusing mixture complexity](https://arxiv.org/abs/2403.18269)|[mc-fusion](https://github.com/uraken38/mc-fusion)| ## 2024-03-27 -|paper|code| -|---|---| -|[on the intersection of signal processing and machine learning: a use case-driven analysis approach](https://arxiv.org/abs/2403.17181)|[signal-processing-for-machine-learning](https://github.com/western-oc2-lab/signal-processing-for-machine-learning)| -|[hill: hierarchy-aware information lossless contrastive learning for hierarchical text classification](https://arxiv.org/abs/2403.17307)|[hill](https://github.com/rooooyy/hill)| +|date|paper|code| +|---|---|---| +|2403.17181|[on the intersection of signal processing and machine learning: a use case-driven analysis approach](https://arxiv.org/abs/2403.17181)|[signal-processing-for-machine-learning](https://github.com/western-oc2-lab/signal-processing-for-machine-learning)| +|2403.17307|[hill: hierarchy-aware information lossless contrastive learning for hierarchical text classification](https://arxiv.org/abs/2403.17307)|[hill](https://github.com/rooooyy/hill)| ## 2024-03-26 -|paper|code| -|---|---| -|[user training with error augmentation for electromyogram-based gesture classification](https://arxiv.org/abs/2309.07289)|[emg-feedback-user-training](https://github.com/neu-spiral/emg-feedback-user-training)| -|[arbitrary discrete fourier analysis and its application in replayed speech detection](https://arxiv.org/abs/2403.01130)|[adfa](https://github.com/shihkuanglee/adfa)| -|[coupled generator decomposition for fusion of electro- and magnetoencephalography data](https://arxiv.org/abs/2403.15409)|[coupled-generator-decomposition](https://github.com/anders-s-olsen/coupled-generator-decomposition)| -|[fast real-time arbitrary waveform generation using graphic processing units](https://arxiv.org/abs/2403.15582)|[awg-on-gpu](https://github.com/jqiamo/awg-on-gpu)| -|[proprioception is all you need: terrain classification for boreal forests](https://arxiv.org/abs/2403.16877)|[BorealTC](https://github.com/norlab-ulaval/BorealTC)| +|date|paper|code| +|---|---|---| +|2403.01130|[arbitrary discrete fourier analysis and its application in replayed speech detection](https://arxiv.org/abs/2403.01130)|[adfa](https://github.com/shihkuanglee/adfa)| +|2403.15409|[coupled generator decomposition for fusion of electro- and magnetoencephalography data](https://arxiv.org/abs/2403.15409)|[coupled-generator-decomposition](https://github.com/anders-s-olsen/coupled-generator-decomposition)| +|2403.15582|[fast real-time arbitrary waveform generation using graphic processing units](https://arxiv.org/abs/2403.15582)|[awg-on-gpu](https://github.com/jqiamo/awg-on-gpu)| +|2403.16877|[proprioception is all you need: terrain classification for boreal forests](https://arxiv.org/abs/2403.16877)|[BorealTC](https://github.com/norlab-ulaval/BorealTC)| ## 2024-03-25 -|paper|code| -|---|---| -|[successive pose estimation and beam tracking for mmwave vehicular communication systems](https://arxiv.org/abs/2307.16117)|[Fast-CFEAR-Radar-Odometry](https://github.com/Cen-Liu/Fast-CFEAR-Radar-Odometry)| +|date|paper|code| +|---|---|---| ## 2024-03-22 -|paper|code| -|---|---| -|[interpretable causal inference for analyzing wearable, sensor, and distributional data](https://arxiv.org/abs/2312.10569)|[addmalts](https://github.com/almost-matching-exactly/addmalts)| -|[towards better statistical understanding of watermarking llms](https://arxiv.org/abs/2403.13027)|[dualga](https://github.com/zhongzecai/dualga)| +|date|paper|code| +|---|---|---| +|2403.13027|[towards better statistical understanding of watermarking llms](https://arxiv.org/abs/2403.13027)|[dualga](https://github.com/zhongzecai/dualga)| ## 2024-03-21 -|paper|code| -|---|---| -|[sdoa-net: an efficient deep learning-based doa estimation network for imperfect array](https://arxiv.org/abs/2203.10231)|[sdoa-net](https://github.com/chenpengseu/sdoa-net)| -|[design of efficient point-mass filter with application in terrain aided navigation](https://arxiv.org/abs/2303.05100)|[efficient-pmf](https://github.com/idm-uwb/efficient-pmf)| -|[identifying tbi physiological states by clustering multivariate clinical time-series data](https://arxiv.org/abs/2303.13024)|[slac-time](https://github.com/vsubbian/slac-time)| -|[energy-efficient analog beamforming for rf-wet with charging time constraint](https://arxiv.org/abs/2311.05325)|[ee-analog-beamforming-wet](https://github.com/osmel-dev/ee-analog-beamforming-wet)| -|[iterative regularization with k-support norm: an important complement to sparse recovery](https://arxiv.org/abs/2401.05394)|[irksn_aaai2024](https://github.com/wdevazelhes/irksn_aaai2024)| -|[page: prototype-based model-level explanations for graph neural networks](https://arxiv.org/abs/2210.17159)|[page](https://github.com/jordan7186/page)| -|[s$\omega$i: score-based o-information estimation](https://arxiv.org/abs/2402.05667)|[soi](https://github.com/mustaphabounoua/soi)| +|date|paper|code| +|---|---|---| ## 2024-03-20 -|paper|code| -|---|---| -|[deep joint source-channel coding over cooperative relay networks](https://arxiv.org/abs/2211.06705)|[relay_jscc](https://github.com/aprilbian/relay_jscc)| -|[brain tumor detection based on a novel and high-quality prediction of the tumor pixel distributions](https://arxiv.org/abs/2308.07495)|[Brain-tumor-detection-based-on-a-novel-and-high-quality-prediction-of-the-tumor-pixel-distributions](https://github.com/YanmingSun/Brain-tumor-detection-based-on-a-novel-and-high-quality-prediction-of-the-tumor-pixel-distributions)| -|[hypergraph-mlp: learning on hypergraphs without message passing](https://arxiv.org/abs/2312.09778)|[hypergraph-mlp](https://github.com/tbh-98/hypergraph-mlp)| -|[guiding masked representation learning to capture spatio-temporal relationship of electrocardiogram](https://arxiv.org/abs/2402.09450)|[st-mem](https://github.com/bakqui/st-mem)| -|[sim2real in reconstructive spectroscopy: deep learning with augmented device-informed data simulation](https://arxiv.org/abs/2403.12354)|[rec_spectrometer](https://github.com/j1goblue/rec_spectrometer)| -|[finding the missing data: a bert-inspired approach against package loss in wireless sensing](https://arxiv.org/abs/2403.12400)|[csi-bert](https://github.com/rs2002/csi-bert)| -|[information decomposition in complex systems via machine learning](https://arxiv.org/abs/2307.04755)|[distributed-information-bottleneck.github.io](https://github.com/distributed-information-bottleneck/distributed-information-bottleneck.github.io)| -|[a fast and provable algorithm for sparse phase retrieval](https://arxiv.org/abs/2309.02046)|[sparsepr](https://github.com/jxying/sparsepr)| -|[language modeling is compression](https://arxiv.org/abs/2309.10668)|[language_modeling_is_compression](https://github.com/google-deepmind/language_modeling_is_compression)| +|date|paper|code| +|---|---|---| +|2403.12354|[sim2real in reconstructive spectroscopy: deep learning with augmented device-informed data simulation](https://arxiv.org/abs/2403.12354)|[rec_spectrometer](https://github.com/j1goblue/rec_spectrometer)| +|2403.12400|[finding the missing data: a bert-inspired approach against package loss in wireless sensing](https://arxiv.org/abs/2403.12400)|[csi-bert](https://github.com/rs2002/csi-bert)| ## 2024-03-19 -|paper|code| -|---|---| -|[deep nonnegative matrix factorization with beta divergences](https://arxiv.org/abs/2309.08249)|[deep-beta-nmf-public](https://github.com/vleplat/deep-beta-nmf-public)| -|[data-driven forced oscillation localization using inferred impulse responses](https://arxiv.org/abs/2310.01656)|[fo_local](https://github.com/shaohuiliu/fo_local)| -|[deep regularized compound gaussian network for solving linear inverse problems](https://arxiv.org/abs/2311.17248)|[dr-cg-net](https://github.com/clyons19/dr-cg-net)| -|[mains: a magnetic field aided inertial navigation system for indoor positioning](https://arxiv.org/abs/2312.02599)|[mainsvsmagekf](https://github.com/huang-chuan/mainsvsmagekf)| -|[selfeeg: a python library for self-supervised learning in electroencephalography](https://arxiv.org/abs/2401.05405)|[selfeeg](https://github.com/medmaxlab/selfeeg)| -|[a continuous boostlet transform for acoustic waves in space-time](https://arxiv.org/abs/2403.11362)|[acha_sparsityanalysis](https://github.com/eliaszea/acha_sparsityanalysis)| -|[a deep learning method for beat-level risk analysis and interpretation of atrial fibrillation patients during sinus rhythm](https://arxiv.org/abs/2403.11405)|[ecgbeat4afsinus](https://github.com/leijsen/ecgbeat4afsinus)| -|[specific emitter identification handling modulation variation with margin disparity discrepancy](https://arxiv.org/abs/2403.11531)|[mdd-sei](https://github.com/zhangyezhuo/mdd-sei)| -|[robust counterfactual explanations for neural networks with probabilistic guarantees](https://arxiv.org/abs/2305.11997)|[TReX-Counterfactuals](https://github.com/FaisalHamman/TReX-Counterfactuals)| +|date|paper|code| +|---|---|---| +|2403.11362|[a continuous boostlet transform for acoustic waves in space-time](https://arxiv.org/abs/2403.11362)|[acha_sparsityanalysis](https://github.com/eliaszea/acha_sparsityanalysis)| +|2403.11405|[a deep learning method for beat-level risk analysis and interpretation of atrial fibrillation patients during sinus rhythm](https://arxiv.org/abs/2403.11405)|[ecgbeat4afsinus](https://github.com/leijsen/ecgbeat4afsinus)| +|2403.11531|[specific emitter identification handling modulation variation with margin disparity discrepancy](https://arxiv.org/abs/2403.11531)|[mdd-sei](https://github.com/zhangyezhuo/mdd-sei)| ## 2024-03-18 -|paper|code| -|---|---| -|[a time-causal and time-recursive analogue of the gabor transform](https://arxiv.org/abs/2308.14512)|[pygabor](https://github.com/tonylindeberg/pygabor)| -|[a conversational brain-artificial intelligence interface](https://arxiv.org/abs/2402.15011)|[eegchat](https://github.com/akmeunier/eegchat)| -|[the information geometry of umap](https://arxiv.org/abs/2309.01237)|[info-geometry-umap](https://github.com/sashakolpakov/info-geometry-umap)| +|date|paper|code| +|---|---|---| ## 2024-03-15 -|paper|code| -|---|---| -|[compressing sign information in dct-based image coding via deep sign retrieval](https://arxiv.org/abs/2209.10712)|[dsr](https://github.com/ctsutake/dsr)| -|[uncertainty-aware and reliable neural mimo receivers via modular bayesian deep learning](https://arxiv.org/abs/2302.02436)|[bayesian-learning-for-receivers](https://github.com/tomerraviv95/bayesian-learning-for-receivers)| -|[model-free reinforcement learning of semantic communication by stochastic policy gradient](https://arxiv.org/abs/2305.03571)|[sinfony](https://github.com/ant-uni-bremen/sinfony)| -|[plug-and-play regularization on magnitude with deep priors for 3d near-field mimo imaging](https://arxiv.org/abs/2312.16024)|[PnP-Regularization-on-Magnitude](https://github.com/METU-SPACE-Lab/PnP-Regularization-on-Magnitude)| -|[visual decoding and reconstruction via eeg embeddings with guided diffusion](https://arxiv.org/abs/2403.07721)|[eeg_image_decode](https://github.com/dongyangli-del/eeg_image_decode)| -|[meta-learning-based fronthaul compression for cloud radio access networks](https://arxiv.org/abs/2403.09004)|[Meta-Learning-Fronthaul-Compression-CRAN](https://github.com/RuihuaQiao/Meta-Learning-Fronthaul-Compression-CRAN)| +|date|paper|code| +|---|---|---| +|2403.07721|[visual decoding and reconstruction via eeg embeddings with guided diffusion](https://arxiv.org/abs/2403.07721)|[eeg_image_decode](https://github.com/dongyangli-del/eeg_image_decode)| +|2403.09004|[meta-learning-based fronthaul compression for cloud radio access networks](https://arxiv.org/abs/2403.09004)|[Meta-Learning-Fronthaul-Compression-CRAN](https://github.com/RuihuaQiao/Meta-Learning-Fronthaul-Compression-CRAN)| ## 2024-03-14 -|paper|code| -|---|---| -|[slicertms: real-time visualization of transcranial magnetic stimulation for mental health treatment](https://arxiv.org/abs/2305.06459)|[SlicerTMS](https://github.com/lorifranke/SlicerTMS)| -|[structure-preserving transformers for sequences of spd matrices](https://arxiv.org/abs/2309.07579)|[spdtransnet](https://github.com/mathieuseraphim/spdtransnet)| +|date|paper|code| +|---|---|---| ## 2024-03-13 -|paper|code| -|---|---| -|[wimans: a benchmark dataset for wifi-based multi-user activity sensing](https://arxiv.org/abs/2402.09430)|[wimans](https://github.com/huangshk/wimans)| -|[exploring challenges in deep learning of single-station ground motion records](https://arxiv.org/abs/2403.07569)|[mage](https://github.com/caglarmert/mage)| -|[innovation processes for inference](https://arxiv.org/abs/2306.05186)|[InnovationProcessesInference](https://github.com/GiulioTani/InnovationProcessesInference)| -|[an efficient difference-of-convex solver for privacy funnel](https://arxiv.org/abs/2403.04778)|[dcaPF-torch](https://github.com/hui811116/dcaPF-torch)| +|date|paper|code| +|---|---|---| +|2403.07569|[exploring challenges in deep learning of single-station ground motion records](https://arxiv.org/abs/2403.07569)|[mage](https://github.com/caglarmert/mage)| +|2403.04778|[an efficient difference-of-convex solver for privacy funnel](https://arxiv.org/abs/2403.04778)|[dcaPF-torch](https://github.com/hui811116/dcaPF-torch)| ## 2024-03-12 -|paper|code| -|---|---| -|[tfn: an interpretable neural network with time-frequency transform embedded for intelligent fault diagnosis](https://arxiv.org/abs/2209.01992)|[tfn](https://github.com/chenqian0618/tfn)| -|[ul-dl duality for cell-free massive mimo with per-ap power and information constraints](https://arxiv.org/abs/2301.06520)|[duality](https://github.com/lorenzomiretti/duality)| -|[symmetric-reciprocal-match method for vector network analyzer calibration](https://arxiv.org/abs/2309.02886)|[srm-calibration](https://github.com/ZiadHatab/srm-calibration)| -|[guiding masked representation learning to capture spatio-temporal relationship of electrocardiogram](https://arxiv.org/abs/2402.09450)|[st-mem](https://github.com/bakqui/st-mem)| -|[blockchain-enabled variational information bottleneck for iot networks](https://arxiv.org/abs/2403.06129)|[blockchain-enabled-variational-information-bottleneck-for-iot-networks](https://github.com/qiongwu86/blockchain-enabled-variational-information-bottleneck-for-iot-networks)| -|[on the salient limitations of the methods of assembly theory and their classification of molecular biosignatures](https://arxiv.org/abs/2210.00901)|[mscomplexity](https://github.com/abicumaran/mscomplexity)| -|[learning unknown intervention targets in structural causal models from heterogeneous data](https://arxiv.org/abs/2312.06091)|[lit](https://github.com/yuqin-yang/lit)| -|[detection of unobserved common causes based on nml code in discrete, mixed, and continuous variables](https://arxiv.org/abs/2403.06499)|[cloud](https://github.com/matsushima-lab/cloud)| +|date|paper|code| +|---|---|---| +|2403.06129|[blockchain-enabled variational information bottleneck for iot networks](https://arxiv.org/abs/2403.06129)|[blockchain-enabled-variational-information-bottleneck-for-iot-networks](https://github.com/qiongwu86/blockchain-enabled-variational-information-bottleneck-for-iot-networks)| +|2403.06499|[detection of unobserved common causes based on nml code in discrete, mixed, and continuous variables](https://arxiv.org/abs/2403.06499)|[cloud](https://github.com/matsushima-lab/cloud)| ## 2024-03-11 -|paper|code| -|---|---| -|[blind source separation of single-channel mixtures via multi-encoder autoencoders](https://arxiv.org/abs/2309.07138)|[self-supervised-bss-via-multi-encoder-ae](https://github.com/webstah/self-supervised-bss-via-multi-encoder-ae)| -|[differentiable learning of generalized structured matrices for efficient deep neural networks](https://arxiv.org/abs/2310.18882)|[Gaudi-GBLR](https://github.com/changwoolee/Gaudi-GBLR)| -|[szcore: a seizure community open-source research evaluation framework for the validation of eeg-based automated seizure detection algorithms](https://arxiv.org/abs/2402.13005)|[epilepsy2bids](https://github.com/esl-epfl/epilepsy2bids)| -|[dero: dead reckoning based on radar odometry with accelerometers aided for robot localization](https://arxiv.org/abs/2403.05136)|[dero](https://github.com/hoangvietdo/dero)| -|[a decoupled approach for composite sparse-plus-smooth penalized optimization](https://arxiv.org/abs/2403.05204)|[compositesps](https://github.com/adriaj/compositesps)| -|[gan-based massive mimo channel model trained on measured data](https://arxiv.org/abs/2403.05321)|[gan-wireless-channel-model](https://github.com/jeija/gan-wireless-channel-model)| -|[bayes conditional distribution estimation for knowledge distillation based on conditional mutual information](https://arxiv.org/abs/2401.08732)|[iclrmcmi](https://github.com/iclr2024mcmi/iclrmcmi)| +|date|paper|code| +|---|---|---| +|2403.05136|[dero: dead reckoning based on radar odometry with accelerometers aided for robot localization](https://arxiv.org/abs/2403.05136)|[dero](https://github.com/hoangvietdo/dero)| +|2403.05204|[a decoupled approach for composite sparse-plus-smooth penalized optimization](https://arxiv.org/abs/2403.05204)|[compositesps](https://github.com/adriaj/compositesps)| +|2403.05321|[gan-based massive mimo channel model trained on measured data](https://arxiv.org/abs/2403.05321)|[gan-wireless-channel-model](https://github.com/jeija/gan-wireless-channel-model)| ## 2024-03-08 -|paper|code| -|---|---| -|[dtp-net: learning to reconstruct eeg signals in time-frequency domain by multi-scale feature reuse](https://arxiv.org/abs/2312.09417)|[eeg-denoise](https://github.com/williamro/eeg-denoise)| +|date|paper|code| +|---|---|---| ## 2024-03-07 -|paper|code| -|---|---| -|[structure-preserving transformers for sequences of spd matrices](https://arxiv.org/abs/2309.07579)|[spdtransnet](https://github.com/mathieuseraphim/spdtransnet)| -|[tsrnet: simple framework for real-time ecg anomaly detection with multimodal time and spectrogram restoration network](https://arxiv.org/abs/2312.10187)|[tsrnet](https://github.com/uark-aicv/tsrnet)| -|[brant-2: foundation model for brain signals](https://arxiv.org/abs/2402.10251)|[brant-2](https://github.com/yzz673/brant-2)| -|[arnn: attentive recurrent neural network for multi-channel eeg signals to identify epileptic seizures](https://arxiv.org/abs/2403.03276)|[arnn](https://github.com/salim-lysiun/arnn)| -|[diffusion-based generative prior for low-complexity mimo channel estimation](https://arxiv.org/abs/2403.03545)|[diffusion_channel_est](https://github.com/benediktfesl/diffusion_channel_est)| +|date|paper|code| +|---|---|---| +|2403.03276|[arnn: attentive recurrent neural network for multi-channel eeg signals to identify epileptic seizures](https://arxiv.org/abs/2403.03276)|[arnn](https://github.com/salim-lysiun/arnn)| +|2403.03545|[diffusion-based generative prior for low-complexity mimo channel estimation](https://arxiv.org/abs/2403.03545)|[diffusion_channel_est](https://github.com/benediktfesl/diffusion_channel_est)| ## 2024-03-05 -|paper|code| -|---|---| -|[matnet: multi-level fusion transformer-based model for day-ahead pv generation forecasting](https://arxiv.org/abs/2306.10356)|[matnet](https://github.com/cosbidev/matnet)| -|[improving robustness via tilted exponential layer: a communication-theoretic perspective](https://arxiv.org/abs/2311.01047)|[texp_for_robustness](https://github.com/bhagyapuranik/texp_for_robustness)| -|[neuro-gpt: towards a foundation model for eeg](https://arxiv.org/abs/2311.03764)|[neurogpt](https://github.com/wenhui0206/neurogpt)| -|[arbitrary discrete fourier analysis and its application in replayed speech detection](https://arxiv.org/abs/2403.01130)|[adfa](https://github.com/shihkuanglee/adfa)| -|[lum-vit: learnable under-sampling mask vision transformer for bandwidth limited optical signal acquisition](https://arxiv.org/abs/2403.01412)|[lum-vit](https://github.com/maxllf/lum-vit)| -|[powerskel: a device-free framework using csi signal for human skeleton estimation in power station](https://arxiv.org/abs/2403.01913)|[ckdformer](https://github.com/power-operation/ckdformer)| -|[hybrid quantum neural network advantage for radar-based drone detection and classification in low signal-to-noise ratio](https://arxiv.org/abs/2403.02080)|[hybrid-quantum-classical-Neural-Network-for-radar-data](https://github.com/AishSweety/hybrid-quantum-classical-Neural-Network-for-radar-data)| -|[neural estimation of the rate-distortion function with applications to operational source coding](https://arxiv.org/abs/2204.01612)|[nerd-rcc](https://github.com/leieric/nerd-rcc)| -|[exposing the deception: uncovering more forgery clues for deepfake detection](https://arxiv.org/abs/2403.01786)|[exposing-the-deception](https://github.com/qingyuliu/exposing-the-deception)| +|date|paper|code| +|---|---|---| +|2403.01130|[arbitrary discrete fourier analysis and its application in replayed speech detection](https://arxiv.org/abs/2403.01130)|[adfa](https://github.com/shihkuanglee/adfa)| +|2403.01412|[lum-vit: learnable under-sampling mask vision transformer for bandwidth limited optical signal acquisition](https://arxiv.org/abs/2403.01412)|[lum-vit](https://github.com/maxllf/lum-vit)| +|2403.01913|[powerskel: a device-free framework using csi signal for human skeleton estimation in power station](https://arxiv.org/abs/2403.01913)|[ckdformer](https://github.com/power-operation/ckdformer)| +|2403.02080|[hybrid quantum neural network advantage for radar-based drone detection and classification in low signal-to-noise ratio](https://arxiv.org/abs/2403.02080)|[hybrid-quantum-classical-Neural-Network-for-radar-data](https://github.com/AishSweety/hybrid-quantum-classical-Neural-Network-for-radar-data)| +|2403.01786|[exposing the deception: uncovering more forgery clues for deepfake detection](https://arxiv.org/abs/2403.01786)|[exposing-the-deception](https://github.com/qingyuliu/exposing-the-deception)| ## 2024-03-04 -|paper|code| -|---|---| -|[self-supervised learning for time series analysis: taxonomy, progress, and prospects](https://arxiv.org/abs/2306.10125)|[Awesome-SSL4TS](https://github.com/qingsongedu/Awesome-SSL4TS)| -|[active sensing for reciprocal mimo channels](https://arxiv.org/abs/2403.00134)|[active-sensing-for-reciprocal-mimo-channels](https://github.com/taojiang-github/active-sensing-for-reciprocal-mimo-channels)| -|[safeguarding data in multimodal ai: a differentially private approach to clip training](https://arxiv.org/abs/2306.08173)|[dpclip](https://github.com/dpclip/dpclip)| -|[stein variational guided model predictive path integral control: proposal and experiments with fast maneuvering vehicles](https://arxiv.org/abs/2309.11040)|[proj-svg_mppi](https://github.com/kohonda/proj-svg_mppi)| +|date|paper|code| +|---|---|---| +|2403.00134|[active sensing for reciprocal mimo channels](https://arxiv.org/abs/2403.00134)|[active-sensing-for-reciprocal-mimo-channels](https://github.com/taojiang-github/active-sensing-for-reciprocal-mimo-channels)| ## 2024-03-01 -|paper|code| -|---|---| -|[statistical component separation for targeted signal recovery in noisy mixtures](https://arxiv.org/abs/2306.15012)|[stat_comp_sep](https://github.com/bregaldo/stat_comp_sep)| -|[listening to the noise: blind denoising with gibbs diffusion](https://arxiv.org/abs/2402.19455)|[gibbs-diffusion](https://github.com/rubenohana/gibbs-diffusion)| -|[quantum state compression with polar codes](https://arxiv.org/abs/2402.18684)|[qscpolar](https://github.com/aviemathelec1995/qscpolar)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/04.md b/archives/2024/04.md index 5cbb1be8..4fa11ca6 100644 --- a/archives/2024/04.md +++ b/archives/2024/04.md @@ -1,175 +1,128 @@ # April 2024 Archive ## 2024-04-30 -|paper|code| -|---|---| -|[a new method of modeling the multi-stage decision-making process of crt using machine learning with uncertainty quantification](https://arxiv.org/abs/2309.08415)|[crt_multistageml_uncertainty](https://github.com/miilab-mtu/crt_multistageml_uncertainty)| -|[fully differentiable ray tracing via discontinuity smoothing for radio network optimization](https://arxiv.org/abs/2401.11882)|[differt2d](https://github.com/jeertmans/differt2d)| -|[siamquality: a convnet-based foundation model for imperfect physiological signals](https://arxiv.org/abs/2404.17667)|[siamquality](https://github.com/chengding0713/siamquality)| -|[cauchy-schwarz divergence information bottleneck for regression](https://arxiv.org/abs/2404.17951)|[cauchy-schwarz-information-bottleneck](https://github.com/sjyucnel/cauchy-schwarz-information-bottleneck)| +|date|paper|code| +|---|---|---| +|2404.17667|[siamquality: a convnet-based foundation model for imperfect physiological signals](https://arxiv.org/abs/2404.17667)|[siamquality](https://github.com/chengding0713/siamquality)| +|2404.17951|[cauchy-schwarz divergence information bottleneck for regression](https://arxiv.org/abs/2404.17951)|[cauchy-schwarz-information-bottleneck](https://github.com/sjyucnel/cauchy-schwarz-information-bottleneck)| ## 2024-04-29 -|paper|code| -|---|---| -|[the luvira dataset: synchronized vision, radio, and audio sensors for indoor localization](https://arxiv.org/abs/2302.05309)|[luvira_dataset](https://github.com/ilaydayaman/luvira_dataset)| -|[telco-rag: navigating the challenges of retrieval-augmented language models for telecommunications](https://arxiv.org/abs/2404.15939)|[telco-rag](https://github.com/netop-team/telco-rag)| -|[interpreting deepcode, a learned feedback code](https://arxiv.org/abs/2404.17519)|[deepcode-interpretability](https://github.com/zyy-cc/deepcode-interpretability)| -|[enumeration of minimum weight codewords of pre-transformed polar codes by tree intersection](https://arxiv.org/abs/2311.17774)|[ptpc](https://github.com/andreaszunker/ptpc)| +|date|paper|code| +|---|---|---| +|2404.15939|[telco-rag: navigating the challenges of retrieval-augmented language models for telecommunications](https://arxiv.org/abs/2404.15939)|[telco-rag](https://github.com/netop-team/telco-rag)| +|2404.17519|[interpreting deepcode, a learned feedback code](https://arxiv.org/abs/2404.17519)|[deepcode-interpretability](https://github.com/zyy-cc/deepcode-interpretability)| ## 2024-04-26 -|paper|code| -|---|---| -|[luvira dataset validation and discussion: comparing vision, radio, and audio sensors for indoor localization](https://arxiv.org/abs/2309.02961)|[luvira_dataset](https://github.com/ilaydayaman/luvira_dataset)| +|date|paper|code| +|---|---|---| ## 2024-04-25 -|paper|code| -|---|---| -|[mains: a magnetic field aided inertial navigation system for indoor positioning](https://arxiv.org/abs/2312.02599)|[mainsvsmagekf](https://github.com/huang-chuan/mainsvsmagekf)| -|[exponentially weighted moving models](https://arxiv.org/abs/2404.08136)|[ewmm_code](https://github.com/cvxgrp/ewmm_code)| -|[eegdir: electroencephalogram denoising network for temporal information storage and global modeling through retentive network](https://arxiv.org/abs/2404.15289)|[EEGDiR](https://github.com/woldier/EEGDiR)| -|[the largest eeg-based bci reproducibility study for open science: the moabb benchmark](https://arxiv.org/abs/2404.15319)|[moabb](https://github.com/NeuroTechX/moabb)| -|[comparing self-supervised learning techniques for wearable human activity recognition](https://arxiv.org/abs/2404.15331)|[self-supervised-learning-har](https://github.com/getalp/self-supervised-learning-har)| -|[classifier-guided neural blind deconvolution: a physics-informed denoising module for bearing fault diagnosis under heavy noise](https://arxiv.org/abs/2404.15341)|[classbd](https://github.com/asdvfghg/classbd)| -|[evaluating fast adaptability of neural networks for brain-computer interface](https://arxiv.org/abs/2404.15350)|[fast_bci](https://github.com/anp-scp/fast_bci)| -|[squwa: signal quality aware dnn architecture for enhanced accuracy in atrial fibrillation detection from noisy ppg signals](https://arxiv.org/abs/2404.15353)|[squwa](https://github.com/runz96/squwa)| -|[mp-dpd: low-complexity mixed-precision neural networks for energy-efficient digital predistortion of wideband power amplifiers](https://arxiv.org/abs/2404.15364)|[opendpd](https://github.com/lab-emi/opendpd)| -|[a weight-aware-based multi-source unsupervised domain adaptation method for human motion intention recognition](https://arxiv.org/abs/2404.15366)|[WMDD](https://github.com/xiaoyinliu0714/WMDD)| -|[leveraging visibility graphs for enhanced arrhythmia classification with graph convolutional networks](https://arxiv.org/abs/2404.15367)|[vg_for_arrhythmia_classification_with_gcn](https://github.com/raffoliveira/vg_for_arrhythmia_classification_with_gcn)| -|[unmasking the role of remote sensors in comfort, energy and demand response](https://arxiv.org/abs/2404.15368)|[sensors4singlezonesystems](https://github.com/inferlab/sensors4singlezonesystems)| -|[message-passing on hypergraphs: detectability, phase transitions and higher-order information](https://arxiv.org/abs/2312.00708)|[hypergraph-message-passing](https://github.com/nickruggeri/hypergraph-message-passing)| +|date|paper|code| +|---|---|---| +|2404.08136|[exponentially weighted moving models](https://arxiv.org/abs/2404.08136)|[ewmm_code](https://github.com/cvxgrp/ewmm_code)| +|2404.15289|[eegdir: electroencephalogram denoising network for temporal information storage and global modeling through retentive network](https://arxiv.org/abs/2404.15289)|[EEGDiR](https://github.com/woldier/EEGDiR)| +|2404.15319|[the largest eeg-based bci reproducibility study for open science: the moabb benchmark](https://arxiv.org/abs/2404.15319)|[moabb](https://github.com/NeuroTechX/moabb)| +|2404.15331|[comparing self-supervised learning techniques for wearable human activity recognition](https://arxiv.org/abs/2404.15331)|[self-supervised-learning-har](https://github.com/getalp/self-supervised-learning-har)| +|2404.15341|[classifier-guided neural blind deconvolution: a physics-informed denoising module for bearing fault diagnosis under heavy noise](https://arxiv.org/abs/2404.15341)|[classbd](https://github.com/asdvfghg/classbd)| +|2404.15350|[evaluating fast adaptability of neural networks for brain-computer interface](https://arxiv.org/abs/2404.15350)|[fast_bci](https://github.com/anp-scp/fast_bci)| +|2404.15353|[squwa: signal quality aware dnn architecture for enhanced accuracy in atrial fibrillation detection from noisy ppg signals](https://arxiv.org/abs/2404.15353)|[squwa](https://github.com/runz96/squwa)| +|2404.15364|[mp-dpd: low-complexity mixed-precision neural networks for energy-efficient digital predistortion of wideband power amplifiers](https://arxiv.org/abs/2404.15364)|[opendpd](https://github.com/lab-emi/opendpd)| +|2404.15366|[a weight-aware-based multi-source unsupervised domain adaptation method for human motion intention recognition](https://arxiv.org/abs/2404.15366)|[WMDD](https://github.com/xiaoyinliu0714/WMDD)| +|2404.15367|[leveraging visibility graphs for enhanced arrhythmia classification with graph convolutional networks](https://arxiv.org/abs/2404.15367)|[vg_for_arrhythmia_classification_with_gcn](https://github.com/raffoliveira/vg_for_arrhythmia_classification_with_gcn)| +|2404.15368|[unmasking the role of remote sensors in comfort, energy and demand response](https://arxiv.org/abs/2404.15368)|[sensors4singlezonesystems](https://github.com/inferlab/sensors4singlezonesystems)| ## 2024-04-23 -|paper|code| -|---|---| -|[using explainable ai to investigate electrocardiogram changes during healthy aging -- from expert features to raw signals](https://arxiv.org/abs/2310.07463)|[ecg-aging](https://github.com/ai4healthuol/ecg-aging)| -|[a multimodal feature distillation with cnn-transformer network for brain tumor segmentation with incomplete modalities](https://arxiv.org/abs/2404.14019)|[mctseg](https://github.com/mkang315/mctseg)| -|[collaborative filtering based on diffusion models: unveiling the potential of high-order connectivity](https://arxiv.org/abs/2404.14240)|[cf_diff](https://github.com/jackfrost168/cf_diff)| -|[turbo-cf: matrix decomposition-free graph filtering for fast recommendation](https://arxiv.org/abs/2404.14243)|[turbo-cf](https://github.com/jindeok/turbo-cf)| +|date|paper|code| +|---|---|---| +|2404.14019|[a multimodal feature distillation with cnn-transformer network for brain tumor segmentation with incomplete modalities](https://arxiv.org/abs/2404.14019)|[mctseg](https://github.com/mkang315/mctseg)| +|2404.14240|[collaborative filtering based on diffusion models: unveiling the potential of high-order connectivity](https://arxiv.org/abs/2404.14240)|[cf_diff](https://github.com/jackfrost168/cf_diff)| +|2404.14243|[turbo-cf: matrix decomposition-free graph filtering for fast recommendation](https://arxiv.org/abs/2404.14243)|[turbo-cf](https://github.com/jindeok/turbo-cf)| ## 2024-04-22 -|paper|code| -|---|---| -|[ul-dl duality for cell-free massive mimo with per-ap power and information constraints](https://arxiv.org/abs/2301.06520)|[duality](https://github.com/lorenzomiretti/duality)| -|[frequency-aware masked autoencoders for multimodal pretraining on biosignals](https://arxiv.org/abs/2309.05927)|[ml-famae](https://github.com/apple/ml-famae)| +|date|paper|code| +|---|---|---| ## 2024-04-19 -|paper|code| -|---|---| -|[incremental measurement of structural entropy for dynamic graphs](https://arxiv.org/abs/2207.12653)|[incre-se](https://github.com/yangrunze1013/incre-se)| +|date|paper|code| +|---|---|---| ## 2024-04-18 -|paper|code| -|---|---| -|[the luvira dataset: measurement description](https://arxiv.org/abs/2302.05309)|[luvira_dataset](https://github.com/ilaydayaman/luvira_dataset)| -|[caster: a computer-vision-assisted wireless channel simulator for gesture recognition](https://arxiv.org/abs/2311.07169)|[testspectrogram](https://github.com/rzy0901/testspectrogram)| -|[diffdet4sar: diffusion-based aircraft target detection network for sar images](https://arxiv.org/abs/2404.03595)|[DiffDet4SAR](https://github.com/JoyeZLearning/DiffDet4SAR)| -|[sky-gvio: an enhanced gnss/ins/vision navigation with fcn-based sky-segmentation in urban canyon](https://arxiv.org/abs/2404.11070)|[sky-view-images](https://github.com/whuwangjr/sky-view-images)| -|[personalized heart disease detection via ecg digital twin generation](https://arxiv.org/abs/2404.11171)|[lavq-editor](https://github.com/huyjj/lavq-editor)| -|[on the salient limitations of the methods of assembly theory and their classification of molecular biosignatures](https://arxiv.org/abs/2210.00901)|[mscomplexity](https://github.com/abicumaran/mscomplexity)| +|date|paper|code| +|---|---|---| +|2404.03595|[diffdet4sar: diffusion-based aircraft target detection network for sar images](https://arxiv.org/abs/2404.03595)|[DiffDet4SAR](https://github.com/JoyeZLearning/DiffDet4SAR)| +|2404.11070|[sky-gvio: an enhanced gnss/ins/vision navigation with fcn-based sky-segmentation in urban canyon](https://arxiv.org/abs/2404.11070)|[sky-view-images](https://github.com/whuwangjr/sky-view-images)| +|2404.11171|[personalized heart disease detection via ecg digital twin generation](https://arxiv.org/abs/2404.11171)|[lavq-editor](https://github.com/huyjj/lavq-editor)| ## 2024-04-17 -|paper|code| -|---|---| -|[wemac: women and emotion multi-modal affective computing dataset](https://arxiv.org/abs/2203.00456)|[wemac_dataset_speech_processing](https://github.com/bindi-uc3m/wemac_dataset_speech_processing)| +|date|paper|code| +|---|---|---| ## 2024-04-16 -|paper|code| -|---|---| -|[on interference-rejection using riemannian geometry for direction of arrival estimation](https://arxiv.org/abs/2301.03399)|[interference-rejection-using-riemannian-geometry-for-doa-estimation](https://github.com/amitaybar/interference-rejection-using-riemannian-geometry-for-doa-estimation)| -|[impact analysis of antenna array geometry on performance of semi-blind structured channel estimation for massive mimo-ofdm systems](https://arxiv.org/abs/2305.09263)|[CRB_of_3D_Antenna_Arrays_on_Performance_of_Semi-blind_Structured_Channel_Estimation](https://github.com/DoHaiSon/CRB_of_3D_Antenna_Arrays_on_Performance_of_Semi-blind_Structured_Channel_Estimation)| -|[on the semi-blind mutually referenced equalizers for mimo systems](https://arxiv.org/abs/2311.00325)|[Semi-blind_Mutually_Referenced_Equalizers](https://github.com/DoHaiSon/Semi-blind_Mutually_Referenced_Equalizers)| -|[rf-diffusion: radio signal generation via time-frequency diffusion](https://arxiv.org/abs/2404.09140)|[rf-diffusion](https://github.com/mobicom24/rf-diffusion)| -|[foundational gpt model for meg](https://arxiv.org/abs/2404.09256)|[meg-transfer-decoding](https://github.com/ricsinaruto/meg-transfer-decoding)| -|[leveraging the doppler effect for channel charting](https://arxiv.org/abs/2404.09620)|[doppler-effect-channelcharting](https://github.com/jeija/doppler-effect-channelcharting)| -|[openairlink: reproducible wireless channel emulation using software defined radios](https://arxiv.org/abs/2404.09660)|[openairlink](https://github.com/n3martix/openairlink)| -|[amplitude-phase fusion for enhanced electrocardiogram morphological analysis](https://arxiv.org/abs/2404.09729)|[ecg-mee-metric](https://github.com/fdu-harry/ecg-mee-metric)| -|[compression represents intelligence linearly](https://arxiv.org/abs/2404.09937)|[llm-compression-intelligence](https://github.com/hkust-nlp/llm-compression-intelligence)| +|date|paper|code| +|---|---|---| +|2404.09140|[rf-diffusion: radio signal generation via time-frequency diffusion](https://arxiv.org/abs/2404.09140)|[rf-diffusion](https://github.com/mobicom24/rf-diffusion)| +|2404.09256|[foundational gpt model for meg](https://arxiv.org/abs/2404.09256)|[meg-transfer-decoding](https://github.com/ricsinaruto/meg-transfer-decoding)| +|2404.09620|[leveraging the doppler effect for channel charting](https://arxiv.org/abs/2404.09620)|[doppler-effect-channelcharting](https://github.com/jeija/doppler-effect-channelcharting)| +|2404.09660|[openairlink: reproducible wireless channel emulation using software defined radios](https://arxiv.org/abs/2404.09660)|[openairlink](https://github.com/n3martix/openairlink)| +|2404.09729|[amplitude-phase fusion for enhanced electrocardiogram morphological analysis](https://arxiv.org/abs/2404.09729)|[ecg-mee-metric](https://github.com/fdu-harry/ecg-mee-metric)| +|2404.09937|[compression represents intelligence linearly](https://arxiv.org/abs/2404.09937)|[llm-compression-intelligence](https://github.com/hkust-nlp/llm-compression-intelligence)| ## 2024-04-15 -|paper|code| -|---|---| -|[near-field velocity sensing and predictive beamforming](https://arxiv.org/abs/2311.09888)|[near-field-velocity-sensing-and-predictive-beamforming](https://github.com/zhaolin820/near-field-velocity-sensing-and-predictive-beamforming)| -|[interpretation of intracardiac electrograms through textual representations](https://arxiv.org/abs/2402.01115)|[text-egm](https://github.com/willxxy/text-egm)| -|[exponentially weighted moving models](https://arxiv.org/abs/2404.08136)|[ewmm_code](https://github.com/cvxgrp/ewmm_code)| -|[snake-fmri: a modular fmri data simulator from the space-time domain to k-space and back](https://arxiv.org/abs/2404.08282)|[snake-fmri](https://github.com/paquiteau/snake-fmri)| +|date|paper|code| +|---|---|---| +|2404.08136|[exponentially weighted moving models](https://arxiv.org/abs/2404.08136)|[ewmm_code](https://github.com/cvxgrp/ewmm_code)| +|2404.08282|[snake-fmri: a modular fmri data simulator from the space-time domain to k-space and back](https://arxiv.org/abs/2404.08282)|[snake-fmri](https://github.com/paquiteau/snake-fmri)| ## 2024-04-12 -|paper|code| -|---|---| -|[cell-free multi-user mimo equalization via in-context learning](https://arxiv.org/abs/2404.05538)|[cell-free-mimo-icl](https://github.com/kclip/cell-free-mimo-icl)| -|[trainable joint channel estimation, detection and decoding for mimo urllc systems](https://arxiv.org/abs/2404.07721)|[jcddnet](https://github.com/sunyi0101/jcddnet)| -|[demystifying why local aggregation helps: convergence analysis of hierarchical sgd](https://arxiv.org/abs/2010.12998)|[hierarchical-sgd](https://github.com/c3atuofu/hierarchical-sgd)| -|[on naisargik images of varshamov-tenengolts and helberg codes](https://arxiv.org/abs/2404.07670)|[grayvt](https://github.com/guptalab/grayvt)| +|date|paper|code| +|---|---|---| +|2404.05538|[cell-free multi-user mimo equalization via in-context learning](https://arxiv.org/abs/2404.05538)|[cell-free-mimo-icl](https://github.com/kclip/cell-free-mimo-icl)| +|2404.07721|[trainable joint channel estimation, detection and decoding for mimo urllc systems](https://arxiv.org/abs/2404.07721)|[jcddnet](https://github.com/sunyi0101/jcddnet)| +|2404.07670|[on naisargik images of varshamov-tenengolts and helberg codes](https://arxiv.org/abs/2404.07670)|[grayvt](https://github.com/guptalab/grayvt)| ## 2024-04-11 -|paper|code| -|---|---| -|[what is learnt by the learnable front-end (leaf)? adapting per-channel energy normalisation (pcen) to noisy conditions](https://arxiv.org/abs/2404.06702)|[adapting-leaf](https://github.com/hanyu-meng/adapting-leaf)| -|[quantum message-passing algorithm for optimal and efficient decoding](https://arxiv.org/abs/2109.08170)|[quantum-message-passing-paper](https://github.com/chripiv/quantum-message-passing-paper)| -|[on the salient limitations of the methods of assembly theory and their classification of molecular biosignatures](https://arxiv.org/abs/2210.00901)|[mscomplexity](https://github.com/abicumaran/mscomplexity)| +|date|paper|code| +|---|---|---| +|2404.06702|[what is learnt by the learnable front-end (leaf)? adapting per-channel energy normalisation (pcen) to noisy conditions](https://arxiv.org/abs/2404.06702)|[adapting-leaf](https://github.com/hanyu-meng/adapting-leaf)| ## 2024-04-10 -|paper|code| -|---|---| -|[synaptogen: a cross-domain generative device model for large-scale neuromorphic circuit design](https://arxiv.org/abs/2404.06344)|[synaptogen](https://github.com/thennen/synaptogen)| -|[efficient computation of the quantum rate-distortion function](https://arxiv.org/abs/2309.15919)|[efficient-qrd](https://github.com/kerry-he/efficient-qrd)| -|[just wing it: optimal estimation of missing mass in a markovian sequence](https://arxiv.org/abs/2404.05819)|[missing-mass](https://github.com/andrewthan/missing-mass)| +|date|paper|code| +|---|---|---| +|2404.06344|[synaptogen: a cross-domain generative device model for large-scale neuromorphic circuit design](https://arxiv.org/abs/2404.06344)|[synaptogen](https://github.com/thennen/synaptogen)| +|2404.05819|[just wing it: optimal estimation of missing mass in a markovian sequence](https://arxiv.org/abs/2404.05819)|[missing-mass](https://github.com/andrewthan/missing-mass)| ## 2024-04-09 -|paper|code| -|---|---| -|[self-supervised learning for time series analysis: taxonomy, progress, and prospects](https://arxiv.org/abs/2306.10125)|[Awesome-SSL4TS](https://github.com/qingsongedu/Awesome-SSL4TS)| -|[k-band: self-supervised mri reconstruction via stochastic gradient descent over k-space subsets](https://arxiv.org/abs/2308.02958)|[k-band](https://github.com/mikgroup/k-band)| -|[subspace phase retrieval](https://arxiv.org/abs/2206.02480)|[spr](https://github.com/mengchuxu97/spr)| -|[multi-sources information fusion learning for multi-points nlos localization](https://arxiv.org/abs/2401.12538)|[AMDNloc](https://github.com/Horizontal666/AMDNloc)| +|date|paper|code| +|---|---|---| ## 2024-04-08 -|paper|code| -|---|---| -|[visual decoding and reconstruction via eeg embeddings with guided diffusion](https://arxiv.org/abs/2403.07721)|[eeg_image_decode](https://github.com/dongyangli-del/eeg_image_decode)| -|[diffdet4sar: diffusion-based aircraft target detection network for sar images](https://arxiv.org/abs/2404.03595)|[DiffDet4SAR](https://github.com/JoyeZLearning/DiffDet4SAR)| +|date|paper|code| +|---|---|---| +|2404.03595|[diffdet4sar: diffusion-based aircraft target detection network for sar images](https://arxiv.org/abs/2404.03595)|[DiffDet4SAR](https://github.com/JoyeZLearning/DiffDet4SAR)| ## 2024-04-05 -|paper|code| -|---|---| -|[decoding natural images from eeg for object recognition](https://arxiv.org/abs/2308.13234)|[nice-eeg](https://github.com/eeyhsong/nice-eeg)| -|[reinforcement learning based dynamic power control for uav mobility management](https://arxiv.org/abs/2312.04742)|[asilomar-2023-ee-uav-varying-reliability](https://github.com/irshadmeer/asilomar-2023-ee-uav-varying-reliability)| -|[spatio-spectral structure tensor total variation for hyperspectral image denoising and destriping](https://arxiv.org/abs/2404.03313)|[spatio-spectral-structure-tensor-total-variation-for-hyperspectral-image-denoising-and-destriping](https://github.com/mdi-tokyotech/spatio-spectral-structure-tensor-total-variation-for-hyperspectral-image-denoising-and-destriping)| -|[alzheimer's disease detection in psg signals](https://arxiv.org/abs/2404.03549)|[DL4ADpred](https://github.com/LorenaGallego/DL4ADpred)| -|[bcamirs at semeval-2024 task 4: beyond words: a multimodal and multilingual exploration of persuasion in memes](https://arxiv.org/abs/2404.03022)|[beyond-words-a-multimodal-exploration-of-persuasion-in-memes](https://github.com/amirabaskohi/beyond-words-a-multimodal-exploration-of-persuasion-in-memes)| -|[early warning systems for financial markets of emerging economies](https://arxiv.org/abs/2404.03319)|[ews_condent](https://github.com/kraevskiyaa/ews_condent)| -|[approximate gradient coding for privacy-flexible federated learning with non-iid data](https://arxiv.org/abs/2404.03524)|[label-heterogeneity](https://github.com/okkomakkonen/label-heterogeneity)| +|date|paper|code| +|---|---|---| +|2404.03313|[spatio-spectral structure tensor total variation for hyperspectral image denoising and destriping](https://arxiv.org/abs/2404.03313)|[spatio-spectral-structure-tensor-total-variation-for-hyperspectral-image-denoising-and-destriping](https://github.com/mdi-tokyotech/spatio-spectral-structure-tensor-total-variation-for-hyperspectral-image-denoising-and-destriping)| +|2404.03549|[alzheimer's disease detection in psg signals](https://arxiv.org/abs/2404.03549)|[DL4ADpred](https://github.com/LorenaGallego/DL4ADpred)| +|2404.03022|[bcamirs at semeval-2024 task 4: beyond words: a multimodal and multilingual exploration of persuasion in memes](https://arxiv.org/abs/2404.03022)|[beyond-words-a-multimodal-exploration-of-persuasion-in-memes](https://github.com/amirabaskohi/beyond-words-a-multimodal-exploration-of-persuasion-in-memes)| +|2404.03319|[early warning systems for financial markets of emerging economies](https://arxiv.org/abs/2404.03319)|[ews_condent](https://github.com/kraevskiyaa/ews_condent)| +|2404.03524|[approximate gradient coding for privacy-flexible federated learning with non-iid data](https://arxiv.org/abs/2404.03524)|[label-heterogeneity](https://github.com/okkomakkonen/label-heterogeneity)| ## 2024-04-04 -|paper|code| -|---|---| -|[gegenbauer graph neural networks for time-varying signal reconstruction](https://arxiv.org/abs/2403.19800)|[gegengnn](https://github.com/jcastro295/gegengnn)| +|date|paper|code| +|---|---|---| ## 2024-04-03 -|paper|code| -|---|---| -|[signal2image modules in deep neural networks for eeg classification](https://arxiv.org/abs/1904.13216)|[signal2image-modules-in-deep-neural-networks-for-eeg-classification](https://github.com/pbizopoulos/signal2image-modules-in-deep-neural-networks-for-eeg-classification)| -|[learned kernels for sparse, interpretable, and efficient medical time series processing](https://arxiv.org/abs/2307.05385)|[smolk](https://github.com/sullychen/smolk)| +|date|paper|code| +|---|---|---| ## 2024-04-02 -|paper|code| -|---|---| -|[visually evaluating generative adversarial networks using itself under multivariate time series](https://arxiv.org/abs/2208.02649)|[GaussianGANs](https://github.com/jack-pan-ai/GaussianGANs)| -|[task-oriented communication for edge video analytics](https://arxiv.org/abs/2211.14049)|[tocom-tem](https://github.com/shaojiawei07/tocom-tem)| -|[computational solar energy -- ensemble learning methods for prediction of solar power generation based on meteorological parameters in eastern india](https://arxiv.org/abs/2301.10159)|[solar_energy_prediction_srra](https://github.com/debojyoti7/solar_energy_prediction_srra)| -|[danse: data-driven non-linear state estimation of model-free process in unsupervised learning setup](https://arxiv.org/abs/2306.03897)|[danse-jrnl](https://github.com/saikatchatt/danse-jrnl)| -|[sdemg: score-based diffusion model for surface electromyographic signal denoising](https://arxiv.org/abs/2402.03808)|[sdemg](https://github.com/tonyliu0910/sdemg)| -|[complex neural network based joint aoa and aod estimation for bistatic isac](https://arxiv.org/abs/2404.00582)|[bistatic_isac](https://github.com/salmane-s9/bistatic_isac)| +|date|paper|code| +|---|---|---| +|2404.00582|[complex neural network based joint aoa and aod estimation for bistatic isac](https://arxiv.org/abs/2404.00582)|[bistatic_isac](https://github.com/salmane-s9/bistatic_isac)| ## 2024-04-01 -|paper|code| -|---|---| -|[square root lasso: well-posedness, lipschitz stability and the tuning trade off](https://arxiv.org/abs/2303.15588)|[srlasso_revolutions](https://github.com/asberk/srlasso_revolutions)| -|[exact recovery of the support of piecewise constant images via total variation regularization](https://arxiv.org/abs/2307.03709)|[2023-support-recovery-tv](https://github.com/rpetit/2023-support-recovery-tv)| -|[algorithms for non-negative matrix factorization on noisy data with negative values](https://arxiv.org/abs/2311.04855)|[nearly_nmf](https://github.com/dylanagreen/nearly_nmf)| -|[3d-speaker-toolkit: an open source toolkit for multi-modal speaker verification and diarization](https://arxiv.org/abs/2403.19971)|[3D-Speaker](https://github.com/alibaba-damo-academy/3D-Speaker)| -|[dual simplex volume maximization for simplex-structured matrix factorization](https://arxiv.org/abs/2403.20197)|[maxvol_dual](https://github.com/mabdolali/maxvol_dual)| -|[evolving semantic communication with generative model](https://arxiv.org/abs/2403.20237)|[gan_secom](https://github.com/recusant7/gan_secom)| -|[localising the seizure onset zone from single-pulse electrical stimulation responses with a transformer](https://arxiv.org/abs/2403.20324)|[localising_soz_from_spes](https://github.com/norrisjamie23/localising_soz_from_spes)| -|[greedy poisson rejection sampling](https://arxiv.org/abs/2305.15313)|[greedy-poisson-rejection-sampling](https://github.com/gergely-flamich/greedy-poisson-rejection-sampling)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/05.md b/archives/2024/05.md index 700fa3e0..935a3d20 100644 --- a/archives/2024/05.md +++ b/archives/2024/05.md @@ -1,179 +1,126 @@ # May 2024 Archive ## 2024-05-31 -|paper|code| -|---|---| -|[a large-scale evaluation of speech foundation models](https://arxiv.org/abs/2404.09385)|[s3prl](https://github.com/s3prl/s3prl)| -|[eeg-dbnet: a dual-branch network for temporal-spectral decoding in motor-imagery brain-computer interfaces](https://arxiv.org/abs/2405.16090)|[eeg-dbnet](https://github.com/xicheng105/eeg-dbnet)| -|[medformer: a multi-granularity patching transformer for medical time-series classification](https://arxiv.org/abs/2405.19363)|[medformer](https://github.com/dl4mhealth/medformer)| +|date|paper|code| +|---|---|---| +|2405.16090|[eeg-dbnet: a dual-branch network for temporal-spectral decoding in motor-imagery brain-computer interfaces](https://arxiv.org/abs/2405.16090)|[eeg-dbnet](https://github.com/xicheng105/eeg-dbnet)| +|2405.19363|[medformer: a multi-granularity patching transformer for medical time-series classification](https://arxiv.org/abs/2405.19363)|[medformer](https://github.com/dl4mhealth/medformer)| ## 2024-05-30 -|paper|code| -|---|---| -|[signal processing meets sgd: from momentum to filter](https://arxiv.org/abs/2311.02818)|[SGDF-Optimizer](https://github.com/LilYau350/SGDF-Optimizer)| -|[faultformer: pretraining transformers for adaptable bearing fault classification](https://arxiv.org/abs/2312.02380)|[faultformer](https://github.com/anthonyzhou-1/faultformer)| -|[random forests for detecting weak signals and extracting physical information: a case study of magnetic navigation](https://arxiv.org/abs/2402.14131)|[magnav](https://github.com/aminmoradixl/magnav)| -|[on the properties and estimation of pointwise mutual information profiles](https://arxiv.org/abs/2310.10240)|[bmi](https://github.com/cbg-ethz/bmi)| -|[track initialization and re-identification for~3d multi-view multi-object tracking](https://arxiv.org/abs/2405.18606)|[mv-glmb-ab](https://github.com/linh-gist/mv-glmb-ab)| +|date|paper|code| +|---|---|---| +|2405.18606|[track initialization and re-identification for~3d multi-view multi-object tracking](https://arxiv.org/abs/2405.18606)|[mv-glmb-ab](https://github.com/linh-gist/mv-glmb-ab)| ## 2024-05-29 -|paper|code| -|---|---| -|[assessment of unsteady flow predictions using hybrid deep learning based reduced order models](https://arxiv.org/abs/2009.04396)|[Assessment-of-hybrid-DLROM](https://github.com/rachit1307-code/Assessment-of-hybrid-DLROM)| -|[multi-device task-oriented communication via maximal coding rate reduction](https://arxiv.org/abs/2309.02888)|[taskcommmcr2](https://github.com/chang-cai/taskcommmcr2)| -|[structure-preserving transformers for sequences of spd matrices](https://arxiv.org/abs/2309.07579)|[spdtransnet](https://github.com/mathieuseraphim/spdtransnet)| -|[sleepfm: multi-modal representation learning for sleep across brain activity, ecg and respiratory signals](https://arxiv.org/abs/2405.17766)|[sleepfm-codebase](https://github.com/rthapa84/sleepfm-codebase)| -|[mambavc: learned visual compression with selective state spaces](https://arxiv.org/abs/2405.15413)|[2024-mambavc](https://github.com/qinsy123/2024-mambavc)| +|date|paper|code| +|---|---|---| +|2405.17766|[sleepfm: multi-modal representation learning for sleep across brain activity, ecg and respiratory signals](https://arxiv.org/abs/2405.17766)|[sleepfm-codebase](https://github.com/rthapa84/sleepfm-codebase)| +|2405.15413|[mambavc: learned visual compression with selective state spaces](https://arxiv.org/abs/2405.15413)|[2024-mambavc](https://github.com/qinsy123/2024-mambavc)| ## 2024-05-28 -|paper|code| -|---|---| -|[enn: a neural network with dct adaptive activation functions](https://arxiv.org/abs/2307.00673)|[enn](https://github.com/marcmartinezgost/enn)| -|[physics-informed appliance signatures generator for energy disaggregation](https://arxiv.org/abs/2401.01828)|[edframe](https://github.com/arx7ti/edframe)| -|[wav-kan: wavelet kolmogorov-arnold networks](https://arxiv.org/abs/2405.12832)|[Wav-KAN](https://github.com/zavareh1/Wav-KAN)| +|date|paper|code| +|---|---|---| +|2405.12832|[wav-kan: wavelet kolmogorov-arnold networks](https://arxiv.org/abs/2405.12832)|[Wav-KAN](https://github.com/zavareh1/Wav-KAN)| ## 2024-05-27 -|paper|code| -|---|---| -|[analog or digital in-memory computing? benchmarking through quantitative modeling](https://arxiv.org/abs/2405.14978)|[zigzag-imc](https://github.com/KULeuven-MICAS/zigzag-imc)| -|[perfect codes over non-prime power alphabets: an approach based on diophantine equations](https://arxiv.org/abs/2405.03347)|[perfect-q-ary-codes](https://github.com/pjcazorla/perfect-q-ary-codes)| +|date|paper|code| +|---|---|---| +|2405.14978|[analog or digital in-memory computing? benchmarking through quantitative modeling](https://arxiv.org/abs/2405.14978)|[zigzag-imc](https://github.com/KULeuven-MICAS/zigzag-imc)| +|2405.03347|[perfect codes over non-prime power alphabets: an approach based on diophantine equations](https://arxiv.org/abs/2405.03347)|[perfect-q-ary-codes](https://github.com/pjcazorla/perfect-q-ary-codes)| ## 2024-05-24 -|paper|code| -|---|---| -|[k-band: self-supervised mri reconstruction via stochastic gradient descent over k-space subsets](https://arxiv.org/abs/2308.02958)|[k-band](https://github.com/mikgroup/k-band)| -|[eegdir: electroencephalogram denoising network for temporal information storage and global modeling through retentive network](https://arxiv.org/abs/2404.15289)|[EEGDiR](https://github.com/woldier/EEGDiR)| -|[a truly concurrent semantics for reversible ccs](https://arxiv.org/abs/2309.14011)|[reversible-ccs-as-nets](https://github.com/hmelgra/reversible-ccs-as-nets)| +|date|paper|code| +|---|---|---| ## 2024-05-22 -|paper|code| -|---|---| -|[optimizing polynomial graph filters: a novel adaptive krylov subspace approach](https://arxiv.org/abs/2403.07954)|[AdaptKry](https://github.com/kkhuang81/AdaptKry)| -|[an efficient compression method for sign information of dct coefficients via sign retrieval](https://arxiv.org/abs/2405.07487)|[sr](https://github.com/ctsutake/sr)| +|date|paper|code| +|---|---|---| +|2405.07487|[an efficient compression method for sign information of dct coefficients via sign retrieval](https://arxiv.org/abs/2405.07487)|[sr](https://github.com/ctsutake/sr)| ## 2024-05-21 -|paper|code| -|---|---| -|[surrogate-based cross-correlation for particle image velocimetry](https://arxiv.org/abs/2112.05303)|[sbcc](https://github.com/yongleex/sbcc)| -|[discrete approximations of gaussian smoothing and gaussian derivatives](https://arxiv.org/abs/2311.11317)|[pyscsp](https://github.com/tonylindeberg/pyscsp)| -|[rscnet: dynamic csi compression for cloud-based wifi sensing](https://arxiv.org/abs/2402.04888)|[rscnet](https://github.com/bornabr/rscnet)| -|[approximation properties relative to continuous scale space for hybrid discretizations of gaussian derivative operators](https://arxiv.org/abs/2405.05095)|[pyscsp](https://github.com/tonylindeberg/pyscsp)| -|[mamca -- optimal on accuracy and efficiency for automatic modulation classification with extended signal length](https://arxiv.org/abs/2405.11263)|[mamca](https://github.com/zhangyezhuo/mamca)| -|[interpretable diffusion via information decomposition](https://arxiv.org/abs/2310.07972)|[info-decomp](https://github.com/kxh001/info-decomp)| -|[differentially private fair binary classifications](https://arxiv.org/abs/2402.15603)|[dp_fair_binary](https://github.com/hradghoukasian/dp_fair_binary)| +|date|paper|code| +|---|---|---| +|2405.05095|[approximation properties relative to continuous scale space for hybrid discretizations of gaussian derivative operators](https://arxiv.org/abs/2405.05095)|[pyscsp](https://github.com/tonylindeberg/pyscsp)| +|2405.11263|[mamca -- optimal on accuracy and efficiency for automatic modulation classification with extended signal length](https://arxiv.org/abs/2405.11263)|[mamca](https://github.com/zhangyezhuo/mamca)| ## 2024-05-20 -|paper|code| -|---|---| -|[exploring new territory: calibration-free decoding for c-vep bci](https://arxiv.org/abs/2403.15521)|[pyntbci](https://github.com/thijor/pyntbci)| -|[robust beamforming with gradient-based liquid neural network](https://arxiv.org/abs/2405.07291)|[GLNN](https://github.com/tp1000d/GLNN)| +|date|paper|code| +|---|---|---| +|2405.07291|[robust beamforming with gradient-based liquid neural network](https://arxiv.org/abs/2405.07291)|[GLNN](https://github.com/tp1000d/GLNN)| ## 2024-05-17 -|paper|code| -|---|---| -|[$f$-divergence based classification: beyond the use of cross-entropy](https://arxiv.org/abs/2401.01268)|[discriminative-classification-fdiv](https://github.com/tonellolab/discriminative-classification-fdiv)| -|[kid-ppg: knowledge informed deep learning for extracting heart rate from a smartwatch](https://arxiv.org/abs/2405.09559)|[KID-PPG](https://github.com/esl-epfl/KID-PPG)| -|[dynamic gnns for precise seizure detection and classification from eeg data](https://arxiv.org/abs/2405.09568)|[NeuroGNN](https://github.com/USC-InfoLab/NeuroGNN)| -|[language-oriented semantic latent representation for image transmission](https://arxiv.org/abs/2405.09976)|[img2img-sc](https://github.com/ispamm/img2img-sc)| -|[towards task-compatible compressible representations](https://arxiv.org/abs/2405.10244)|[research](https://github.com/adeandrade/research)| +|date|paper|code| +|---|---|---| +|2405.09559|[kid-ppg: knowledge informed deep learning for extracting heart rate from a smartwatch](https://arxiv.org/abs/2405.09559)|[KID-PPG](https://github.com/esl-epfl/KID-PPG)| +|2405.09568|[dynamic gnns for precise seizure detection and classification from eeg data](https://arxiv.org/abs/2405.09568)|[NeuroGNN](https://github.com/USC-InfoLab/NeuroGNN)| +|2405.09976|[language-oriented semantic latent representation for image transmission](https://arxiv.org/abs/2405.09976)|[img2img-sc](https://github.com/ispamm/img2img-sc)| +|2405.10244|[towards task-compatible compressible representations](https://arxiv.org/abs/2405.10244)|[research](https://github.com/adeandrade/research)| ## 2024-05-16 -|paper|code| -|---|---| -|[calibrating wireless ray tracing for digital twinning using local phase error estimates](https://arxiv.org/abs/2312.12625)|[phase-aware-rt-calibration](https://github.com/kclip/phase-aware-rt-calibration)| -|[unsupervised learning based end-to-end delayless generative fixed-filter active noise control](https://arxiv.org/abs/2402.09460)|[unsupervised-gfanc](https://github.com/luo-zhengding/unsupervised-gfanc)| -|[unsupervised learning for joint beamforming design in ris-aided isac systems](https://arxiv.org/abs/2403.17324)|[DL-Beamforming-RIS-ISAC](https://github.com/Yejacky456/DL-Beamforming-RIS-ISAC)| -|[joint instantaneous amplitude-frequency analysis of vibration signals for vibration-based condition monitoring of rolling bearings](https://arxiv.org/abs/2405.08919)|[Joint-Instantaneous-Amplitude-Frequency-Analysis-for-Vibration-Based-Condition-Monitoring](https://github.com/Western-OC2-Lab/Joint-Instantaneous-Amplitude-Frequency-Analysis-for-Vibration-Based-Condition-Monitoring)| +|date|paper|code| +|---|---|---| +|2405.08919|[joint instantaneous amplitude-frequency analysis of vibration signals for vibration-based condition monitoring of rolling bearings](https://arxiv.org/abs/2405.08919)|[Joint-Instantaneous-Amplitude-Frequency-Analysis-for-Vibration-Based-Condition-Monitoring](https://github.com/Western-OC2-Lab/Joint-Instantaneous-Amplitude-Frequency-Analysis-for-Vibration-Based-Condition-Monitoring)| ## 2024-05-15 -|paper|code| -|---|---| -|[multi-target tracking with transferable convolutional neural networks](https://arxiv.org/abs/2210.15539)|[mtt](https://github.com/damowerko/mtt)| -|[genet: a graph neural network-based anti-noise task-oriented semantic communication paradigm](https://arxiv.org/abs/2403.18296)|[genet](https://github.com/chunbaobao/genet)| -|[modeling of time-varying wireless communication channel with fading and shadowing](https://arxiv.org/abs/2405.08199)|[Modeling-of-Time-varying-Wireless-Communication-Channel-with-Fading-and-Shadowing](https://github.com/BrightBlueCheese/Modeling-of-Time-varying-Wireless-Communication-Channel-with-Fading-and-Shadowing)| +|date|paper|code| +|---|---|---| +|2405.08199|[modeling of time-varying wireless communication channel with fading and shadowing](https://arxiv.org/abs/2405.08199)|[Modeling-of-Time-varying-Wireless-Communication-Channel-with-Fading-and-Shadowing](https://github.com/BrightBlueCheese/Modeling-of-Time-varying-Wireless-Communication-Channel-with-Fading-and-Shadowing)| ## 2024-05-14 -|paper|code| -|---|---| -|[audioldm 2: learning holistic audio generation with self-supervised pretraining](https://arxiv.org/abs/2308.05734)|[AudioLDM2](https://github.com/haoheliu/AudioLDM2)| -|[learning multi-frequency partial correlation graphs](https://arxiv.org/abs/2311.15756)|[bspcg](https://github.com/officiallydac/bspcg)| -|[prospects for ai-enhanced ecg as a unified screening tool for cardiac and non-cardiac conditions -- an explorative study in emergency care](https://arxiv.org/abs/2312.11050)|[ecg-mimic](https://github.com/ai4healthuol/ecg-mimic)| -|[personalized heart disease detection via ecg digital twin generation](https://arxiv.org/abs/2404.11171)|[lavq-editor](https://github.com/huyjj/lavq-editor)| -|[neuronet: a novel hybrid self-supervised learning framework for sleep stage classification using single-channel eeg](https://arxiv.org/abs/2404.17585)|[NeuroNet](https://github.com/dlcjfgmlnasa/NeuroNet)| -|[timely status updates in slotted aloha networks with energy harvesting](https://arxiv.org/abs/2404.18990)|[aoi_slottedaloha_energyharvesting](https://github.com/khachoang1412/aoi_slottedaloha_energyharvesting)| -|[time-of-arrival estimation and phase unwrapping of head-related transfer functions with integer linear programming](https://arxiv.org/abs/2405.06804)|[hrtf-ilp](https://github.com/yoyololicon/hrtf-ilp)| -|[a supervised information enhanced multi-granularity contrastive learning framework for eeg based emotion recognition](https://arxiv.org/abs/2405.07260)|[si-cleer](https://github.com/muzixiang/si-cleer)| -|[transition role of entangled data in quantum machine learning](https://arxiv.org/abs/2306.03481)|[transition-role-of-entangled-data-in-qml](https://github.com/wangxinbiao08/transition-role-of-entangled-data-in-qml)| -|[texshape: information theoretic sentence embedding for language models](https://arxiv.org/abs/2402.05132)|[neuralinformationshaping](https://github.com/hesfahanizadeh/neuralinformationshaping)| -|[an efficient compression method for sign information of dct coefficients via sign retrieval](https://arxiv.org/abs/2405.07487)|[sr](https://github.com/ctsutake/sr)| -|[partial information decomposition as information bottleneck](https://arxiv.org/abs/2405.07665)|[pid-as-ib](https://github.com/artemyk/pid-as-ib)| -|[localized adaptive risk control](https://arxiv.org/abs/2405.07976)|[localized-adaptive-risk-control](https://github.com/kclip/localized-adaptive-risk-control)| +|date|paper|code| +|---|---|---| +|2405.06804|[time-of-arrival estimation and phase unwrapping of head-related transfer functions with integer linear programming](https://arxiv.org/abs/2405.06804)|[hrtf-ilp](https://github.com/yoyololicon/hrtf-ilp)| +|2405.07260|[a supervised information enhanced multi-granularity contrastive learning framework for eeg based emotion recognition](https://arxiv.org/abs/2405.07260)|[si-cleer](https://github.com/muzixiang/si-cleer)| +|2405.07487|[an efficient compression method for sign information of dct coefficients via sign retrieval](https://arxiv.org/abs/2405.07487)|[sr](https://github.com/ctsutake/sr)| +|2405.07665|[partial information decomposition as information bottleneck](https://arxiv.org/abs/2405.07665)|[pid-as-ib](https://github.com/artemyk/pid-as-ib)| +|2405.07976|[localized adaptive risk control](https://arxiv.org/abs/2405.07976)|[localized-adaptive-risk-control](https://github.com/kclip/localized-adaptive-risk-control)| ## 2024-05-13 -|paper|code| -|---|---| -|[compressing sign information in dct-based image coding via deep sign retrieval](https://arxiv.org/abs/2209.10712)|[dsr](https://github.com/ctsutake/dsr)| -|[asf-yolo: a novel yolo model with attentional scale sequence fusion for cell instance segmentation](https://arxiv.org/abs/2312.06458)|[asf-yolo](https://github.com/mkang315/asf-yolo)| -|[diffusion-aided joint source channel coding for high realism wireless image transmission](https://arxiv.org/abs/2404.17736)|[diffjscc](https://github.com/mingyuyng/diffjscc)| -|[optimal beamforming of ris-aided wireless communications: an alternating inner product maximization approach](https://arxiv.org/abs/2405.06442)|[RIS_Optimization](https://github.com/RujingXiong/RIS_Optimization)| +|date|paper|code| +|---|---|---| +|2405.06442|[optimal beamforming of ris-aided wireless communications: an alternating inner product maximization approach](https://arxiv.org/abs/2405.06442)|[RIS_Optimization](https://github.com/RujingXiong/RIS_Optimization)| ## 2024-05-10 -|paper|code| -|---|---| -|[ecg-based estimation of respiratory modulation of av nodal conduction during atrial fibrillation](https://arxiv.org/abs/2309.05458)|[ecg-based_estimation_of_respiratory_modulation_of_av_nodal_conduction_during_atrial_fibrillation](https://github.com/plappertf/ecg-based_estimation_of_respiratory_modulation_of_av_nodal_conduction_during_atrial_fibrillation)| +|date|paper|code| +|---|---|---| ## 2024-05-09 -|paper|code| -|---|---| -|[data augmentation for generating synthetic electrogastrogram time series](https://arxiv.org/abs/2303.02408)|[syegg](https://github.com/nadicasm/syegg)| -|[enhancing deep reinforcement learning: a tutorial on generative diffusion models in network optimization](https://arxiv.org/abs/2308.05384)|[gdmopt](https://github.com/hongyangdu/gdmopt)| -|[uncertainty-aware bayes' rule and its applications](https://arxiv.org/abs/2311.05532)|[bayes-rule](https://github.com/spratm-asleaf/bayes-rule)| -|[regime learning for differentiable particle filters](https://arxiv.org/abs/2405.04865)|[Regime_Switching](https://github.com/John-JoB/Regime_Switching)| -|[communication-efficient collaborative perception via information filling with codebook](https://arxiv.org/abs/2405.04966)|[codefilling](https://github.com/phyllish/codefilling)| +|date|paper|code| +|---|---|---| +|2405.04865|[regime learning for differentiable particle filters](https://arxiv.org/abs/2405.04865)|[Regime_Switching](https://github.com/John-JoB/Regime_Switching)| +|2405.04966|[communication-efficient collaborative perception via information filling with codebook](https://arxiv.org/abs/2405.04966)|[codefilling](https://github.com/phyllish/codefilling)| ## 2024-05-08 -|paper|code| -|---|---| -|[robofisense: attention-based robotic arm activity recognition with wifi sensing](https://arxiv.org/abs/2312.15345)|[robofisense](https://github.com/siamilab/robofisense)| -|[learning linear block error correction codes](https://arxiv.org/abs/2405.04050)|[e2e_dc_ecct](https://github.com/yonilc/e2e_dc_ecct)| +|date|paper|code| +|---|---|---| +|2405.04050|[learning linear block error correction codes](https://arxiv.org/abs/2405.04050)|[e2e_dc_ecct](https://github.com/yonilc/e2e_dc_ecct)| ## 2024-05-07 -|paper|code| -|---|---| -|[generalised envelope spectrum-based signal-to-noise objectives: formulation, optimisation and application for gear fault detection under time-varying speed conditions](https://arxiv.org/abs/2405.00727)|[snrocl](https://gitlab.com/vspa/snrocl)| -|[antenna failure resilience: deep learning-enabled robust doa estimation with single snapshot sparse arrays](https://arxiv.org/abs/2405.02788)|[deep_rsa_doa](https://github.com/ruxinzh/deep_rsa_doa)| -|[fully reversing the shoebox image source method: from impulse responses to room parameters](https://arxiv.org/abs/2405.03385)|[acoustic-sfw](https://github.com/sprunckt/acoustic-sfw)| -|[performance evaluation of pac decoding with deep neural networks](https://arxiv.org/abs/2405.02590)|[Performance-Evaluation-of-PAC-Decoding-with-Deep-Neural-Networks](https://github.com/daijingixn/Performance-Evaluation-of-PAC-Decoding-with-Deep-Neural-Networks)| -|[perfect codes over non-prime power alphabets: an approach based on diophantine equations](https://arxiv.org/abs/2405.03347)|[perfect-q-ary-codes](https://github.com/pjcazorla/perfect-q-ary-codes)| +|date|paper|code| +|---|---|---| +|2405.00727|[generalised envelope spectrum-based signal-to-noise objectives: formulation, optimisation and application for gear fault detection under time-varying speed conditions](https://arxiv.org/abs/2405.00727)|[snrocl](https://gitlab.com/vspa/snrocl)| +|2405.02788|[antenna failure resilience: deep learning-enabled robust doa estimation with single snapshot sparse arrays](https://arxiv.org/abs/2405.02788)|[deep_rsa_doa](https://github.com/ruxinzh/deep_rsa_doa)| +|2405.03385|[fully reversing the shoebox image source method: from impulse responses to room parameters](https://arxiv.org/abs/2405.03385)|[acoustic-sfw](https://github.com/sprunckt/acoustic-sfw)| +|2405.02590|[performance evaluation of pac decoding with deep neural networks](https://arxiv.org/abs/2405.02590)|[Performance-Evaluation-of-PAC-Decoding-with-Deep-Neural-Networks](https://github.com/daijingixn/Performance-Evaluation-of-PAC-Decoding-with-Deep-Neural-Networks)| +|2405.03347|[perfect codes over non-prime power alphabets: an approach based on diophantine equations](https://arxiv.org/abs/2405.03347)|[perfect-q-ary-codes](https://github.com/pjcazorla/perfect-q-ary-codes)| ## 2024-05-06 -|paper|code| -|---|---| -|[risk-aware continuous control with neural contextual bandits](https://arxiv.org/abs/2312.09961)|[risk_aware_contextual_bandit](https://github.com/jaayala/risk_aware_contextual_bandit)| -|[extended kalman filter -- koopman operator for tractable stochastic optimal control](https://arxiv.org/abs/2402.18554)|[linearizing-uncertainty-for-control](https://github.com/msramada/linearizing-uncertainty-for-control)| -|[identification of snps in genomes using gramep, an alignment-free method based on the principle of maximum entropy](https://arxiv.org/abs/2405.01715)|[gramep](https://github.com/omatheuspimenta/gramep)| +|date|paper|code| +|---|---|---| +|2405.01715|[identification of snps in genomes using gramep, an alignment-free method based on the principle of maximum entropy](https://arxiv.org/abs/2405.01715)|[gramep](https://github.com/omatheuspimenta/gramep)| ## 2024-05-03 -|paper|code| -|---|---| -|[denoiser-based projections for 2-d super-resolution multi-reference alignment](https://arxiv.org/abs/2204.04754)|[denoiser_projection](https://github.com/jonathanshani/denoiser_projection)| -|[eeg-deformer: a dense convolutional transformer for brain-computer interfaces](https://arxiv.org/abs/2405.00719)|[eeg-deformer](https://github.com/yi-ding-cs/eeg-deformer)| -|[joint signal detection and automatic modulation classification via deep learning](https://arxiv.org/abs/2405.00736)|[changshuoradiodata](https://github.com/singingkettle/changshuoradiodata)| -|[locality regularized reconstruction: structured sparsity and delaunay triangulations](https://arxiv.org/abs/2405.00837)|[LocalityRegularization](https://github.com/MarshMue/LocalityRegularization)| +|date|paper|code| +|---|---|---| +|2405.00719|[eeg-deformer: a dense convolutional transformer for brain-computer interfaces](https://arxiv.org/abs/2405.00719)|[eeg-deformer](https://github.com/yi-ding-cs/eeg-deformer)| +|2405.00736|[joint signal detection and automatic modulation classification via deep learning](https://arxiv.org/abs/2405.00736)|[changshuoradiodata](https://github.com/singingkettle/changshuoradiodata)| +|2405.00837|[locality regularized reconstruction: structured sparsity and delaunay triangulations](https://arxiv.org/abs/2405.00837)|[LocalityRegularization](https://github.com/MarshMue/LocalityRegularization)| ## 2024-05-02 -|paper|code| -|---|---| -|[titan: bringing the deep image prior to implicit representations](https://arxiv.org/abs/2211.00219)|[titan-implicit-prior](https://github.com/dlej/titan-implicit-prior)| -|[guaranteed dynamic scheduling of ultra-reliable low-latency traffic via conformal prediction](https://arxiv.org/abs/2302.07675)|[online_cp_urllc](https://github.com/kclip/online_cp_urllc)| -|[the information geometry of umap](https://arxiv.org/abs/2309.01237)|[info-geometry-umap](https://github.com/sashakolpakov/info-geometry-umap)| -|[an efficient difference-of-convex solver for privacy funnel](https://arxiv.org/abs/2403.04778)|[dcaPF-torch](https://github.com/hui811116/dcaPF-torch)| +|date|paper|code| +|---|---|---| ## 2024-05-01 -|paper|code| -|---|---| -|[multi-task learning for radar signal characterisation](https://arxiv.org/abs/2306.13105)|[radchar](https://github.com/abcxyzi/radchar)| -|[timely status updates in slotted aloha network with energy harvesting](https://arxiv.org/abs/2404.18990)|[aoi_slottedaloha_energyharvesting](https://github.com/khachoang1412/aoi_slottedaloha_energyharvesting)| -|[ultra inertial poser: scalable motion capture and tracking from sparse inertial sensors and ultra-wideband ranging](https://arxiv.org/abs/2404.19541)|[ultrainertialposer](https://github.com/eth-siplab/ultrainertialposer)| -|[type-based unsourced multiple access](https://arxiv.org/abs/2404.19552)|[TUMA](https://github.com/khachoang1412/TUMA)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/06.md b/archives/2024/06.md index 8c8d047d..fb0f943c 100644 --- a/archives/2024/06.md +++ b/archives/2024/06.md @@ -1,164 +1,109 @@ # June 2024 Archive ## 2024-06-28 -|paper|code| -|---|---| -|[a deep automotive radar detector using the radelft dataset](https://arxiv.org/abs/2406.04723)|[RaDelft-Dataset](https://github.com/RaDelft/RaDelft-Dataset)| -|[incremental measurement of structural entropy for dynamic graphs](https://arxiv.org/abs/2207.12653)|[incre-se](https://github.com/yangrunze1013/incre-se)| -|[partial information decomposition: redundancy as information bottleneck](https://arxiv.org/abs/2405.07665)|[pid-as-ib](https://github.com/artemyk/pid-as-ib)| -|[local to global: learning dynamics and effect of initialization for transformers](https://arxiv.org/abs/2406.03072)|[markov](https://github.com/bond1995/markov)| +|date|paper|code| +|---|---|---| +|2406.04723|[a deep automotive radar detector using the radelft dataset](https://arxiv.org/abs/2406.04723)|[RaDelft-Dataset](https://github.com/RaDelft/RaDelft-Dataset)| +|2406.03072|[local to global: learning dynamics and effect of initialization for transformers](https://arxiv.org/abs/2406.03072)|[markov](https://github.com/bond1995/markov)| ## 2024-06-27 -|paper|code| -|---|---| -|[federated learning compression designed for lightweight communications](https://arxiv.org/abs/2310.14693)|[fl_exps](https://github.com/lgrativol/fl_exps)| -|[whalenet: a novel deep learning architecture for marine mammals vocalizations on watkins marine mammal sound database](https://arxiv.org/abs/2402.17775)|[whalenet](https://github.com/alelicciardi99/whalenet)| -|[listening to the noise: blind denoising with gibbs diffusion](https://arxiv.org/abs/2402.19455)|[gibbs-diffusion](https://github.com/rubenohana/gibbs-diffusion)| -|[towards task-compatible compressible representations](https://arxiv.org/abs/2405.10244)|[research](https://github.com/adeandrade/research)| -|[flocora: federated learning compression with low-rank adaptation](https://arxiv.org/abs/2406.14082)|[flocora_eusipco24](https://github.com/lgrativol/flocora_eusipco24)| -|[benchmarking mortality risk prediction from electrocardiograms](https://arxiv.org/abs/2406.17002)|[ecg-survival-benchmark](https://github.com/cavalab/ecg-survival-benchmark)| -|[emt: a novel transformer for generalized cross-subject eeg emotion recognition](https://arxiv.org/abs/2406.18345)|[emt](https://github.com/yi-ding-cs/emt)| +|date|paper|code| +|---|---|---| +|2406.14082|[flocora: federated learning compression with low-rank adaptation](https://arxiv.org/abs/2406.14082)|[flocora_eusipco24](https://github.com/lgrativol/flocora_eusipco24)| +|2406.17002|[benchmarking mortality risk prediction from electrocardiograms](https://arxiv.org/abs/2406.17002)|[ecg-survival-benchmark](https://github.com/cavalab/ecg-survival-benchmark)| +|2406.18345|[emt: a novel transformer for generalized cross-subject eeg emotion recognition](https://arxiv.org/abs/2406.18345)|[emt](https://github.com/yi-ding-cs/emt)| ## 2024-06-26 -|paper|code| -|---|---| -|[mind's eye: image recognition by eeg via multimodal similarity-keeping contrastive learning](https://arxiv.org/abs/2406.16910)|[MUSE_EEG](https://github.com/ChiShengChen/MUSE_EEG)| -|[a multi-resolution mutual learning network for multi-label ecg classification](https://arxiv.org/abs/2406.16928)|[mrm](https://github.com/wxhdf/mrm)| -|[xi-net: transformer based seismic waveform reconstructor](https://arxiv.org/abs/2406.16932)|[waveformreconstructor](https://github.com/anshuman04/waveformreconstructor)| -|[constructing structured tensor priors for bayesian inverse problems](https://arxiv.org/abs/2406.17597)|[AbTensors](https://github.com/TUDelft-DeTAIL/AbTensors)| -|[the information geometry of umap](https://arxiv.org/abs/2309.01237)|[info-geometry-umap](https://github.com/sashakolpakov/info-geometry-umap)| +|date|paper|code| +|---|---|---| +|2406.16910|[mind's eye: image recognition by eeg via multimodal similarity-keeping contrastive learning](https://arxiv.org/abs/2406.16910)|[MUSE_EEG](https://github.com/ChiShengChen/MUSE_EEG)| +|2406.16928|[a multi-resolution mutual learning network for multi-label ecg classification](https://arxiv.org/abs/2406.16928)|[mrm](https://github.com/wxhdf/mrm)| +|2406.16932|[xi-net: transformer based seismic waveform reconstructor](https://arxiv.org/abs/2406.16932)|[waveformreconstructor](https://github.com/anshuman04/waveformreconstructor)| +|2406.17597|[constructing structured tensor priors for bayesian inverse problems](https://arxiv.org/abs/2406.17597)|[AbTensors](https://github.com/TUDelft-DeTAIL/AbTensors)| ## 2024-06-25 -|paper|code| -|---|---| -|[motion-robust free-running volumetric cardiovascular mri](https://arxiv.org/abs/2308.02088)|[motion-robust-CMR](https://github.com/OSU-MR/motion-robust-CMR)| -|[discrete approximations of gaussian smoothing and gaussian derivatives](https://arxiv.org/abs/2311.11317)|[pyscsp](https://github.com/tonylindeberg/pyscsp)| -|[markov chain monte carlo multi-scan data association for sets of trajectories](https://arxiv.org/abs/2312.03423)|[batch-tpmbm-using-mcmc-sampling](https://github.com/yuhsuansia/batch-tpmbm-using-mcmc-sampling)| -|[feature characterization for profile surface texture](https://arxiv.org/abs/2406.06381)|[feature-characterization-for-profile-surface-texture](https://github.com/mts-public/feature-characterization-for-profile-surface-texture)| -|[automatic ai model selection for wireless systems: online learning via digital twinning](https://arxiv.org/abs/2406.15819)|[DT-powered-AMS](https://github.com/qiushuo0913/DT-powered-AMS)| -|[learning and communications co-design for remote inference systems: feature length selection and transmission scheduling](https://arxiv.org/abs/2308.10094)|[impact-of-data-freshness-in-learning](https://github.com/kamran0153/impact-of-data-freshness-in-learning)| +|date|paper|code| +|---|---|---| +|2406.06381|[feature characterization for profile surface texture](https://arxiv.org/abs/2406.06381)|[feature-characterization-for-profile-surface-texture](https://github.com/mts-public/feature-characterization-for-profile-surface-texture)| +|2406.15819|[automatic ai model selection for wireless systems: online learning via digital twinning](https://arxiv.org/abs/2406.15819)|[DT-powered-AMS](https://github.com/qiushuo0913/DT-powered-AMS)| ## 2024-06-24 -|paper|code| -|---|---| -|[a comparative study of deep learning and iterative algorithms for joint channel estimation and signal detection in ofdm systems](https://arxiv.org/abs/2303.03678)|[mimo_jcesd](https://github.com/j991222/mimo_jcesd)| -|[a geometry-based stochastic wireless channel model using channel images](https://arxiv.org/abs/2312.06637)|[geostochasticchanmodel](https://github.com/sk8053/geostochasticchanmodel)| +|date|paper|code| +|---|---|---| ## 2024-06-21 -|paper|code| -|---|---| -|[self-supervised learning for human activity recognition using 700,000 person-days of wearable data](https://arxiv.org/abs/2206.02909)|[ssl-wearables](https://github.com/OxWearables/ssl-wearables)| -|[eeg-dbnet: a dual-branch network for temporal-spectral decoding in motor-imagery brain-computer interfaces](https://arxiv.org/abs/2405.16090)|[eeg-dbnet](https://github.com/xicheng105/eeg-dbnet)| -|[on the inductive biases of demographic parity-based fair learning algorithms](https://arxiv.org/abs/2402.18129)|[fairness-ib](https://github.com/lh218/fairness-ib)| +|date|paper|code| +|---|---|---| ## 2024-06-19 -|paper|code| -|---|---| -|[eeg2rep: enhancing self-supervised eeg representation through informative masked inputs](https://arxiv.org/abs/2402.17772)|[eeg2rep](https://github.com/navidfoumani/eeg2rep)| -|[interpretable modulated differentiable stft and physics-informed balanced spectrum metric for freight train wheelset bearing cross-machine transfer fault diagnosis under speed fluctuations](https://arxiv.org/abs/2406.11917)|[PyDSN](https://github.com/liguge/PyDSN)| -|[a comparative analysis of the ensemble methods for drug design](https://arxiv.org/abs/2012.07640)|[Comparative-Analysis](https://github.com/rifqat/Comparative-Analysis)| +|date|paper|code| +|---|---|---| +|2406.11917|[interpretable modulated differentiable stft and physics-informed balanced spectrum metric for freight train wheelset bearing cross-machine transfer fault diagnosis under speed fluctuations](https://arxiv.org/abs/2406.11917)|[PyDSN](https://github.com/liguge/PyDSN)| ## 2024-06-18 -|paper|code| -|---|---| -|[afs-bm: enhancing model performance through adaptive feature selection with binary masking](https://arxiv.org/abs/2401.11250)|[afs_bm-algorithm](https://github.com/yigitturali/afs_bm-algorithm)| -|[a decoupled approach for composite sparse-plus-smooth penalized optimization](https://arxiv.org/abs/2403.05204)|[compositesps](https://github.com/adriaj/compositesps)| -|[sim2real in reconstructive spectroscopy: deep learning with augmented device-informed data simulation](https://arxiv.org/abs/2403.12354)|[rec_spectrometer](https://github.com/j1goblue/rec_spectrometer)| -|[full reference point cloud quality assessment using support vector regression](https://arxiv.org/abs/2406.10520)|[frsvr-pcqa](https://github.com/stac-usc/frsvr-pcqa)| -|[deep-reinforcement-learning-based aoi-aware resource allocation for ris-aided iov networks](https://arxiv.org/abs/2406.11245)|[ris-rb-aoi-v2x-drl](https://github.com/qiongwu86/ris-rb-aoi-v2x-drl)| -|[reconfigurable intelligent surface assisted vec based on multi-agent reinforcement learning](https://arxiv.org/abs/2406.11318)|[ris-vec-marl](https://github.com/qiongwu86/ris-vec-marl)| -|[an efficient frequency diversity scheme for ultra-reliable communications in two-path fading channels](https://arxiv.org/abs/2206.13459)|[two-ray-ultra-reliability](https://github.com/klb2/two-ray-ultra-reliability)| -|[generalization error of graph neural networks in the mean-field regime](https://arxiv.org/abs/2402.07025)|[gnn_mf_ge](https://github.com/sherylhyx/gnn_mf_ge)| +|date|paper|code| +|---|---|---| +|2406.10520|[full reference point cloud quality assessment using support vector regression](https://arxiv.org/abs/2406.10520)|[frsvr-pcqa](https://github.com/stac-usc/frsvr-pcqa)| +|2406.11245|[deep-reinforcement-learning-based aoi-aware resource allocation for ris-aided iov networks](https://arxiv.org/abs/2406.11245)|[ris-rb-aoi-v2x-drl](https://github.com/qiongwu86/ris-rb-aoi-v2x-drl)| +|2406.11318|[reconfigurable intelligent surface assisted vec based on multi-agent reinforcement learning](https://arxiv.org/abs/2406.11318)|[ris-vec-marl](https://github.com/qiongwu86/ris-vec-marl)| ## 2024-06-17 -|paper|code| -|---|---| -|[semantic: semantic interference cancellation towards 6g wireless communications](https://arxiv.org/abs/2310.12768)|[SemantIC](https://github.com/linwest/SemantIC)| -|[harmonics of learning: universal fourier features emerge in invariant networks](https://arxiv.org/abs/2312.08550)|[spectral-universality](https://github.com/sophiaas/spectral-universality)| -|[algebra of nonlocal boxes and the collapse of communication complexity](https://arxiv.org/abs/2312.00725)|[algebra-of-boxes-code](https://github.com/pierre-botteron/algebra-of-boxes-code)| +|date|paper|code| +|---|---|---| ## 2024-06-14 -|paper|code| -|---|---| -|[toward fully-end-to-end listened speech decoding from eeg signals](https://arxiv.org/abs/2406.08644)|[fesde](https://github.com/lee-jhwn/fesde)| -|[multimodal learning without labeled multimodal data: guarantees and applications](https://arxiv.org/abs/2306.04539)|[pid](https://github.com/pliang279/pid)| +|date|paper|code| +|---|---|---| +|2406.08644|[toward fully-end-to-end listened speech decoding from eeg signals](https://arxiv.org/abs/2406.08644)|[fesde](https://github.com/lee-jhwn/fesde)| ## 2024-06-13 -|paper|code| -|---|---| -|[melep: a novel predictive measure of transferability in multi-label ecg diagnosis](https://arxiv.org/abs/2311.04224)|[melep-ecg](https://github.com/cuongvng/melep-ecg)| -|[provably robust score-based diffusion posterior sampling for plug-and-play image reconstruction](https://arxiv.org/abs/2403.17042)|[diffusion-plug-and-play](https://github.com/x1xu/diffusion-plug-and-play)| -|[regime learning for differentiable particle filters](https://arxiv.org/abs/2405.04865)|[Regime_Switching](https://github.com/John-JoB/Regime_Switching)| -|[approximation properties relative to continuous scale space for hybrid discretizations of gaussian derivative operators](https://arxiv.org/abs/2405.05095)|[pyscsp](https://github.com/tonylindeberg/pyscsp)| -|[semantic-aware resource allocation based on deep reinforcement learning for 5g-v2x hetnets](https://arxiv.org/abs/2406.07996)|[semantic-aware-resource-allocation-based-on-deep-reinforcement-learning-for-5g-v2x-hetnets](https://github.com/qiongwu86/semantic-aware-resource-allocation-based-on-deep-reinforcement-learning-for-5g-v2x-hetnets)| -|[bcamirs at semeval-2024 task 4: beyond words: a multimodal and multilingual exploration of persuasion in memes](https://arxiv.org/abs/2404.03022)|[beyond-words-a-multimodal-exploration-of-persuasion-in-memes](https://github.com/amirabaskohi/beyond-words-a-multimodal-exploration-of-persuasion-in-memes)| +|date|paper|code| +|---|---|---| +|2406.07996|[semantic-aware resource allocation based on deep reinforcement learning for 5g-v2x hetnets](https://arxiv.org/abs/2406.07996)|[semantic-aware-resource-allocation-based-on-deep-reinforcement-learning-for-5g-v2x-hetnets](https://github.com/qiongwu86/semantic-aware-resource-allocation-based-on-deep-reinforcement-learning-for-5g-v2x-hetnets)| ## 2024-06-12 -|paper|code| -|---|---| -|[disco might not be funky: random intelligent reflective surface configurations that attack](https://arxiv.org/abs/2310.00687)|[disco-intelligent-reflecting-surfaces-active-channel-aging-for-fully-passive-jamming-attacks](https://github.com/huanhuan1799/disco-intelligent-reflecting-surfaces-active-channel-aging-for-fully-passive-jamming-attacks)| -|[room transfer function reconstruction using complex-valued neural networks and irregularly distributed microphones](https://arxiv.org/abs/2402.04866)|[complex-sound-field](https://github.com/ronfrancesca/complex-sound-field)| -|[flexloc: conditional neural networks for zero-shot sensor perspective invariance in object localization with distributed multimodal sensors](https://arxiv.org/abs/2406.06796)|[flexloc](https://github.com/nesl/flexloc)| -|[accelerating ill-conditioned hankel matrix recovery via structured newton-like descent](https://arxiv.org/abs/2406.07409)|[HSNLD](https://github.com/caesarcai/HSNLD)| -|[analog information decoding of bosonic quantum ldpc codes](https://arxiv.org/abs/2311.01328)|[mqt-qecc](https://github.com/cda-tum/mqt-qecc)| -|[image and video tokenization with binary spherical quantization](https://arxiv.org/abs/2406.07548)|[bsq-vit](https://github.com/zhaoyue-zephyrus/bsq-vit)| +|date|paper|code| +|---|---|---| +|2406.06796|[flexloc: conditional neural networks for zero-shot sensor perspective invariance in object localization with distributed multimodal sensors](https://arxiv.org/abs/2406.06796)|[flexloc](https://github.com/nesl/flexloc)| +|2406.07409|[accelerating ill-conditioned hankel matrix recovery via structured newton-like descent](https://arxiv.org/abs/2406.07409)|[HSNLD](https://github.com/caesarcai/HSNLD)| +|2406.07548|[image and video tokenization with binary spherical quantization](https://arxiv.org/abs/2406.07548)|[bsq-vit](https://github.com/zhaoyue-zephyrus/bsq-vit)| ## 2024-06-11 -|paper|code| -|---|---| -|[a unified multi-task semantic communication system for multimodal data](https://arxiv.org/abs/2209.07689)|[t-udeepsc](https://github.com/zhang-guangyi/t-udeepsc)| -|[dh-ptam: a deep hybrid stereo events-frames parallel tracking and mapping system](https://arxiv.org/abs/2306.01891)|[dh-ptam](https://github.com/abanobsoliman/dh-ptam)| -|[distributionally robust receive beamforming](https://arxiv.org/abs/2401.12345)|[beamforming](https://github.com/spratm-asleaf/beamforming)| -|[solving inverse problems with model mismatch using untrained neural networks within model-based architectures](https://arxiv.org/abs/2403.04847)|[a-adaptive-model-based-methods](https://github.com/invprobs/a-adaptive-model-based-methods)| -|[singing voice graph modeling for singfake detection](https://arxiv.org/abs/2406.03111)|[singgraph](https://github.com/xjchengit/singgraph)| -|[compressible dynamics in deep overparameterized low-rank learning & adaptation](https://arxiv.org/abs/2406.04112)|[deep-lora-transformers](https://github.com/cjyaras/deep-lora-transformers)| -|[winner-takes-all learners are geometry-aware conditional density estimators](https://arxiv.org/abs/2406.04706)|[VoronoiWTA](https://github.com/Victorletzelter/VoronoiWTA)| -|[soundscape captioning using sound affective quality network and large language model](https://arxiv.org/abs/2406.05914)|[soundscaper](https://github.com/yuanbo2020/soundscaper)| -|[lessons from generalization error analysis of federated learning: you may communicate less often!](https://arxiv.org/abs/2306.05862)|[generalization_fl_icml2024](https://github.com/romainchor/generalization_fl_icml2024)| -|[localized adaptive risk control](https://arxiv.org/abs/2405.07976)|[localized-adaptive-risk-control](https://github.com/kclip/localized-adaptive-risk-control)| -|[fadam: adam is a natural gradient optimizer using diagonal empirical fisher information](https://arxiv.org/abs/2405.12807)|[fadam_pytorch](https://github.com/lessw2020/fadam_pytorch)| -|[physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics](https://arxiv.org/abs/2406.01539)|[PINN_high_dimensional_PDE](https://github.com/WeiqiWangMath/PINN_high_dimensional_PDE)| +|date|paper|code| +|---|---|---| +|2406.03111|[singing voice graph modeling for singfake detection](https://arxiv.org/abs/2406.03111)|[singgraph](https://github.com/xjchengit/singgraph)| +|2406.04112|[compressible dynamics in deep overparameterized low-rank learning & adaptation](https://arxiv.org/abs/2406.04112)|[deep-lora-transformers](https://github.com/cjyaras/deep-lora-transformers)| +|2406.04706|[winner-takes-all learners are geometry-aware conditional density estimators](https://arxiv.org/abs/2406.04706)|[VoronoiWTA](https://github.com/Victorletzelter/VoronoiWTA)| +|2406.05914|[soundscape captioning using sound affective quality network and large language model](https://arxiv.org/abs/2406.05914)|[soundscaper](https://github.com/yuanbo2020/soundscaper)| +|2406.01539|[physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics](https://arxiv.org/abs/2406.01539)|[PINN_high_dimensional_PDE](https://github.com/WeiqiWangMath/PINN_high_dimensional_PDE)| ## 2024-06-10 -|paper|code| -|---|---| -|[active sensing for reciprocal mimo channels](https://arxiv.org/abs/2403.00134)|[active-sensing-for-reciprocal-mimo-channels](https://github.com/taojiang-github/active-sensing-for-reciprocal-mimo-channels)| -|[learning optimal linear precoding for cell-free massive mimo with gnn](https://arxiv.org/abs/2406.04456)|[olp-gnn](https://github.com/Nokia-Bell-Labs/olp-gnn)| -|[digital twins of the em environment: benchmark for ray launching models](https://arxiv.org/abs/2406.05042)|[ray-launching-benchmark](https://github.com/Michele-Zhu/ray-launching-benchmark)| -|[s$\omega$i: score-based o-information estimation](https://arxiv.org/abs/2402.05667)|[soi](https://github.com/mustaphabounoua/soi)| -|[revisiting attention weights as interpretations of message-passing neural networks](https://arxiv.org/abs/2406.04612)|[gatt](https://github.com/jordan7186/gatt)| +|date|paper|code| +|---|---|---| +|2406.04456|[learning optimal linear precoding for cell-free massive mimo with gnn](https://arxiv.org/abs/2406.04456)|[olp-gnn](https://github.com/Nokia-Bell-Labs/olp-gnn)| +|2406.05042|[digital twins of the em environment: benchmark for ray launching models](https://arxiv.org/abs/2406.05042)|[ray-launching-benchmark](https://github.com/Michele-Zhu/ray-launching-benchmark)| +|2406.04612|[revisiting attention weights as interpretations of message-passing neural networks](https://arxiv.org/abs/2406.04612)|[gatt](https://github.com/jordan7186/gatt)| ## 2024-06-07 -|paper|code| -|---|---| -|[clarifying the effect of mean subtraction on dynamic mode decomposition](https://arxiv.org/abs/2105.03607)|[msub_mdselect_dmd](https://github.com/gowtham-ss-ragavan/msub_mdselect_dmd)| -|[selective noise suppression methods using random svpwm to shape the noise spectrum of pmsms](https://arxiv.org/abs/2302.08053)|[SNS-in-random-SVPWM](https://github.com/IoaJianWen/SNS-in-random-SVPWM)| -|[privacy preserving semi-decentralized mean estimation over intermittently-connected networks](https://arxiv.org/abs/2406.03766)|[private-collaborative-relaying](https://github.com/rajarshisaha95/private-collaborative-relaying)| -|[informed graph learning by domain knowledge injection and smooth graph signal representation](https://arxiv.org/abs/2406.03898)|[igl](https://github.com/keiv4n/igl)| -|[untrained neural nets for snapshot compressive imaging: theory and algorithms](https://arxiv.org/abs/2406.03694)|[SCI-BDVP](https://github.com/Computational-Imaging-RU/SCI-BDVP)| +|date|paper|code| +|---|---|---| +|2406.03766|[privacy preserving semi-decentralized mean estimation over intermittently-connected networks](https://arxiv.org/abs/2406.03766)|[private-collaborative-relaying](https://github.com/rajarshisaha95/private-collaborative-relaying)| +|2406.03898|[informed graph learning by domain knowledge injection and smooth graph signal representation](https://arxiv.org/abs/2406.03898)|[igl](https://github.com/keiv4n/igl)| +|2406.03694|[untrained neural nets for snapshot compressive imaging: theory and algorithms](https://arxiv.org/abs/2406.03694)|[SCI-BDVP](https://github.com/Computational-Imaging-RU/SCI-BDVP)| ## 2024-06-06 -|paper|code| -|---|---| -|[interpreting deepcode, a learned feedback code](https://arxiv.org/abs/2404.17519)|[deepcode-interpretability](https://github.com/zyy-cc/deepcode-interpretability)| -|[random matrix theory improved fr\'echet mean of symmetric positive definite matrices](https://arxiv.org/abs/2405.06558)|[icml-rmt-2024](https://github.com/ammarmian/icml-rmt-2024)| -|[deeppolar: inventing nonlinear large-kernel polar codes via deep learning](https://arxiv.org/abs/2402.08864)|[deeppolar](https://github.com/hebbarashwin/deeppolar)| +|date|paper|code| +|---|---|---| ## 2024-06-05 -|paper|code| -|---|---| -|[robust waveform design for integrated sensing and communication](https://arxiv.org/abs/2311.00071)|[robust-waveform](https://github.com/spratm-asleaf/robust-waveform)| -|[kernel vs. kernel: exploring how the data structure affects neural collapse](https://arxiv.org/abs/2406.02105)|[shallow_nc1](https://github.com/kvignesh1420/shallow_nc1)| +|date|paper|code| +|---|---|---| +|2406.02105|[kernel vs. kernel: exploring how the data structure affects neural collapse](https://arxiv.org/abs/2406.02105)|[shallow_nc1](https://github.com/kvignesh1420/shallow_nc1)| ## 2024-06-04 -|paper|code| -|---|---| -|[deep optimal transport for domain adaptation on spd manifolds](https://arxiv.org/abs/2201.05745)|[deep-optimal-transport-for-domain-adaptation-on-spd-manifolds](https://github.com/geometricbci/deep-optimal-transport-for-domain-adaptation-on-spd-manifolds)| -|[hypergraph-mlp: learning on hypergraphs without message passing](https://arxiv.org/abs/2312.09778)|[hypergraph-mlp](https://github.com/tbh-98/hypergraph-mlp)| -|[regime learning for differentiable particle filters](https://arxiv.org/abs/2405.04865)|[Regime_Switching](https://github.com/John-JoB/Regime_Switching)| -|[an unsupervised approach for periodic source detection in time series](https://arxiv.org/abs/2406.00566)|[unsupervised_periodicity_detection](https://github.com/eth-siplab/unsupervised_periodicity_detection)| -|[a gaussian process-based streaming algorithm for prediction of time series with regimes and outliers](https://arxiv.org/abs/2406.00570)|[Lintel](https://github.com/DanWaxman/Lintel)| -|[the information geometry of umap](https://arxiv.org/abs/2309.01237)|[info-geometry-umap](https://github.com/sashakolpakov/info-geometry-umap)| -|[fadam: adam is a natural gradient optimizer using diagonal empirical fisher information](https://arxiv.org/abs/2405.12807)|[fadam_pytorch](https://github.com/lessw2020/fadam_pytorch)| -|[physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics](https://arxiv.org/abs/2406.01539)|[PINN_high_dimensional_PDE](https://github.com/WeiqiWangMath/PINN_high_dimensional_PDE)| +|date|paper|code| +|---|---|---| +|2406.00566|[an unsupervised approach for periodic source detection in time series](https://arxiv.org/abs/2406.00566)|[unsupervised_periodicity_detection](https://github.com/eth-siplab/unsupervised_periodicity_detection)| +|2406.00570|[a gaussian process-based streaming algorithm for prediction of time series with regimes and outliers](https://arxiv.org/abs/2406.00570)|[Lintel](https://github.com/DanWaxman/Lintel)| +|2406.01539|[physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics](https://arxiv.org/abs/2406.01539)|[PINN_high_dimensional_PDE](https://github.com/WeiqiWangMath/PINN_high_dimensional_PDE)| diff --git a/archives/2024/07.md b/archives/2024/07.md index 857e24ee..4b034c20 100644 --- a/archives/2024/07.md +++ b/archives/2024/07.md @@ -1,176 +1,123 @@ # July 2024 Archive ## 2024-07-31 -|paper|code| -|---|---| -|[single-shot quantum signal processing interferometry](https://arxiv.org/abs/2311.13703)|[qsp-interferometry](https://github.com/yuanliu1/qsp-interferometry)| -|[robust beamforming for ris-aided communications: gradient-based manifold meta learning](https://arxiv.org/abs/2402.10626)|[GMML](https://github.com/fenghaozhu/GMML)| -|[edge learning based collaborative automatic modulation classification for hierarchical cognitive radio networks](https://arxiv.org/abs/2407.20772)|[CAMC](https://github.com/AI4CogComm/CAMC)| +|date|paper|code| +|---|---|---| +|2407.20772|[edge learning based collaborative automatic modulation classification for hierarchical cognitive radio networks](https://arxiv.org/abs/2407.20772)|[CAMC](https://github.com/AI4CogComm/CAMC)| ## 2024-07-30 -|paper|code| -|---|---| -|[a new framework for nonlinear kalman filters](https://arxiv.org/abs/2407.05717)|[a-new-framework-for-nonlinear-kalman-filters](https://github.com/shida-jiang/a-new-framework-for-nonlinear-kalman-filters)| -|[selection for short-term empowerment accelerates the evolution of homeostatic neural cellular automata](https://arxiv.org/abs/2305.15220)|[empowered-nca-ii](https://github.com/caitlingrasso/empowered-nca-ii)| +|date|paper|code| +|---|---|---| +|2407.05717|[a new framework for nonlinear kalman filters](https://arxiv.org/abs/2407.05717)|[a-new-framework-for-nonlinear-kalman-filters](https://github.com/shida-jiang/a-new-framework-for-nonlinear-kalman-filters)| ## 2024-07-29 -|paper|code| -|---|---| -|[a physical-layer orchestration framework for open system models of autonomous riss](https://arxiv.org/abs/2304.10858)|[self-configuring-orchestration](https://github.com/victorcroisfelt/self-configuring-orchestration)| -|[mds-ed: multimodal decision support in the emergency department -- a benchmark dataset for diagnoses and deterioration prediction in emergency medicine](https://arxiv.org/abs/2407.17856)|[mds-ed](https://github.com/ai4healthuol/mds-ed)| -|[a scalable quantum non-local neural network for image classification](https://arxiv.org/abs/2407.18906)|[QNL-Net](https://github.com/sparshgup/QNL-Net)| +|date|paper|code| +|---|---|---| +|2407.17856|[mds-ed: multimodal decision support in the emergency department -- a benchmark dataset for diagnoses and deterioration prediction in emergency medicine](https://arxiv.org/abs/2407.17856)|[mds-ed](https://github.com/ai4healthuol/mds-ed)| +|2407.18906|[a scalable quantum non-local neural network for image classification](https://arxiv.org/abs/2407.18906)|[QNL-Net](https://github.com/sparshgup/QNL-Net)| ## 2024-07-26 -|paper|code| -|---|---| -|[physics-enhanced graph neural networks for soft sensing in industrial internet of things](https://arxiv.org/abs/2404.08061)|[PEGNN_SS](https://github.com/EPFL-IMOS/PEGNN_SS)| -|[detection of manatee vocalisations using the audio spectrogram transformer](https://arxiv.org/abs/2407.18083)|[manatees](https://github.com/tdewolff/manatees)| -|[scaling training data with lossy image compression](https://arxiv.org/abs/2407.17954)|[lossycompressionscalingkdd2024](https://github.com/granica-ai/lossycompressionscalingkdd2024)| +|date|paper|code| +|---|---|---| +|2407.18083|[detection of manatee vocalisations using the audio spectrogram transformer](https://arxiv.org/abs/2407.18083)|[manatees](https://github.com/tdewolff/manatees)| +|2407.17954|[scaling training data with lossy image compression](https://arxiv.org/abs/2407.17954)|[lossycompressionscalingkdd2024](https://github.com/granica-ai/lossycompressionscalingkdd2024)| ## 2024-07-25 -|paper|code| -|---|---| -|[lab-scale vibration analysis dataset and baseline methods for machinery fault diagnosis with machine learning](https://arxiv.org/abs/2212.14732)|[vbl-va001](https://github.com/bagustris/vbl-va001)| -|[toward real-time digital twins of em environments: computational benchmark of ray launching software](https://arxiv.org/abs/2406.05042)|[ray-launching-benchmark](https://github.com/Michele-Zhu/ray-launching-benchmark)| -|[probing the information theoretical roots of spatial dependence measures](https://arxiv.org/abs/2405.18459)|[spatial-self-information](https://github.com/octopolugal/spatial-self-information)| +|date|paper|code| +|---|---|---| ## 2024-07-24 -|paper|code| -|---|---| -|[using explainable ai for eeg-based reduced montage neonatal seizure detection](https://arxiv.org/abs/2406.16908)|[braineocare](https://github.com/dinuka-1999/braineocare)| -|[channel shaping using beyond diagonal reconfigurable intelligent surface: analysis, optimization, and enhanced flexibility](https://arxiv.org/abs/2407.15196)|[channel-shaping-using-beyond-diagonal-reconfigurable-intelligent-surface](https://github.com/snowztail/channel-shaping-using-beyond-diagonal-reconfigurable-intelligent-surface)| -|[dc is all you need: describing relu from a signal processing standpoint](https://arxiv.org/abs/2407.16556)|[relu_dc_is_all_you_need](https://github.com/esl-epfl/relu_dc_is_all_you_need)| +|date|paper|code| +|---|---|---| +|2407.15196|[channel shaping using beyond diagonal reconfigurable intelligent surface: analysis, optimization, and enhanced flexibility](https://arxiv.org/abs/2407.15196)|[channel-shaping-using-beyond-diagonal-reconfigurable-intelligent-surface](https://github.com/snowztail/channel-shaping-using-beyond-diagonal-reconfigurable-intelligent-surface)| +|2407.16556|[dc is all you need: describing relu from a signal processing standpoint](https://arxiv.org/abs/2407.16556)|[relu_dc_is_all_you_need](https://github.com/esl-epfl/relu_dc_is_all_you_need)| ## 2024-07-23 -|paper|code| -|---|---| -|[learned kernels for sparse, interpretable, and efficient medical time series processing](https://arxiv.org/abs/2307.05385)|[smolk](https://github.com/sullychen/smolk)| -|[ensemble kalman filtering meets gaussian process ssm for non-mean-field and online inference](https://arxiv.org/abs/2312.05910)|[gpssmproj](https://github.com/zhidilin/gpssmproj)| -|[dreamer: dual-ris-aided imager in complementary modes](https://arxiv.org/abs/2407.14820)|[dreamer](https://github.com/fuhaiwang/dreamer)| -|[can all variations within the unified mask-based beamformer framework achieve identical peak extraction performance?](https://arxiv.org/abs/2407.15310)|[unified_framework_for_mask-based_bf](https://github.com/hreshare/unified_framework_for_mask-based_bf)| -|[the rlign algorithm for enhanced electrocardiogram analysis through r-peak alignment for explainable classification and clustering](https://arxiv.org/abs/2407.15555)|[rlign](https://github.com/imi-ms/rlign)| -|[the information geometry of umap](https://arxiv.org/abs/2309.01237)|[info-geometry-umap](https://github.com/sashakolpakov/info-geometry-umap)| -|[multi-sources information fusion learning for multi-points nlos localization](https://arxiv.org/abs/2401.12538)|[AMDNloc](https://github.com/Horizontal666/AMDNloc)| -|[adaptive foundation models for online decisions: hyperagent with fast incremental uncertainty estimation](https://arxiv.org/abs/2407.13195)|[GPT-HyperAgent](https://github.com/szrlee/GPT-HyperAgent)| +|date|paper|code| +|---|---|---| +|2407.14820|[dreamer: dual-ris-aided imager in complementary modes](https://arxiv.org/abs/2407.14820)|[dreamer](https://github.com/fuhaiwang/dreamer)| +|2407.15310|[can all variations within the unified mask-based beamformer framework achieve identical peak extraction performance?](https://arxiv.org/abs/2407.15310)|[unified_framework_for_mask-based_bf](https://github.com/hreshare/unified_framework_for_mask-based_bf)| +|2407.15555|[the rlign algorithm for enhanced electrocardiogram analysis through r-peak alignment for explainable classification and clustering](https://arxiv.org/abs/2407.15555)|[rlign](https://github.com/imi-ms/rlign)| +|2407.13195|[adaptive foundation models for online decisions: hyperagent with fast incremental uncertainty estimation](https://arxiv.org/abs/2407.13195)|[GPT-HyperAgent](https://github.com/szrlee/GPT-HyperAgent)| ## 2024-07-22 -|paper|code| -|---|---| -|[algorithms for non-negative matrix factorization on noisy data with negative values](https://arxiv.org/abs/2311.04855)|[nearly_nmf](https://github.com/dylanagreen/nearly_nmf)| -|[rigorous dynamical mean field theory for stochastic gradient descent methods](https://arxiv.org/abs/2210.06591)|[rigorous-dynamical-mean-field-theory](https://github.com/spoc-group/rigorous-dynamical-mean-field-theory)| +|date|paper|code| +|---|---|---| ## 2024-07-19 -|paper|code| -|---|---| -|[multi-scale transformer-based network for emotion recognition from multi physiological signals](https://arxiv.org/abs/2305.00769)|[EPiC-2023-ACII](https://github.com/vsl-team/EPiC-2023-ACII)| -|[thraws: a novel dataset for thermal hotspots detection in raw sentinel-2 data](https://arxiv.org/abs/2305.11891)|[pyraws](https://github.com/esa-philab/pyraws)| -|[advanced mathematical modelling for energy-efficient data transmission and fusion in wireless sensor networks](https://arxiv.org/abs/2407.12806)|[bpnn_wsn](https://github.com/hikomal/bpnn_wsn)| -|[reconfigurable intelligent surface aided vehicular edge computing: joint phase-shift optimization and multi-user power allocation](https://arxiv.org/abs/2407.13123)|[DDPG-RIS-MADDPG-POWER](https://github.com/qiongwu86/DDPG-RIS-MADDPG-POWER)| -|[an empirical investigation into the time and frequency response characteristics of hopf resonators](https://arxiv.org/abs/2407.13629)|[DetectorBank](https://github.com/keziah55/DetectorBank)| -|[the language of infographics: toward understanding conceptual metaphor use in scientific storytelling](https://arxiv.org/abs/2407.13416)|[metaphortool](https://github.com/lauragarrison87/metaphortool)| -|[non-asymptotic uncertainty quantification in high-dimensional learning](https://arxiv.org/abs/2407.13666)|[UQ_high_dim_learning](https://github.com/frederikhoppe/UQ_high_dim_learning)| +|date|paper|code| +|---|---|---| +|2407.12806|[advanced mathematical modelling for energy-efficient data transmission and fusion in wireless sensor networks](https://arxiv.org/abs/2407.12806)|[bpnn_wsn](https://github.com/hikomal/bpnn_wsn)| +|2407.13123|[reconfigurable intelligent surface aided vehicular edge computing: joint phase-shift optimization and multi-user power allocation](https://arxiv.org/abs/2407.13123)|[DDPG-RIS-MADDPG-POWER](https://github.com/qiongwu86/DDPG-RIS-MADDPG-POWER)| +|2407.13629|[an empirical investigation into the time and frequency response characteristics of hopf resonators](https://arxiv.org/abs/2407.13629)|[DetectorBank](https://github.com/keziah55/DetectorBank)| +|2407.13416|[the language of infographics: toward understanding conceptual metaphor use in scientific storytelling](https://arxiv.org/abs/2407.13416)|[metaphortool](https://github.com/lauragarrison87/metaphortool)| +|2407.13666|[non-asymptotic uncertainty quantification in high-dimensional learning](https://arxiv.org/abs/2407.13666)|[UQ_high_dim_learning](https://github.com/frederikhoppe/UQ_high_dim_learning)| ## 2024-07-18 -|paper|code| -|---|---| -|[luvira dataset validation and discussion: comparing vision, radio, and audio sensors for indoor localization](https://arxiv.org/abs/2309.02961)|[luvira_dataset](https://github.com/ilaydayaman/luvira_dataset)| -|[diffusion-aided joint source channel coding for high realism wireless image transmission](https://arxiv.org/abs/2404.17736)|[diffjscc](https://github.com/mingyuyng/diffjscc)| -|[mmvr: millimeter-wave multi-view radar dataset and benchmark for indoor perception](https://arxiv.org/abs/2406.10708)|[12611978](https://zenodo.org/record/12611978)| +|date|paper|code| +|---|---|---| ## 2024-07-17 -|paper|code| -|---|---| -|[hierarchical state space models for continuous sequence-to-sequence modeling](https://arxiv.org/abs/2402.10211)|[hiss](https://github.com/raunaqbhirangi/hiss)| -|[joint data inpainting and graph learning via unrolled neural networks](https://arxiv.org/abs/2407.11429)|[Graph-Learning-via-Unrolling](https://github.com/PushkalM11/Graph-Learning-via-Unrolling)| -|[multi-channel masked autoencoder and comprehensive evaluations for reconstructing 12-lead ecg from arbitrary single-lead ecg](https://arxiv.org/abs/2407.11481)|[mcma](https://github.com/chenjiar3/mcma)| -|[algebra of nonlocal boxes and the collapse of communication complexity](https://arxiv.org/abs/2312.00725)|[algebra-of-boxes-code](https://github.com/pierre-botteron/algebra-of-boxes-code)| +|date|paper|code| +|---|---|---| +|2407.11429|[joint data inpainting and graph learning via unrolled neural networks](https://arxiv.org/abs/2407.11429)|[Graph-Learning-via-Unrolling](https://github.com/PushkalM11/Graph-Learning-via-Unrolling)| +|2407.11481|[multi-channel masked autoencoder and comprehensive evaluations for reconstructing 12-lead ecg from arbitrary single-lead ecg](https://arxiv.org/abs/2407.11481)|[mcma](https://github.com/chenjiar3/mcma)| ## 2024-07-16 -|paper|code| -|---|---| -|[you can wash hands better: accurate daily handwashing assessment with smartwatches](https://arxiv.org/abs/2112.06657)|[uwash](https://github.com/aiotgroup/uwash)| -|[single-shot quantum signal processing interferometry](https://arxiv.org/abs/2311.13703)|[qsp-interferometry](https://github.com/yuanliu1/qsp-interferometry)| -|[towards task-compatible compressible representations](https://arxiv.org/abs/2405.10244)|[research](https://github.com/adeandrade/research)| -|[biased backpressure routing using link features and graph neural networks](https://arxiv.org/abs/2407.09753)|[dutybp](https://github.com/zhongyuanzhao/dutybp)| -|[type-based unsourced multiple access](https://arxiv.org/abs/2404.19552)|[TUMA](https://github.com/khachoang1412/TUMA)| -|[group projected subspace pursuit for block sparse signal reconstruction: convergence analysis and applications](https://arxiv.org/abs/2407.07707)|[BlockSparse](https://github.com/RoyYuchenHe/BlockSparse)| -|[fast and provable simultaneous blind super-resolution and demixing for point source signals: scaled gradient descent without regularization](https://arxiv.org/abs/2407.09900)|[Simultaneous-Blind-Super-Resolution-and-Demixing](https://github.com/jcchen2017/Simultaneous-Blind-Super-Resolution-and-Demixing)| +|date|paper|code| +|---|---|---| +|2407.09753|[biased backpressure routing using link features and graph neural networks](https://arxiv.org/abs/2407.09753)|[dutybp](https://github.com/zhongyuanzhao/dutybp)| +|2407.07707|[group projected subspace pursuit for block sparse signal reconstruction: convergence analysis and applications](https://arxiv.org/abs/2407.07707)|[BlockSparse](https://github.com/RoyYuchenHe/BlockSparse)| +|2407.09900|[fast and provable simultaneous blind super-resolution and demixing for point source signals: scaled gradient descent without regularization](https://arxiv.org/abs/2407.09900)|[Simultaneous-Blind-Super-Resolution-and-Demixing](https://github.com/jcchen2017/Simultaneous-Blind-Super-Resolution-and-Demixing)| ## 2024-07-15 -|paper|code| -|---|---| -|[compressed sensing: a discrete optimization approach](https://arxiv.org/abs/2306.04647)|[discretecompressedsensing.jl](https://github.com/nicholasjohnson2020/discretecompressedsensing.jl)| +|date|paper|code| +|---|---|---| ## 2024-07-12 -|paper|code| -|---|---| -|[subspacenet: deep learning-aided subspace methods for doa estimation](https://arxiv.org/abs/2306.02271)|[subspacenet](https://github.com/shlezingerlab/subspacenet)| -|[generalizable sleep staging via multi-level domain alignment](https://arxiv.org/abs/2401.05363)|[sleepdg](https://github.com/wjq-learning/sleepdg)| -|[a fast multitaper power spectrum estimation in nonuniformly sampled time series](https://arxiv.org/abs/2407.01943)|[mtnufft](https://github.com/jiecui/mtnufft)| -|[joint optimization of age of information and energy consumption in nr-v2x system based on deep reinforcement learning](https://arxiv.org/abs/2407.08458)|[joint-optimization-of-aoi-and-energy-consumption-in-nr-v2x-system-based-on-drl](https://github.com/qiongwu86/joint-optimization-of-aoi-and-energy-consumption-in-nr-v2x-system-based-on-drl)| +|date|paper|code| +|---|---|---| +|2407.01943|[a fast multitaper power spectrum estimation in nonuniformly sampled time series](https://arxiv.org/abs/2407.01943)|[mtnufft](https://github.com/jiecui/mtnufft)| +|2407.08458|[joint optimization of age of information and energy consumption in nr-v2x system based on deep reinforcement learning](https://arxiv.org/abs/2407.08458)|[joint-optimization-of-aoi-and-energy-consumption-in-nr-v2x-system-based-on-drl](https://github.com/qiongwu86/joint-optimization-of-aoi-and-energy-consumption-in-nr-v2x-system-based-on-drl)| ## 2024-07-11 -|paper|code| -|---|---| -|[principal component analysis in space forms](https://arxiv.org/abs/2301.02750)|[HoroPCA](https://github.com/HazyResearch/HoroPCA)| -|[a coding-theoretic analysis of hyperspherical prototypical learning geometry](https://arxiv.org/abs/2407.07664)|[coding_theoretic_hpl](https://github.com/martinlindstrom/coding_theoretic_hpl)| +|date|paper|code| +|---|---|---| +|2407.07664|[a coding-theoretic analysis of hyperspherical prototypical learning geometry](https://arxiv.org/abs/2407.07664)|[coding_theoretic_hpl](https://github.com/martinlindstrom/coding_theoretic_hpl)| ## 2024-07-10 -|paper|code| -|---|---| -|[subject-adaptive transfer learning using resting state eeg signals for cross-subject eeg motor imagery classification](https://arxiv.org/abs/2405.19346)|[miccai2024-restl](https://github.com/sionan/miccai2024-restl)| -|[fadam: adam is a natural gradient optimizer using diagonal empirical fisher information](https://arxiv.org/abs/2405.12807)|[fadam_pytorch](https://github.com/lessw2020/fadam_pytorch)| +|date|paper|code| +|---|---|---| ## 2024-07-09 -|paper|code| -|---|---| -|[cafnet: a confidence-driven framework for radar camera depth estimation](https://arxiv.org/abs/2407.00697)|[cafnet](https://github.com/harborsarah/cafnet)| -|[annotation of sleep depth index with scalable deep learning yields novel digital biomarkers for sleep health](https://arxiv.org/abs/2407.04753)|[SDI](https://github.com/sczzz3/SDI)| -|[a new framework for nonlinear kalman filters](https://arxiv.org/abs/2407.05717)|[a-new-framework-for-nonlinear-kalman-filters](https://github.com/shida-jiang/a-new-framework-for-nonlinear-kalman-filters)| -|[ldgcn: an edge-end lightweight dual gcn based on single-channel eeg for driver drowsiness monitoring](https://arxiv.org/abs/2407.05749)|[driver-drowsiness-monitoring](https://github.com/bryantdom/driver-drowsiness-monitoring)| -|[information limits and thouless-anderson-palmer equations for spiked matrix models with structured noise](https://arxiv.org/abs/2405.20993)|[spiked-matrix-models-with-structured-noise](https://github.com/xu-yz19/spiked-matrix-models-with-structured-noise)| -|[rpn: reconciled polynomial network towards unifying pgms, kernel svms, mlp and kan](https://arxiv.org/abs/2407.04819)|[tinyBIG](https://github.com/jwzhanggy/tinyBIG)| +|date|paper|code| +|---|---|---| +|2407.00697|[cafnet: a confidence-driven framework for radar camera depth estimation](https://arxiv.org/abs/2407.00697)|[cafnet](https://github.com/harborsarah/cafnet)| +|2407.04753|[annotation of sleep depth index with scalable deep learning yields novel digital biomarkers for sleep health](https://arxiv.org/abs/2407.04753)|[SDI](https://github.com/sczzz3/SDI)| +|2407.05717|[a new framework for nonlinear kalman filters](https://arxiv.org/abs/2407.05717)|[a-new-framework-for-nonlinear-kalman-filters](https://github.com/shida-jiang/a-new-framework-for-nonlinear-kalman-filters)| +|2407.05749|[ldgcn: an edge-end lightweight dual gcn based on single-channel eeg for driver drowsiness monitoring](https://arxiv.org/abs/2407.05749)|[driver-drowsiness-monitoring](https://github.com/bryantdom/driver-drowsiness-monitoring)| +|2407.04819|[rpn: reconciled polynomial network towards unifying pgms, kernel svms, mlp and kan](https://arxiv.org/abs/2407.04819)|[tinyBIG](https://github.com/jwzhanggy/tinyBIG)| ## 2024-07-08 -|paper|code| -|---|---| -|[neuro-bert: rethinking masked autoencoding for self-supervised neurological pretraining](https://arxiv.org/abs/2204.12440)|[OpenBioSeq](https://github.com/Westlake-AI/OpenBioSeq)| -|[swinjscc: taming swin transformer for deep joint source-channel coding](https://arxiv.org/abs/2308.09361)|[swinjscc](https://github.com/semcomm/swinjscc)| -|[learning multi-frequency partial correlation graphs](https://arxiv.org/abs/2311.15756)|[bspcg](https://github.com/officiallydac/bspcg)| -|[mt-hccar: multi-task deep learning with hierarchical classification and attention-based regression for cloud property retrieval](https://arxiv.org/abs/2401.16520)|[mt-hccar](https://github.com/ai-4-atmosphere-remote-sensing/mt-hccar)| -|[feature characterization for profile surface texture](https://arxiv.org/abs/2406.06381)|[feature-characterization-for-profile-surface-texture](https://github.com/mts-public/feature-characterization-for-profile-surface-texture)| -|[groupwise deformable registration of diffusion tensor cardiovascular magnetic resonance: disentangling diffusion contrast, respiratory and cardiac motions](https://arxiv.org/abs/2406.13788)|[dtcmr-reg](https://github.com/ayanglab/dtcmr-reg)| -|[prediction of rare channel conditions using bayesian statistics and extreme value theory](https://arxiv.org/abs/2407.01188)|[bayesian_evt_urllc](https://github.com/aau-cnt/bayesian_evt_urllc)| -|[biometric authentication based on enhanced remote photoplethysmography signal morphology](https://arxiv.org/abs/2407.04127)|[rppg_biometrics](https://github.com/zhaodongsun/rppg_biometrics)| -|[inference through innovation processes tested in the authorship attribution task](https://arxiv.org/abs/2306.05186)|[InnovationProcessesInference](https://github.com/GiulioTani/InnovationProcessesInference)| +|date|paper|code| +|---|---|---| +|2407.01188|[prediction of rare channel conditions using bayesian statistics and extreme value theory](https://arxiv.org/abs/2407.01188)|[bayesian_evt_urllc](https://github.com/aau-cnt/bayesian_evt_urllc)| +|2407.04127|[biometric authentication based on enhanced remote photoplethysmography signal morphology](https://arxiv.org/abs/2407.04127)|[rppg_biometrics](https://github.com/zhaodongsun/rppg_biometrics)| ## 2024-07-04 -|paper|code| -|---|---| -|[fullsubnet: a full-band and sub-band fusion model for real-time single-channel speech enhancement](https://arxiv.org/abs/2010.15508)|[FullSubNet](https://github.com/haoxiangsnr/FullSubNet)| -|[edpnet: an efficient dual prototype network for motor imagery eeg decoding](https://arxiv.org/abs/2407.03177)|[edpnet](https://github.com/hancan16/edpnet)| +|date|paper|code| +|---|---|---| +|2407.03177|[edpnet: an efficient dual prototype network for motor imagery eeg decoding](https://arxiv.org/abs/2407.03177)|[edpnet](https://github.com/hancan16/edpnet)| ## 2024-07-03 -|paper|code| -|---|---| -|[deep imbalanced regression to estimate vascular age from ppg data: a novel digital biomarker for cardiovascular health](https://arxiv.org/abs/2406.14953)|[Dist-Loss](https://github.com/Ngk03/Dist-Loss)| +|date|paper|code| +|---|---|---| ## 2024-07-02 -|paper|code| -|---|---| -|[stimulus-informed generalized canonical correlation analysis for group analysis of neural responses to natural stimuli](https://arxiv.org/abs/2401.17841)|[si-gcca](https://github.com/alexanderbertrandlab/si-gcca)| -|[integrating pre-trained language model with physical layer communications](https://arxiv.org/abs/2402.11656)|[on-device-ai-comm](https://github.com/abman23/on-device-ai-comm)| -|[srvit: vision transformers for estimating radar reflectivity from satellite observations at scale](https://arxiv.org/abs/2406.16955)|[srvit](https://github.com/stockeh/srvit)| -|[robust low-cost drone detection and classification in low snr environments](https://arxiv.org/abs/2406.18624)|[noisy-drone-rf-signal-classification-v2](https://github.com/sgluege/noisy-drone-rf-signal-classification-v2)| -|[neural distributed source coding](https://arxiv.org/abs/2106.02797)|[neural-dsc](https://github.com/acnagle/neural-dsc)| -|[generalization error of graph neural networks in the mean-field regime](https://arxiv.org/abs/2402.07025)|[gnn_mf_ge](https://github.com/sherylhyx/gnn_mf_ge)| +|date|paper|code| +|---|---|---| ## 2024-07-01 -|paper|code| -|---|---| -|[linear periodically time-variant digital pll phase noise modeling using conversion matrices and uncorrelated upsampling](https://arxiv.org/abs/2401.13897)|[PLL](https://github.com/patmercier/PLL)| -|[spatio-spectral structure tensor total variation for hyperspectral image denoising and destriping](https://arxiv.org/abs/2404.03313)|[spatio-spectral-structure-tensor-total-variation-for-hyperspectral-image-denoising-and-destriping](https://github.com/mdi-tokyotech/spatio-spectral-structure-tensor-total-variation-for-hyperspectral-image-denoising-and-destriping)| -|[fadam: adam is a natural gradient optimizer using diagonal empirical fisher information](https://arxiv.org/abs/2405.12807)|[fadam_pytorch](https://github.com/lessw2020/fadam_pytorch)| -|[kernel vs. kernel: exploring how the data structure affects neural collapse](https://arxiv.org/abs/2406.02105)|[shallow_nc1](https://github.com/kvignesh1420/shallow_nc1)| -|[machine learning predictors for min-entropy estimation](https://arxiv.org/abs/2406.19983)|[ml-predictors-min-entropy-estimation](https://github.com/qursa-uc3m/ml-predictors-min-entropy-estimation)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/08.md b/archives/2024/08.md index 2336fd9e..626e0473 100644 --- a/archives/2024/08.md +++ b/archives/2024/08.md @@ -1,186 +1,121 @@ # August 2024 Archive ## 2024-08-31 -|paper|code| -|---|---| -|[josephson oscillations of two weakly coupled bose-einstein condensates](https://arxiv.org/abs/2407.06208)|[BecJosephsonCurrent](https://github.com/alexej-schelle/BecJosephsonCurrent)| +|date|paper|code| +|---|---|---| ## 2024-08-30 -|paper|code| -|---|---| -|[massive digital over-the-air computation for communication-efficient federated edge learning](https://arxiv.org/abs/2405.15969)|[md-aircomp](https://github.com/liqiao19/md-aircomp)| -|[flexible framework for generating synthetic electrocardiograms and photoplethysmograms](https://arxiv.org/abs/2408.16291)|[framework_for_synthetic_biosignals](https://github.com/utu-health-research/framework_for_synthetic_biosignals)| -|[espargos: phase-coherent wifi csi datasets for wireless sensing research](https://arxiv.org/abs/2408.16377)|[espargos-wifi-channelcharting](https://github.com/jeija/espargos-wifi-channelcharting)| -|[robomnist: a multimodal dataset for multi-robot activity recognition using wifi sensing, video, and audio](https://arxiv.org/abs/2408.16703)|[robomnist](https://github.com/siamilab/robomnist)| -|[protograph-based batched network codes](https://arxiv.org/abs/2408.16365)|[bnc](https://github.com/zhu-mingyang/bnc)| +|date|paper|code| +|---|---|---| +|2408.16291|[flexible framework for generating synthetic electrocardiograms and photoplethysmograms](https://arxiv.org/abs/2408.16291)|[framework_for_synthetic_biosignals](https://github.com/utu-health-research/framework_for_synthetic_biosignals)| +|2408.16377|[espargos: phase-coherent wifi csi datasets for wireless sensing research](https://arxiv.org/abs/2408.16377)|[espargos-wifi-channelcharting](https://github.com/jeija/espargos-wifi-channelcharting)| +|2408.16703|[robomnist: a multimodal dataset for multi-robot activity recognition using wifi sensing, video, and audio](https://arxiv.org/abs/2408.16703)|[robomnist](https://github.com/siamilab/robomnist)| +|2408.16365|[protograph-based batched network codes](https://arxiv.org/abs/2408.16365)|[bnc](https://github.com/zhu-mingyang/bnc)| ## 2024-08-29 -|paper|code| -|---|---| -|[geometric neural network based on phase space for bci-eeg decoding](https://arxiv.org/abs/2403.05645)|[Phase-SPDNet](https://github.com/carraraig/Phase-SPDNet)| -|[es-ptam: event-based stereo parallel tracking and mapping](https://arxiv.org/abs/2408.15605)|[es-ptam](https://github.com/tub-rip/es-ptam)| +|date|paper|code| +|---|---|---| +|2408.15605|[es-ptam: event-based stereo parallel tracking and mapping](https://arxiv.org/abs/2408.15605)|[es-ptam](https://github.com/tub-rip/es-ptam)| ## 2024-08-28 -|paper|code| -|---|---| -|[multi-scale transformer-based network for emotion recognition from multi physiological signals](https://arxiv.org/abs/2305.00769)|[EPiC-2023-ACII](https://github.com/vsl-team/EPiC-2023-ACII)| -|[graph gospa metric: a metric to measure the discrepancy between graphs of different sizes](https://arxiv.org/abs/2311.07596)|[the-graph-gospa-metric](https://github.com/jinhaogu/the-graph-gospa-metric)| -|[neural network-based successive interference cancellation for non-linear bandlimited channels](https://arxiv.org/abs/2401.09217)|[nn-mi](https://github.com/dplabst/nn-mi)| -|[localising the seizure onset zone from single-pulse electrical stimulation responses with a cnn transformer](https://arxiv.org/abs/2403.20324)|[localising_soz_from_spes](https://github.com/norrisjamie23/localising_soz_from_spes)| -|[minimal algorithmic information loss methods for dimension reduction, feature selection and network sparsification](https://arxiv.org/abs/1802.05843)|[Network-Robustness-by-Kolmogorov-Complexity](https://github.com/andandandand/Network-Robustness-by-Kolmogorov-Complexity)| -|[fast erasure decoder for hypergraph product codes](https://arxiv.org/abs/2208.01002)|[pruned-peeling-and-vh-decoder](https://github.com/nicholas-connolly/pruned-peeling-and-vh-decoder)| +|date|paper|code| +|---|---|---| ## 2024-08-27 -|paper|code| -|---|---| -|[toward integrated sensing and communications in ieee 802.11bf wi-fi networks](https://arxiv.org/abs/2212.13930)|[sharpax](https://github.com/francescamen/sharpax)| -|[interpretable and robust ai in eeg systems: a survey](https://arxiv.org/abs/2304.10755)|[survey](https://github.com/xinliangzhou/survey)| -|[a generalized bandsplit neural network for cinematic audio source separation](https://arxiv.org/abs/2309.02539)|[bandit](https://github.com/karnwatcharasupat/bandit)| -|[wi-bfi: extracting the ieee 802.11 beamforming feedback information from commercial wi-fi devices](https://arxiv.org/abs/2309.04408)|[wi-bfi](https://github.com/kfoysalhaque/wi-bfi)| -|[outlier-insensitive kalman filtering: theory and applications](https://arxiv.org/abs/2309.09505)|[oikf-nuv](https://github.com/kalmannet/oikf-nuv)| -|[topological filtering of a signal over a network](https://arxiv.org/abs/2408.14109)|[topapprox](https://github.com/mvlier/topapprox)| -|[reduce computational complexity for continuous wavelet transform in acoustic recognition using hop size](https://arxiv.org/abs/2408.14302)|[Continuous-Wavelet-Transform-in-Acoustic-Recognition-Using-Hop-Size](https://github.com/phandangthoai/Continuous-Wavelet-Transform-in-Acoustic-Recognition-Using-Hop-Size)| -|[on confidence sequences for bounded random processes via universal gambling strategies](https://arxiv.org/abs/2207.12382)|[confidence-sequence-via-gambling](https://github.com/jongharyu/confidence-sequence-via-gambling)| -|[hrgraph: leveraging llms for hr data knowledge graphs with information propagation-based job recommendation](https://arxiv.org/abs/2408.13521)|[hrgraph](https://github.com/azminewasi/hrgraph)| +|date|paper|code| +|---|---|---| +|2408.14109|[topological filtering of a signal over a network](https://arxiv.org/abs/2408.14109)|[topapprox](https://github.com/mvlier/topapprox)| +|2408.14302|[reduce computational complexity for continuous wavelet transform in acoustic recognition using hop size](https://arxiv.org/abs/2408.14302)|[Continuous-Wavelet-Transform-in-Acoustic-Recognition-Using-Hop-Size](https://github.com/phandangthoai/Continuous-Wavelet-Transform-in-Acoustic-Recognition-Using-Hop-Size)| +|2408.13521|[hrgraph: leveraging llms for hr data knowledge graphs with information propagation-based job recommendation](https://arxiv.org/abs/2408.13521)|[hrgraph](https://github.com/azminewasi/hrgraph)| ## 2024-08-26 -|paper|code| -|---|---| -|[mitigating mismatch compression in differential local field potentials](https://arxiv.org/abs/2204.03778)|[mismatch_compression](https://github.com/virati/mismatch_compression)| -|[concept-based explainability for an eeg transformer model](https://arxiv.org/abs/2307.12745)|[tcav-bendr](https://github.com/andersgmadsen/tcav-bendr)| +|date|paper|code| +|---|---|---| ## 2024-08-23 -|paper|code| -|---|---| -|[self-supervised learning for clustering of wireless spectrum activity](https://arxiv.org/abs/2210.02899)|[self-supervised-spectrum-sensing](https://github.com/sensorlab/self-supervised-spectrum-sensing)| -|[pulse shape discrimination based on the tempotron: a powerful classifier on gpu](https://arxiv.org/abs/2305.18205)|[TempotronGPU](https://github.com/HaoranLiu507/TempotronGPU)| -|[leveraging variational autoencoders for parameterized mmse estimation](https://arxiv.org/abs/2307.05352)|[vae-estimator](https://github.com/tum-msv/vae-estimator)| -|[real-time event recognition of long-distance distributed vibration sensing with knowledge distillation and hardware acceleration](https://arxiv.org/abs/2408.03647)|[efficient-dvs](https://github.com/hust-iof/efficient-dvs)| -|[gram-schmidt methods for unsupervised feature extraction and selection](https://arxiv.org/abs/2311.09386)|[gram_schmidt_feature_extraction](https://github.com/byaghooti/gram_schmidt_feature_extraction)| -|[fadam: adam is a natural gradient optimizer using diagonal empirical fisher information](https://arxiv.org/abs/2405.12807)|[fadam_pytorch](https://github.com/lessw2020/fadam_pytorch)| -|[a scalable quantum non-local neural network for image classification](https://arxiv.org/abs/2407.18906)|[QNL-Net](https://github.com/sparshgup/QNL-Net)| +|date|paper|code| +|---|---|---| +|2408.03647|[real-time event recognition of long-distance distributed vibration sensing with knowledge distillation and hardware acceleration](https://arxiv.org/abs/2408.03647)|[efficient-dvs](https://github.com/hust-iof/efficient-dvs)| ## 2024-08-22 -|paper|code| -|---|---| -|[s4sleep: elucidating the design space of deep-learning-based sleep stage classification models](https://arxiv.org/abs/2310.06715)|[s4sleep](https://github.com/ai4healthuol/s4sleep)| -|[energy-efficient beamforming for riss-aided communications: gradient based meta learning](https://arxiv.org/abs/2311.06861)|[GMML](https://github.com/fenghaozhu/GMML)| -|[towards end-to-end gps localization with neural pseudorange correction](https://arxiv.org/abs/2401.10685)|[e2eprnet](https://github.com/ailocar/e2eprnet)| -|[5g nr prach detection with convolutional neural networks (cnn): overcoming cell interference challenges](https://arxiv.org/abs/2408.11659)|[PRACHInterferenceDetectionModel](https://github.com/dguel82/PRACHInterferenceDetectionModel)| -|[trellis bma: coded trace reconstruction on ids channels for dna storage](https://arxiv.org/abs/2107.06440)|[clustered-nanopore-reads-dataset](https://github.com/microsoft/clustered-nanopore-reads-dataset)| -|[fast erasure decoder for hypergraph product codes](https://arxiv.org/abs/2208.01002)|[pruned-peeling-and-vh-decoder](https://github.com/nicholas-connolly/pruned-peeling-and-vh-decoder)| -|[improved field size bounds for higher order mds codes](https://arxiv.org/abs/2212.11262)|[mds3-groebner](https://github.com/jbrakensiek/mds3-groebner)| -|[understanding is compression](https://arxiv.org/abs/2407.07723)|[medal](https://github.com/mcGill-NLP/medal)| +|date|paper|code| +|---|---|---| +|2408.11659|[5g nr prach detection with convolutional neural networks (cnn): overcoming cell interference challenges](https://arxiv.org/abs/2408.11659)|[PRACHInterferenceDetectionModel](https://github.com/dguel82/PRACHInterferenceDetectionModel)| ## 2024-08-21 -|paper|code| -|---|---| -|[robust mri reconstruction by smoothed unrolling (smug)](https://arxiv.org/abs/2312.07784)|[smug_journal](https://github.com/sjames40/smug_journal)| -|[spectrum prediction with deep 3d pyramid vision transformer learning](https://arxiv.org/abs/2408.06870)|[Real-world-Spectrum](https://github.com/pgl1234/Real-world-Spectrum)| -|[parkinson's disease classification via eeg: all you need is a single convolutional layer](https://arxiv.org/abs/2408.10457)|[LightCNNforPD](https://github.com/MDFahimAnjum/LightCNNforPD)| +|date|paper|code| +|---|---|---| +|2408.06870|[spectrum prediction with deep 3d pyramid vision transformer learning](https://arxiv.org/abs/2408.06870)|[Real-world-Spectrum](https://github.com/pgl1234/Real-world-Spectrum)| +|2408.10457|[parkinson's disease classification via eeg: all you need is a single convolutional layer](https://arxiv.org/abs/2408.10457)|[LightCNNforPD](https://github.com/MDFahimAnjum/LightCNNforPD)| ## 2024-08-20 -|paper|code| -|---|---| -|[textless unit-to-unit training for many-to-many multilingual speech-to-speech translation](https://arxiv.org/abs/2308.01831)|[utut](https://github.com/choijeongsoo/utut)| -|[learning based dynamic cluster reconfiguration for uav mobility management with 3d beamforming](https://arxiv.org/abs/2402.00224)|[icmlcn-2024-dynamic-clustering](https://github.com/irshadmeer/icmlcn-2024-dynamic-clustering)| -|[sim2real in reconstructive spectroscopy: deep learning with augmented device-informed data simulation](https://arxiv.org/abs/2403.12354)|[rec_spectrometer](https://github.com/j1goblue/rec_spectrometer)| -|[an observability-constrained magnetic field-aided inertial navigation system -- extended version](https://arxiv.org/abs/2406.02161)|[OC-MAINS-code](https://github.com/Huang-Chuan/OC-MAINS-code)| -|[an optimal pairwise merge algorithm improves the quality and consistency of nonnegative matrix factorization](https://arxiv.org/abs/2408.09013)|[NMFMerge.jl](https://github.com/HolyLab/NMFMerge.jl)| -|[compression represents intelligence linearly](https://arxiv.org/abs/2404.09937)|[llm-compression-intelligence](https://github.com/hkust-nlp/llm-compression-intelligence)| +|date|paper|code| +|---|---|---| +|2408.09013|[an optimal pairwise merge algorithm improves the quality and consistency of nonnegative matrix factorization](https://arxiv.org/abs/2408.09013)|[NMFMerge.jl](https://github.com/HolyLab/NMFMerge.jl)| ## 2024-08-19 -|paper|code| -|---|---| -|[multistatic-radar rcs-signature recognition of aerial vehicles: a bayesian fusion approach](https://arxiv.org/abs/2402.17987)|[rcs_atr](https://github.com/mlpotter/rcs_atr)| -|[adversarial contrastive learning based physics-informed temporal networks for cuffless blood pressure estimation](https://arxiv.org/abs/2408.08488)|[acl-pitn](https://github.com/zest86/acl-pitn)| -|[entropy coding of unordered data structures](https://arxiv.org/abs/2408.08837)|[shuffle-coding](https://github.com/juliuskunze/shuffle-coding)| +|date|paper|code| +|---|---|---| +|2408.08488|[adversarial contrastive learning based physics-informed temporal networks for cuffless blood pressure estimation](https://arxiv.org/abs/2408.08488)|[acl-pitn](https://github.com/zest86/acl-pitn)| +|2408.08837|[entropy coding of unordered data structures](https://arxiv.org/abs/2408.08837)|[shuffle-coding](https://github.com/juliuskunze/shuffle-coding)| ## 2024-08-16 -|paper|code| -|---|---| -|[exact tensor completion powered by slim transforms](https://arxiv.org/abs/2402.03468)|[transformed_tnn](https://github.com/vecevecev/transformed_tnn)| -|[accelerating high-fidelity waveform generation via adversarial flow matching optimization](https://arxiv.org/abs/2408.08019)|[periodwave](https://github.com/sh-lee-prml/periodwave)| -|[gsvd-nmf: recovering missing features in non-negative matrix factorization](https://arxiv.org/abs/2408.08260)|[gsvdinitialization.jl](https://github.com/holylab/gsvdinitialization.jl)| -|[josephson oscillations of two weakly coupled bose-einstein condensates](https://arxiv.org/abs/2407.06208)|[BecJosephsonCurrent](https://github.com/alexej-schelle/BecJosephsonCurrent)| +|date|paper|code| +|---|---|---| +|2408.08019|[accelerating high-fidelity waveform generation via adversarial flow matching optimization](https://arxiv.org/abs/2408.08019)|[periodwave](https://github.com/sh-lee-prml/periodwave)| +|2408.08260|[gsvd-nmf: recovering missing features in non-negative matrix factorization](https://arxiv.org/abs/2408.08260)|[gsvdinitialization.jl](https://github.com/holylab/gsvdinitialization.jl)| ## 2024-08-15 -|paper|code| -|---|---| -|[self-supervised scalable deep compressed sensing](https://arxiv.org/abs/2308.13777)|[scnet](https://github.com/guaishou74851/scnet)| -|[virus-nerf -- vision, infrared and ultrasonic based neural radiance fields](https://arxiv.org/abs/2403.09477)|[virus_nerf](https://github.com/ethz-asl/virus_nerf)| -|[using explainable ai for eeg-based reduced montage neonatal seizure detection](https://arxiv.org/abs/2406.16908)|[braineocare](https://github.com/dinuka-1999/braineocare)| -|[lipcot: linear predictive coding based tokenizer for self-supervised learning of time series data via language models](https://arxiv.org/abs/2408.07292)|[lipcot](https://github.com/mdfahimanjum/lipcot)| -|[adaptive basis function selection for computationally efficient predictions](https://arxiv.org/abs/2408.07480)|[adaptive-bf-selection](https://github.com/aokullberg/adaptive-bf-selection)| -|[periodwave: multi-period flow matching for high-fidelity waveform generation](https://arxiv.org/abs/2408.07547)|[periodwave](https://github.com/sh-lee-prml/periodwave)| -|[outsourcing control requires control complexity](https://arxiv.org/abs/2209.01418)|[learningrequiresintinf](https://github.com/carlottalanger/learningrequiresintinf)| -|[on the salient limitations of the methods of assembly theory and their classification of molecular biosignatures](https://arxiv.org/abs/2210.00901)|[mscomplexity](https://github.com/abicumaran/mscomplexity)| -|[information-theoretic measures on lattices for high-order interactions](https://arxiv.org/abs/2408.07533)|[nips2024hoi](https://github.com/neurips2024hoi/nips2024hoi)| +|date|paper|code| +|---|---|---| +|2408.07292|[lipcot: linear predictive coding based tokenizer for self-supervised learning of time series data via language models](https://arxiv.org/abs/2408.07292)|[lipcot](https://github.com/mdfahimanjum/lipcot)| +|2408.07480|[adaptive basis function selection for computationally efficient predictions](https://arxiv.org/abs/2408.07480)|[adaptive-bf-selection](https://github.com/aokullberg/adaptive-bf-selection)| +|2408.07547|[periodwave: multi-period flow matching for high-fidelity waveform generation](https://arxiv.org/abs/2408.07547)|[periodwave](https://github.com/sh-lee-prml/periodwave)| +|2408.07533|[information-theoretic measures on lattices for high-order interactions](https://arxiv.org/abs/2408.07533)|[nips2024hoi](https://github.com/neurips2024hoi/nips2024hoi)| ## 2024-08-14 -|paper|code| -|---|---| -|[eeg-macs: manifold attention and confidence stratification for eeg-based cross-center brain disease diagnosis under unreliable annotations](https://arxiv.org/abs/2405.00734)|[eeg-disease-macs](https://github.com/ici-bci/eeg-disease-macs)| -|[interpretable pre-trained transformers for heart time-series data](https://arxiv.org/abs/2407.20775)|[heartgpt](https://github.com/harryjdavies/heartgpt)| -|[how transformers learn causal structure with gradient descent](https://arxiv.org/abs/2402.14735)|[transformers-learn-causal-structure](https://github.com/eshnich/transformers-learn-causal-structure)| +|date|paper|code| +|---|---|---| ## 2024-08-13 -|paper|code| -|---|---| -|[convolutional proximal neural networks and plug-and-play algorithms](https://arxiv.org/abs/2011.02281)|[Proximal_Neural_Networks](https://github.com/johertrich/Proximal_Neural_Networks)| -|[localising the seizure onset zone from single-pulse electrical stimulation responses with a cnn transformer](https://arxiv.org/abs/2403.20324)|[localising_soz_from_spes](https://github.com/norrisjamie23/localising_soz_from_spes)| -|[time is not enough: time-frequency based explanation for time-series black-box models](https://arxiv.org/abs/2408.03636)|[time_is_not_enough](https://github.com/gustmd0121/time_is_not_enough)| -|[a robust baro-radar-inertial odometry m-estimator for multicopter navigation in cities and forests](https://arxiv.org/abs/2408.05764)|[rio](https://github.com/ethz-asl/rio)| -|[residual-inr: communication efficient on-device learning using implicit neural representation](https://arxiv.org/abs/2408.05617)|[residual-inr](https://github.com/sharc-lab/residual-inr)| +|date|paper|code| +|---|---|---| +|2408.03636|[time is not enough: time-frequency based explanation for time-series black-box models](https://arxiv.org/abs/2408.03636)|[time_is_not_enough](https://github.com/gustmd0121/time_is_not_enough)| +|2408.05764|[a robust baro-radar-inertial odometry m-estimator for multicopter navigation in cities and forests](https://arxiv.org/abs/2408.05764)|[rio](https://github.com/ethz-asl/rio)| +|2408.05617|[residual-inr: communication efficient on-device learning using implicit neural representation](https://arxiv.org/abs/2408.05617)|[residual-inr](https://github.com/sharc-lab/residual-inr)| ## 2024-08-12 -|paper|code| -|---|---| -|[the rlign algorithm for enhanced electrocardiogram analysis through r-peak alignment for explainable classification and clustering](https://arxiv.org/abs/2407.15555)|[rlign](https://github.com/imi-ms/rlign)| +|date|paper|code| +|---|---|---| ## 2024-08-09 -|paper|code| -|---|---| -|[exploiting structure in quantum relative entropy programs](https://arxiv.org/abs/2407.00241)|[qrep-structure](https://github.com/kerry-he/qrep-structure)| +|date|paper|code| +|---|---|---| ## 2024-08-08 -|paper|code| -|---|---| -|[exploiting semantic localization in highly dynamic wireless networks using deep homoscedastic domain adaptation](https://arxiv.org/abs/2310.07792)|[semanticloc](https://github.com/leo-chu/semanticloc)| -|[telco-rag: navigating the challenges of retrieval-augmented language models for telecommunications](https://arxiv.org/abs/2404.15939)|[telco-rag](https://github.com/netop-team/telco-rag)| -|[unleashing the power of data tsunami: a comprehensive survey on data assessment and selection for instruction tuning of language models](https://arxiv.org/abs/2408.02085)|[fantastic-data-engineering](https://github.com/yuleiqin/fantastic-data-engineering)| -|[real-time event recognition of long-distance distributed vibration sensing with knowledge distillation and hardware acceleration](https://arxiv.org/abs/2408.03647)|[efficient-dvs](https://github.com/hust-iof/efficient-dvs)| -|[bayes-optimal learning of an extensive-width neural network from quadratically many samples](https://arxiv.org/abs/2408.03733)|[ExtensiveWidthQuadraticSamples](https://github.com/SPOC-group/ExtensiveWidthQuadraticSamples)| +|date|paper|code| +|---|---|---| +|2408.02085|[unleashing the power of data tsunami: a comprehensive survey on data assessment and selection for instruction tuning of language models](https://arxiv.org/abs/2408.02085)|[fantastic-data-engineering](https://github.com/yuleiqin/fantastic-data-engineering)| +|2408.03647|[real-time event recognition of long-distance distributed vibration sensing with knowledge distillation and hardware acceleration](https://arxiv.org/abs/2408.03647)|[efficient-dvs](https://github.com/hust-iof/efficient-dvs)| +|2408.03733|[bayes-optimal learning of an extensive-width neural network from quadratically many samples](https://arxiv.org/abs/2408.03733)|[ExtensiveWidthQuadraticSamples](https://github.com/SPOC-group/ExtensiveWidthQuadraticSamples)| ## 2024-08-07 -|paper|code| -|---|---| -|[comparison analysis between standard polysomnographic data and in-ear-eeg signals: a preliminary study](https://arxiv.org/abs/2401.10107)|[in_ear_eeg_vs_psg](https://github.com/gianpaolopalo13/in_ear_eeg_vs_psg)| +|date|paper|code| +|---|---|---| ## 2024-08-06 -|paper|code| -|---|---| -|[sky-gvio: an enhanced gnss/ins/vision navigation with fcn-based sky-segmentation in urban canyon](https://arxiv.org/abs/2404.11070)|[sky-view-images](https://github.com/whuwangjr/sky-view-images)| -|[fadam: adam is a natural gradient optimizer using diagonal empirical fisher information](https://arxiv.org/abs/2405.12807)|[fadam_pytorch](https://github.com/lessw2020/fadam_pytorch)| +|date|paper|code| +|---|---|---| ## 2024-08-05 -|paper|code| -|---|---| -|[approximate message passing with rigorous guarantees for pooled data and quantitative group testing](https://arxiv.org/abs/2309.15507)|[amp_pooled_qgt](https://github.com/pablopasc/amp_pooled_qgt)| -|[robust beamforming with gradient-based liquid neural network](https://arxiv.org/abs/2405.07291)|[GLNN](https://github.com/tp1000d/GLNN)| -|[functional renormalization group for signal detection and stochastic ergodicity breaking](https://arxiv.org/abs/2310.07499)|[stochastic-signal-detection](https://github.com/thesfinox/stochastic-signal-detection)| +|date|paper|code| +|---|---|---| ## 2024-08-02 -|paper|code| -|---|---| -|[localization of brain activity from eeg/meg using mv-pure framework](https://arxiv.org/abs/1809.03930)|[supFunSim](https://github.com/IS-UMK/supFunSim)| -|[hierarchical state space models for continuous sequence-to-sequence modeling](https://arxiv.org/abs/2402.10211)|[hiss](https://github.com/raunaqbhirangi/hiss)| +|date|paper|code| +|---|---|---| ## 2024-08-01 -|paper|code| -|---|---| -|[k-deep simplex: deep manifold learning via local dictionaries](https://arxiv.org/abs/2012.02134)|[manifold-learning-with-simplex-constraints](https://github.com/pbt17/manifold-learning-with-simplex-constraints)| -|[sleepyco: automatic sleep scoring with feature pyramid and contrastive learning](https://arxiv.org/abs/2209.09452)|[sleepyco](https://github.com/gist-ailab/sleepyco)| -|[stimulus-informed generalized canonical correlation analysis for group analysis of neural responses to natural stimuli](https://arxiv.org/abs/2401.17841)|[si-gcca](https://github.com/alexanderbertrandlab/si-gcca)| -|[an exact theory of causal emergence for linear stochastic iteration systems](https://arxiv.org/abs/2405.09207)|[an_exact_causal_emergence_theory](https://github.com/kilovoltage/an_exact_causal_emergence_theory)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/09.md b/archives/2024/09.md index 10dfc476..2c4c7ee7 100644 --- a/archives/2024/09.md +++ b/archives/2024/09.md @@ -1,150 +1,102 @@ # September 2024 Archive ## 2024-09-30 -|paper|code| -|---|---| -|[interpretation of intracardiac electrograms through textual representations](https://arxiv.org/abs/2402.01115)|[text-egm](https://github.com/willxxy/text-egm)| -|[proprioception is all you need: terrain classification for boreal forests](https://arxiv.org/abs/2403.16877)|[BorealTC](https://github.com/norlab-ulaval/BorealTC)| -|[simpler gradient methods for blind super-resolution with lower iteration complexity](https://arxiv.org/abs/2409.18387)|[SimplerGDs-VHL](https://github.com/Jinshengg/SimplerGDs-VHL)| +|date|paper|code| +|---|---|---| +|2409.18387|[simpler gradient methods for blind super-resolution with lower iteration complexity](https://arxiv.org/abs/2409.18387)|[SimplerGDs-VHL](https://github.com/Jinshengg/SimplerGDs-VHL)| ## 2024-09-26 -|paper|code| -|---|---| -|[optimal vintage factor analysis with deflation varimax](https://arxiv.org/abs/2310.10545)|[optimal_deflation_varimax](https://github.com/jindiande/optimal_deflation_varimax)| -|[visual decoding and reconstruction via eeg embeddings with guided diffusion](https://arxiv.org/abs/2403.07721)|[eeg_image_decode](https://github.com/dongyangli-del/eeg_image_decode)| -|[the language of infographics: toward understanding conceptual metaphor use in scientific storytelling](https://arxiv.org/abs/2407.13416)|[metaphortool](https://github.com/lauragarrison87/metaphortool)| +|date|paper|code| +|---|---|---| ## 2024-09-25 -|paper|code| -|---|---| -|[mds-ed: multimodal decision support in the emergency department -- a benchmark dataset for diagnoses and deterioration prediction in emergency medicine](https://arxiv.org/abs/2407.17856)|[mds-ed](https://github.com/ai4healthuol/mds-ed)| +|date|paper|code| +|---|---|---| ## 2024-09-24 -|paper|code| -|---|---| -|[beamfocusing optimization for near-field wideband multi-user communications](https://arxiv.org/abs/2306.16861)|[beamfocusing-optimization-for-near-field-wideband-multi-user-communications](https://github.com/zhaolin820/beamfocusing-optimization-for-near-field-wideband-multi-user-communications)| -|[near-field velocity sensing and predictive beamforming](https://arxiv.org/abs/2311.09888)|[near-field-velocity-sensing-and-predictive-beamforming](https://github.com/zhaolin820/near-field-velocity-sensing-and-predictive-beamforming)| -|[szcore: a seizure community open-source research evaluation framework for the validation of eeg-based automated seizure detection algorithms](https://arxiv.org/abs/2402.13005)|[sz-validation-framework](https://github.com/esl-epfl/sz-validation-framework)| -|[genet: a graph neural network-based anti-noise task-oriented semantic communication paradigm](https://arxiv.org/abs/2403.18296)|[genet](https://github.com/chunbaobao/genet)| -|[speed: scalable preprocessing of eeg data for self-supervised learning](https://arxiv.org/abs/2408.08065)|[speed](https://github.com/andersgmadsen/speed)| -|[train-on-request: an on-device continual learning workflow for adaptive real-world brain machine interfaces](https://arxiv.org/abs/2409.09161)|[bmi-odcl](https://github.com/pulp-bio/bmi-odcl)| -|[performance evaluation of pac decoding with deep neural networks](https://arxiv.org/abs/2405.02590)|[Performance-Evaluation-of-PAC-Decoding-with-Deep-Neural-Networks](https://github.com/daijingixn/Performance-Evaluation-of-PAC-Decoding-with-Deep-Neural-Networks)| -|[alphazip: neural network-enhanced lossless text compression](https://arxiv.org/abs/2409.15046)|[alphazip](https://github.com/swathi-shree-narashiman/alphazip)| +|date|paper|code| +|---|---|---| +|2409.09161|[train-on-request: an on-device continual learning workflow for adaptive real-world brain machine interfaces](https://arxiv.org/abs/2409.09161)|[bmi-odcl](https://github.com/pulp-bio/bmi-odcl)| +|2409.15046|[alphazip: neural network-enhanced lossless text compression](https://arxiv.org/abs/2409.15046)|[alphazip](https://github.com/swathi-shree-narashiman/alphazip)| ## 2024-09-23 -|paper|code| -|---|---| -|[high perceptual quality wireless image delivery with denoising diffusion models](https://arxiv.org/abs/2309.15889)|[deepjscc-diffusion](https://github.com/ipc-lab/deepjscc-diffusion)| +|date|paper|code| +|---|---|---| ## 2024-09-20 -|paper|code| -|---|---| -|[online proximal admm for graph learning from streaming smooth signals](https://arxiv.org/abs/2409.12916)|[ogl](https://github.com/hchahuara/ogl)| -|[on the computational entanglement of distant features in adversarial machine learning](https://arxiv.org/abs/2309.15669)|[adversary-example-through-relativity](https://github.com/yenlunglai/adversary-example-through-relativity)| -|[enhancing 3d robotic vision robustness by minimizing adversarial mutual information through a curriculum training approach](https://arxiv.org/abs/2409.12379)|[mine-n-learn](https://github.com/nstrndrbi/mine-n-learn)| +|date|paper|code| +|---|---|---| +|2409.12916|[online proximal admm for graph learning from streaming smooth signals](https://arxiv.org/abs/2409.12916)|[ogl](https://github.com/hchahuara/ogl)| +|2409.12379|[enhancing 3d robotic vision robustness by minimizing adversarial mutual information through a curriculum training approach](https://arxiv.org/abs/2409.12379)|[mine-n-learn](https://github.com/nstrndrbi/mine-n-learn)| ## 2024-09-19 -|paper|code| -|---|---| -|[real-time sound event localization and detection: deployment challenges on edge devices](https://arxiv.org/abs/2409.11700)|[realtime-seld-edge](https://github.com/itsjunwei/realtime-seld-edge)| -|[adversarial attacks on neural networks through canonical riemannian foliations](https://arxiv.org/abs/2203.00922)|[curvnetattack](https://github.com/eliot-tron/curvnetattack)| +|date|paper|code| +|---|---|---| +|2409.11700|[real-time sound event localization and detection: deployment challenges on edge devices](https://arxiv.org/abs/2409.11700)|[realtime-seld-edge](https://github.com/itsjunwei/realtime-seld-edge)| ## 2024-09-18 -|paper|code| -|---|---| -|[a time-causal and time-recursive analogue of the gabor transform](https://arxiv.org/abs/2308.14512)|[pygabor](https://github.com/tonylindeberg/pygabor)| -|[3d-speaker-toolkit: an open-source toolkit for multimodal speaker verification and diarization](https://arxiv.org/abs/2403.19971)|[3D-Speaker](https://github.com/modelscope/3D-Speaker)| -|[laugh now cry later: controlling time-varying emotional states of flow-matching-based zero-shot text-to-speech](https://arxiv.org/abs/2407.12229)|[emoctrltts-eval](https://github.com/hbwu-ntu/emoctrltts-eval)| -|[nirvawave: an accurate and efficient near field wave propagation simulator for 6g and beyond](https://arxiv.org/abs/2409.11293)|[nirvawave](https://github.com/vahidyazdnian1378/nirvawave)| -|[muse: flexible voiceprint receptive fields and multi-path fusion enhanced taylor transformer for u-net-based speech enhancement](https://arxiv.org/abs/2406.04589)|[MUSE-Speech-Enhancement](https://github.com/huaidanquede/MUSE-Speech-Enhancement)| -|[generalized measures of anticipation and responsivity in online language processing](https://arxiv.org/abs/2409.10728)|[generalized-surprisal](https://github.com/rycolab/generalized-surprisal)| +|date|paper|code| +|---|---|---| +|2409.11293|[nirvawave: an accurate and efficient near field wave propagation simulator for 6g and beyond](https://arxiv.org/abs/2409.11293)|[nirvawave](https://github.com/vahidyazdnian1378/nirvawave)| +|2409.10728|[generalized measures of anticipation and responsivity in online language processing](https://arxiv.org/abs/2409.10728)|[generalized-surprisal](https://github.com/rycolab/generalized-surprisal)| ## 2024-09-17 -|paper|code| -|---|---| -|[interpretable ecg analysis for myocardial infarction detection through counterfactuals](https://arxiv.org/abs/2312.08304)|[vcce](https://github.com/tanyelai/vcce)| -|[csi-gpt: integrating generative pre-trained transformer with federated-tuning to acquire downlink massive mimo channels](https://arxiv.org/abs/2406.03438)|[csi-gpt](https://github.com/bit-zy/csi-gpt)| -|[train-on-request: an on-device continual learning workflow for adaptive real-world brain machine interfaces](https://arxiv.org/abs/2409.09161)|[bmi-odcl](https://github.com/pulp-bio/bmi-odcl)| -|[hyperedge representations with hypergraph wavelets: applications to spatial transcriptomics](https://arxiv.org/abs/2409.09469)|[hypergraph-wavelets](https://github.com/KrishnaswamyLab/hypergraph-wavelets)| -|[harnessing the power of federated learning in federated contextual bandits](https://arxiv.org/abs/2312.16341)|[fedigw](https://github.com/shengroup/fedigw)| -|[tele-llms: a series of specialized large language models for telecommunications](https://arxiv.org/abs/2409.05314)|[tele-llms](https://github.com/ali-maatouk/tele-llms)| +|date|paper|code| +|---|---|---| +|2409.09161|[train-on-request: an on-device continual learning workflow for adaptive real-world brain machine interfaces](https://arxiv.org/abs/2409.09161)|[bmi-odcl](https://github.com/pulp-bio/bmi-odcl)| +|2409.09469|[hyperedge representations with hypergraph wavelets: applications to spatial transcriptomics](https://arxiv.org/abs/2409.09469)|[hypergraph-wavelets](https://github.com/KrishnaswamyLab/hypergraph-wavelets)| +|2409.05314|[tele-llms: a series of specialized large language models for telecommunications](https://arxiv.org/abs/2409.05314)|[tele-llms](https://github.com/ali-maatouk/tele-llms)| ## 2024-09-16 -|paper|code| -|---|---| -|[a new framework for nonlinear kalman filters](https://arxiv.org/abs/2407.05717)|[a-new-framework-for-nonlinear-kalman-filters](https://github.com/shida-jiang/a-new-framework-for-nonlinear-kalman-filters)| -|[biased backpressure routing using link features and graph neural networks](https://arxiv.org/abs/2407.09753)|[dutybp](https://github.com/zhongyuanzhao/dutybp)| -|[online learning of expanding graphs](https://arxiv.org/abs/2409.08660)|[online_ntf_expanding](https://github.com/reysam93/online_ntf_expanding)| -|[learning short codes for fading channels with no or receiver-only channel state information](https://arxiv.org/abs/2409.08581)|[Learning-Short-Codes-for-Fading-Channels-with-No-or-Receiver-Only-Channel-State-Information](https://github.com/RishP11/Learning-Short-Codes-for-Fading-Channels-with-No-or-Receiver-Only-Channel-State-Information)| +|date|paper|code| +|---|---|---| +|2409.08660|[online learning of expanding graphs](https://arxiv.org/abs/2409.08660)|[online_ntf_expanding](https://github.com/reysam93/online_ntf_expanding)| +|2409.08581|[learning short codes for fading channels with no or receiver-only channel state information](https://arxiv.org/abs/2409.08581)|[Learning-Short-Codes-for-Fading-Channels-with-No-or-Receiver-Only-Channel-State-Information](https://github.com/RishP11/Learning-Short-Codes-for-Fading-Channels-with-No-or-Receiver-Only-Channel-State-Information)| ## 2024-09-13 -|paper|code| -|---|---| -|[dero: dead reckoning based on radar odometry with accelerometers aided for robot localization](https://arxiv.org/abs/2403.05136)|[dero](https://github.com/hoangvietdo/dero)| -|[domain adaptation for doa estimation in multipath channels with interferences](https://arxiv.org/abs/2409.07782)|[domain-adaptation-for-doa-estimation-in-multipath-channels-with-interferences](https://github.com/amitaybar/domain-adaptation-for-doa-estimation-in-multipath-channels-with-interferences)| -|[identification of head impact locations, speeds, and force based on head kinematics](https://arxiv.org/abs/2409.08177)|[impact_retriever](https://github.com/xzhan96-stf/impact_retriever)| +|date|paper|code| +|---|---|---| +|2409.07782|[domain adaptation for doa estimation in multipath channels with interferences](https://arxiv.org/abs/2409.07782)|[domain-adaptation-for-doa-estimation-in-multipath-channels-with-interferences](https://github.com/amitaybar/domain-adaptation-for-doa-estimation-in-multipath-channels-with-interferences)| +|2409.08177|[identification of head impact locations, speeds, and force based on head kinematics](https://arxiv.org/abs/2409.08177)|[impact_retriever](https://github.com/xzhan96-stf/impact_retriever)| ## 2024-09-12 -|paper|code| -|---|---| -|[tinychirp: bird song recognition using tinyml models on low-power wireless acoustic sensors](https://arxiv.org/abs/2407.21453)|[tinychirp](https://github.com/tinypart/tinychirp)| +|date|paper|code| +|---|---|---| ## 2024-09-11 -|paper|code| -|---|---| -|[unlocking the use of raw multispectral earth observation imagery for onboard artificial intelligence](https://arxiv.org/abs/2305.11891)|[pyraws](https://github.com/esa-philab/pyraws)| -|[get-up: geometric-aware depth estimation with radar points upsampling](https://arxiv.org/abs/2409.02720)|[get-up](https://github.com/harborsarah/get-up)| -|[minimax optimal algorithms with fixed-$k$-nearest neighbors](https://arxiv.org/abs/2202.02464)|[split-knn-rules](https://github.com/jongharyu/split-knn-rules)| -|[can large language models learn independent causal mechanisms?](https://arxiv.org/abs/2402.02636)|[modular-lm](https://github.com/strong-ai-lab/modular-lm)| +|date|paper|code| +|---|---|---| +|2409.02720|[get-up: geometric-aware depth estimation with radar points upsampling](https://arxiv.org/abs/2409.02720)|[get-up](https://github.com/harborsarah/get-up)| ## 2024-09-10 -|paper|code| -|---|---| -|[doubly-iterative sparsified mmse turbo equalization for otfs modulation](https://arxiv.org/abs/2207.00866)|[dismmse-turbo-equalizer-for-otfs](https://github.com/alga53/dismmse-turbo-equalizer-for-otfs)| -|[rscnet: dynamic csi compression for cloud-based wifi sensing](https://arxiv.org/abs/2402.04888)|[rscnet](https://github.com/bornabr/rscnet)| -|[feature characterization for profile surface texture](https://arxiv.org/abs/2406.06381)|[feature-characterization-for-profile-surface-texture](https://github.com/mts-public/feature-characterization-for-profile-surface-texture)| -|[indicvoices-r: unlocking a massive multilingual multi-speaker speech corpus for scaling indian tts](https://arxiv.org/abs/2409.05356)|[indicvoices-r](https://github.com/ai4bharat/indicvoices-r)| -|[estimating conditional mutual information for dynamic feature selection](https://arxiv.org/abs/2306.03301)|[dime](https://github.com/suinleelab/dime)| -|[on the computational entanglement of distant features in adversarial machine learning](https://arxiv.org/abs/2309.15669)|[adversary-example-through-relativity](https://github.com/yenlunglai/adversary-example-through-relativity)| -|[adaptive $k$-nearest neighbor classifier based on the local estimation of the shape operator](https://arxiv.org/abs/2409.05084)|[kknn](https://github.com/alexandrelevada/kknn)| -|[tele-llms: a series of specialized large language models for telecommunications](https://arxiv.org/abs/2409.05314)|[tele-llms](https://github.com/ali-maatouk/tele-llms)| +|date|paper|code| +|---|---|---| +|2409.05356|[indicvoices-r: unlocking a massive multilingual multi-speaker speech corpus for scaling indian tts](https://arxiv.org/abs/2409.05356)|[indicvoices-r](https://github.com/ai4bharat/indicvoices-r)| +|2409.05084|[adaptive $k$-nearest neighbor classifier based on the local estimation of the shape operator](https://arxiv.org/abs/2409.05084)|[kknn](https://github.com/alexandrelevada/kknn)| +|2409.05314|[tele-llms: a series of specialized large language models for telecommunications](https://arxiv.org/abs/2409.05314)|[tele-llms](https://github.com/ali-maatouk/tele-llms)| ## 2024-09-09 -|paper|code| -|---|---| -|[topology of surface electromyogram signals: hand gesture decoding on riemannian manifolds](https://arxiv.org/abs/2311.08548)|[geometryofsemg](https://github.com/harshavardhanatg/geometryofsemg)| -|[mixnet: joining force of classical and modern approaches toward the comprehensive pipeline in motor imagery eeg classification](https://arxiv.org/abs/2409.04104)|[mixnet](https://github.com/max-phairot-a/mixnet)| -|[3d-gp-lmvic: learning-based multi-view image coding with 3d gaussian geometric priors](https://arxiv.org/abs/2409.04013)|[3D-GP-LMVIC](https://github.com/YujunHuang063/3D-GP-LMVIC)| +|date|paper|code| +|---|---|---| +|2409.04104|[mixnet: joining force of classical and modern approaches toward the comprehensive pipeline in motor imagery eeg classification](https://arxiv.org/abs/2409.04104)|[mixnet](https://github.com/max-phairot-a/mixnet)| +|2409.04013|[3d-gp-lmvic: learning-based multi-view image coding with 3d gaussian geometric priors](https://arxiv.org/abs/2409.04013)|[3D-GP-LMVIC](https://github.com/YujunHuang063/3D-GP-LMVIC)| ## 2024-09-06 -|paper|code| -|---|---| -|[an efficient frequency diversity scheme for ultra-reliable communications in two-path fading channels](https://arxiv.org/abs/2206.13459)|[two-ray-ultra-reliability](https://github.com/klb2/two-ray-ultra-reliability)| +|date|paper|code| +|---|---|---| ## 2024-09-05 -|paper|code| -|---|---| -|[variational mode decomposition and linear embeddings are what you need for time-series forecasting](https://arxiv.org/abs/2408.16122)|[vmd-with-ltsf-linear](https://github.com/espalemit/vmd-with-ltsf-linear)| -|[quantum state preparation using an exact cnot synthesis formulation](https://arxiv.org/abs/2401.01009)|[quantum-xyz](https://github.com/nozidoali/quantum-xyz)| -|[fadam: adam is a natural gradient optimizer using diagonal empirical fisher information](https://arxiv.org/abs/2405.12807)|[fadam_pytorch](https://github.com/lessw2020/fadam_pytorch)| +|date|paper|code| +|---|---|---| ## 2024-09-04 -|paper|code| -|---|---| -|[opendpd: an open-source end-to-end learning & benchmarking framework for wideband power amplifier modeling and digital pre-distortion](https://arxiv.org/abs/2401.08318)|[opendpd](https://github.com/lab-emi/opendpd)| -|[interpretation of intracardiac electrograms through textual representations](https://arxiv.org/abs/2402.01115)|[text-egm](https://github.com/willxxy/text-egm)| -|[buet multi-disease heart sound dataset: a comprehensive auscultation dataset for developing computer-aided diagnostic systems](https://arxiv.org/abs/2409.00724)|[HS-Dataset](https://github.com/sani002/HS-Dataset)| -|[unsure: unknown noise level stein's unbiased risk estimator](https://arxiv.org/abs/2409.01985)|[unsure](https://github.com/tachella/unsure)| -|[a truly concurrent semantics for reversible ccs](https://arxiv.org/abs/2309.14011)|[reversible-ccs-as-nets](https://github.com/hmelgra/reversible-ccs-as-nets)| -|[entropy loss: an interpretability amplifier of 3d object detection network for intelligent driving](https://arxiv.org/abs/2409.00839)|[Eloss-Interpretability](https://github.com/yhbcode000/Eloss-Interpretability)| +|date|paper|code| +|---|---|---| +|2409.00724|[buet multi-disease heart sound dataset: a comprehensive auscultation dataset for developing computer-aided diagnostic systems](https://arxiv.org/abs/2409.00724)|[HS-Dataset](https://github.com/sani002/HS-Dataset)| +|2409.01985|[unsure: unknown noise level stein's unbiased risk estimator](https://arxiv.org/abs/2409.01985)|[unsure](https://github.com/tachella/unsure)| +|2409.00839|[entropy loss: an interpretability amplifier of 3d object detection network for intelligent driving](https://arxiv.org/abs/2409.00839)|[Eloss-Interpretability](https://github.com/yhbcode000/Eloss-Interpretability)| ## 2024-09-02 -|paper|code| -|---|---| -|[eegmatch: learning with incomplete labels for semi-supervised eeg-based cross-subject emotion recognition](https://arxiv.org/abs/2304.06496)|[eegmatch](https://github.com/kazabana/eegmatch)| -|[multi-timescale ensemble q-learning for markov decision process policy optimization](https://arxiv.org/abs/2402.05476)|[tsp_23_supplementary_file](https://github.com/talhabozkus/tsp_23_supplementary_file)| -|[leveraging digital cousins for ensemble q-learning in large-scale wireless networks](https://arxiv.org/abs/2402.08022)|[digital-cousins-for-ensemble-q-learning](https://github.com/talhabozkus/digital-cousins-for-ensemble-q-learning)| -|[biomedbench: a benchmark suite of tinyml biomedical applications for low-power wearables](https://arxiv.org/abs/2406.03886)|[biomedbench](https://github.com/esl-epfl/biomedbench)| -|[cafnet: a confidence-driven framework for radar camera depth estimation](https://arxiv.org/abs/2407.00697)|[cafnet](https://github.com/harborsarah/cafnet)| -|[mpada: open source framework for multimodal time series antenna array measurements](https://arxiv.org/abs/2408.16850)|[mpada](https://github.com/yuyichang/mpada)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/10.md b/archives/2024/10.md index 02098829..66a9527a 100644 --- a/archives/2024/10.md +++ b/archives/2024/10.md @@ -1,205 +1,117 @@ # October 2024 Archive ## 2024-10-31 -|paper|code| -|---|---| -|[spectral graph pruning against over-squashing and over-smoothing](https://arxiv.org/abs/2404.04612)|[spectralpruningbraess](https://github.com/relationalml/spectralpruningbraess)| -|[spgesture: source-free domain-adaptive semg-based gesture recognition with jaccard attentive spiking neural network](https://arxiv.org/abs/2405.14398)|[spgesture](https://github.com/guoweiyu/spgesture)| -|[unfolding target detection with state space model](https://arxiv.org/abs/2410.22774)|[neurodet](https://github.com/aiot-lab/neurodet)| -|[dynamic threshold-based two-layer online unsupervised anomaly detector](https://arxiv.org/abs/2410.22967)|[adaptive-nad](https://github.com/mylearncodespace/adaptive-nad)| -|[contrastive learning and adversarial disentanglement for privacy-preserving task-oriented semantic communications](https://arxiv.org/abs/2410.22784)|[clad](https://github.com/omarerak/clad)| -|[generalization bounds via conditional $f$-information](https://arxiv.org/abs/2410.22887)|[Conditional-f-Information-Bound](https://github.com/ZiqiaoWangGeothe/Conditional-f-Information-Bound)| +|date|paper|code| +|---|---|---| +|2410.22774|[unfolding target detection with state space model](https://arxiv.org/abs/2410.22774)|[neurodet](https://github.com/aiot-lab/neurodet)| +|2410.22967|[dynamic threshold-based two-layer online unsupervised anomaly detector](https://arxiv.org/abs/2410.22967)|[adaptive-nad](https://github.com/mylearncodespace/adaptive-nad)| +|2410.22784|[contrastive learning and adversarial disentanglement for privacy-preserving task-oriented semantic communications](https://arxiv.org/abs/2410.22784)|[clad](https://github.com/omarerak/clad)| +|2410.22887|[generalization bounds via conditional $f$-information](https://arxiv.org/abs/2410.22887)|[Conditional-f-Information-Bound](https://github.com/ZiqiaoWangGeothe/Conditional-f-Information-Bound)| ## 2024-10-30 -|paper|code| -|---|---| -|[advanced digital signal processing techniques for high-speed optical communications links](https://arxiv.org/abs/1903.12260)|[dsp-library](https://github.com/dario-pilori/dsp-library)| -|[sequential weakly labeled multi-activity localization and recognition on wearable sensors using recurrent attention networks](https://arxiv.org/abs/2004.05768)|[RAN](https://github.com/KennCoder7/RAN)| -|[communication-computation trade-off in resource-constrained edge inference](https://arxiv.org/abs/2006.02166)|[Edge_Inference_three-step_framework](https://github.com/shaojiawei07/Edge_Inference_three-step_framework)| -|[reconfigurable intelligent surface enabled federated learning: a unified communication-learning design approach](https://arxiv.org/abs/2011.10282)|[RIS-FL](https://github.com/liuhang1994/RIS-FL)| -|[eeg-deformer: a dense convolutional transformer for brain-computer interfaces](https://arxiv.org/abs/2405.00719)|[eeg-deformer](https://github.com/yi-ding-cs/eeg-deformer)| -|[a spatial-spectral and temporal dual prototype network for motor imagery brain-computer interface](https://arxiv.org/abs/2407.03177)|[sst-dpn](https://github.com/hancan16/sst-dpn)| -|[dynamical embedding of single channel electroencephalogram for artifact subspace reconstruction](https://arxiv.org/abs/2407.04727)|[e-asr](https://github.com/neurallabiitguwahati/e-asr)| -|[a new framework for nonlinear kalman filters](https://arxiv.org/abs/2407.05717)|[a-new-framework-for-nonlinear-kalman-filters](https://github.com/shida-jiang/a-new-framework-for-nonlinear-kalman-filters)| -|[single-channel electroencephalography decomposition by detector-atom network and its pre-trained model](https://arxiv.org/abs/2408.02185)|[detector-atom-net](https://github.com/hgshrs/detector-atom-net)| -|[an optimal pairwise merge algorithm improves the quality and consistency of nonnegative matrix factorization](https://arxiv.org/abs/2408.09013)|[NMFMerge.jl](https://github.com/HolyLab/NMFMerge.jl)| -|[multiple-beam interference spectroscopy: instrument analysis and spectrum reconstruction](https://arxiv.org/abs/2410.21586)|[inverspyctrometry](https://github.com/mhmdjouni/inverspyctrometry)| -|[pk-yolo: pretrained knowledge guided yolo for brain tumor detection in multiplanar mri slices](https://arxiv.org/abs/2410.21822)|[pk-yolo](https://github.com/mkang315/pk-yolo)| -|[fairness and sum-rate maximization via joint channel and power allocation in uplink scma networks](https://arxiv.org/abs/1805.11722)|[Fairness-and-Sum-Rate-Maximization-via-Joint-Subcarrier-and-Power-Allocation-in-Uplink-SCMA-Transmis](https://github.com/jvce92/Fairness-and-Sum-Rate-Maximization-via-Joint-Subcarrier-and-Power-Allocation-in-Uplink-SCMA-Transmis)| -|[a game-theoretic framework for coexistence of wifi and cellular networks in the 6-ghz unlicensed spectrum](https://arxiv.org/abs/2012.10644)|[coexistence](https://github.com/aniq55/coexistence)| -|[multitok: variable-length tokenization for efficient llms adapted from lzw compression](https://arxiv.org/abs/2410.21548)|[multitok](https://github.com/noelkelias/multitok)| +|date|paper|code| +|---|---|---| +|2410.21586|[multiple-beam interference spectroscopy: instrument analysis and spectrum reconstruction](https://arxiv.org/abs/2410.21586)|[inverspyctrometry](https://github.com/mhmdjouni/inverspyctrometry)| +|2410.21822|[pk-yolo: pretrained knowledge guided yolo for brain tumor detection in multiplanar mri slices](https://arxiv.org/abs/2410.21822)|[pk-yolo](https://github.com/mkang315/pk-yolo)| +|2410.21548|[multitok: variable-length tokenization for efficient llms adapted from lzw compression](https://arxiv.org/abs/2410.21548)|[multitok](https://github.com/noelkelias/multitok)| ## 2024-10-29 -|paper|code| -|---|---| -|[the effect of acute stress on the interpretability and generalization of schizophrenia predictive machine learning models](https://arxiv.org/abs/2410.19739)|[stressschizophrenia](https://github.com/xalentis/stressschizophrenia)| -|[unimts: unified pre-training for motion time series](https://arxiv.org/abs/2410.19818)|[unimts](https://github.com/xiyuanzh/unimts)| -|[automatic classification of sleep stages from eeg signals using riemannian metrics and transformer networks](https://arxiv.org/abs/2410.19819)|[SPDTransNet_plus](https://github.com/MathieuSeraphim/SPDTransNet_plus)| -|[papagei: open foundation models for optical physiological signals](https://arxiv.org/abs/2410.20542)|[papagei-foundation-model](https://github.com/nokia-bell-labs/papagei-foundation-model)| +|date|paper|code| +|---|---|---| +|2410.19739|[the effect of acute stress on the interpretability and generalization of schizophrenia predictive machine learning models](https://arxiv.org/abs/2410.19739)|[stressschizophrenia](https://github.com/xalentis/stressschizophrenia)| +|2410.19818|[unimts: unified pre-training for motion time series](https://arxiv.org/abs/2410.19818)|[unimts](https://github.com/xiyuanzh/unimts)| +|2410.19819|[automatic classification of sleep stages from eeg signals using riemannian metrics and transformer networks](https://arxiv.org/abs/2410.19819)|[SPDTransNet_plus](https://github.com/MathieuSeraphim/SPDTransNet_plus)| +|2410.20542|[papagei: open foundation models for optical physiological signals](https://arxiv.org/abs/2410.20542)|[papagei-foundation-model](https://github.com/nokia-bell-labs/papagei-foundation-model)| ## 2024-10-28 -|paper|code| -|---|---| -|[deep reinforcement learning for urllc data management on top of scheduled embb traffic](https://arxiv.org/abs/2103.01801)|[telerl2021](https://github.com/InsaneMonster/telerl2021)| -|[fbcnet: a multi-view convolutional neural network for brain-computer interface](https://arxiv.org/abs/2104.01233)|[FBCNet](https://github.com/ravikiran-mane/FBCNet)| -|[scalable power control/beamforming in heterogeneous wireless networks with graph neural networks](https://arxiv.org/abs/2104.05463)|[hignn](https://github.com/zhangxiaochen95/hignn)| -|[lggnet: learning from local-global-graph representations for brain-computer interface](https://arxiv.org/abs/2105.02786)|[LGG](https://github.com/yi-ding-cs/LGG)| -|[dilated convolution based csi feedback compression for massive mimo systems](https://arxiv.org/abs/2106.04043)|[DCRNet](https://github.com/recusant7/DCRNet)| -|[multi-modality fusion using canonical correlation analysis methods: application in breast cancer survival prediction from histology and genomics](https://arxiv.org/abs/2111.13987)|[modelling_cca_brca_survival](https://github.com/svaishnavi411/modelling_cca_brca_survival)| -|[accoustate: auto-annotation of imu-generated activity signatures under smart infrastructure](https://arxiv.org/abs/2112.06651)|[acconotate](https://github.com/stilllearningsoumya/acconotate)| -|[deep optimal transport for domain adaptation on spd manifolds](https://arxiv.org/abs/2201.05745)|[deep-optimal-transport-for-domain-adaptation-on-spd-manifolds](https://github.com/geometricbci/deep-optimal-transport-for-domain-adaptation-on-spd-manifolds)| -|[beats: an open-source, high-precision, multi-channel eeg acquisition tool system](https://arxiv.org/abs/2203.02102)|[beats](https://github.com/buptanteeg/beats)| -|[reconfigurable massive mimo: harnessing the power of the electromagnetic domain for enhanced information transfer](https://arxiv.org/abs/2302.11385)|[r-mmimo](https://github.com/kekeyingbit/r-mmimo)| -|[invertible kernel pca with random fourier features](https://arxiv.org/abs/2303.05043)|[invertible_kernel_PCA](https://github.com/dgedon/invertible_kernel_PCA)| -|[a novel channel model for reconfigurable intelligent surfaces with consideration of polarization and switch impairments](https://arxiv.org/abs/2304.03713)|[matlab_ris_channelmodel](https://github.com/icefreeman123/matlab_ris_channelmodel)| -|[maximum likelihood based phase-retrieval using fresnel propagation forward models with optional constraints](https://arxiv.org/abs/2305.00334)|[phasetorch](https://github.com/phasetorch/phasetorch)| -|[a rainbow in deep network black boxes](https://arxiv.org/abs/2305.18512)|[rainbow](https://github.com/florentinguth/rainbow)| -|[graph neural network-enhanced expectation propagation algorithm for mimo turbo receivers](https://arxiv.org/abs/2308.11335)|[GNN-enhanced-EP-for-Turbo-MIMO](https://github.com/STARainZ/GNN-enhanced-EP-for-Turbo-MIMO)| -|[deep learning based modeling of wireless communication channel with fading](https://arxiv.org/abs/2312.06849)|[Deep-Learning-based-Modeling-of-Wireless-Communication-Channel-with-Fading](https://github.com/BrightBlueCheese/Deep-Learning-based-Modeling-of-Wireless-Communication-Channel-with-Fading)| -|[radio map estimation -- an open dataset with directive transmitter antennas and initial experiments](https://arxiv.org/abs/2402.00878)|[rml](https://github.com/fabja19/rml)| -|[graph representation learning for contention and interference management in wireless networks](https://arxiv.org/abs/2402.00879)|[ac-grl-wi-fi](https://github.com/zhouyou-gu/ac-grl-wi-fi)| -|[polyclean: atomic optimization for super-resolution imaging and uncertainty estimation in radio interferometry](https://arxiv.org/abs/2406.01342)|[polyclean](https://github.com/AdriaJ/polyclean)| -|[the multi-cluster fluctuating two-ray fading model](https://arxiv.org/abs/2212.02448)|[mftr-fading-channel-model](https://github.com/josedavidvega/mftr-fading-channel-model)| -|[a spatially non-stationary fading channel model for simulation and (semi-) analytical study of elaa-mimo](https://arxiv.org/abs/2308.13858)|[non-stationary-fading-channel-model](https://github.com/elaa-mimo/non-stationary-fading-channel-model)| -|[treet: transfer entropy estimation via transformer](https://arxiv.org/abs/2402.06919)|[treet](https://github.com/omerlux/treet)| +|date|paper|code| +|---|---|---| ## 2024-10-27 -|paper|code| -|---|---| -|[synaptogen: a cross-domain generative device model for large-scale neuromorphic circuit design](https://arxiv.org/abs/2404.06344)|[synaptogen](https://github.com/thennen/synaptogen)| +|date|paper|code| +|---|---|---| ## 2024-10-25 -|paper|code| -|---|---| -|[approximate message passing with rigorous guarantees for pooled data and quantitative group testing](https://arxiv.org/abs/2309.15507)|[amp_pooled_qgt](https://github.com/pablopasc/amp_pooled_qgt)| -|[ecg semantic integrator (esi): a foundation ecg model pretrained with llm-enhanced cardiological text](https://arxiv.org/abs/2405.19366)|[esi](https://github.com/comp-well-org/esi)| -|[wavetable synthesis using cvae for timbre control based on semantic label](https://arxiv.org/abs/2410.18628)|[wavetablecvae](https://github.com/tsugumasa320/wavetablecvae)| -|[the representation jensen-shannon divergence](https://arxiv.org/abs/2305.16446)|[representationjsd](https://github.com/uk-cliplab/representationjsd)| -|[striking a new chord: neural networks in music information dynamics](https://arxiv.org/abs/2410.17989)|[SeqLab](https://github.com/frshdjfry/SeqLab)| +|date|paper|code| +|---|---|---| +|2410.18628|[wavetable synthesis using cvae for timbre control based on semantic label](https://arxiv.org/abs/2410.18628)|[wavetablecvae](https://github.com/tsugumasa320/wavetablecvae)| +|2410.17989|[striking a new chord: neural networks in music information dynamics](https://arxiv.org/abs/2410.17989)|[SeqLab](https://github.com/frshdjfry/SeqLab)| ## 2024-10-24 -|paper|code| -|---|---| -|[modeling of time-varying wireless communication channel with fading and shadowing](https://arxiv.org/abs/2405.08199)|[Modeling-of-Time-varying-Wireless-Communication-Channel-with-Fading-and-Shadowing](https://github.com/BrightBlueCheese/Modeling-of-Time-varying-Wireless-Communication-Channel-with-Fading-and-Shadowing)| -|[eeg-dif: early warning of epileptic seizures through generative diffusion model-based multi-channel eeg signals forecasting](https://arxiv.org/abs/2410.17343)|[eeg-dif](https://github.com/jzk00/eeg-dif)| +|date|paper|code| +|---|---|---| +|2410.17343|[eeg-dif: early warning of epileptic seizures through generative diffusion model-based multi-channel eeg signals forecasting](https://arxiv.org/abs/2410.17343)|[eeg-dif](https://github.com/jzk00/eeg-dif)| ## 2024-10-23 -|paper|code| -|---|---| -|[evaluating feature attribution methods for electrocardiogram](https://arxiv.org/abs/2211.12702)|[attribution-ecg](https://github.com/snu-drl/attribution-ecg)| -|[emt: a novel transformer for generalized cross-subject eeg emotion recognition](https://arxiv.org/abs/2406.18345)|[emt](https://github.com/yi-ding-cs/emt)| -|[channel shaping using beyond diagonal reconfigurable intelligent surface: analysis, optimization, and enhanced flexibility](https://arxiv.org/abs/2407.15196)|[channel-shaping-using-beyond-diagonal-reconfigurable-intelligent-surface](https://github.com/snowztail/channel-shaping-using-beyond-diagonal-reconfigurable-intelligent-surface)| -|[low-coherence sequence design under papr constraints](https://arxiv.org/abs/2407.21400)|[ieee-wcl-loceda](https://github.com/gangle-sun/ieee-wcl-loceda)| -|[onboard satellite image classification for earth observation: a comparative study of vit models](https://arxiv.org/abs/2409.03901)|[snt-sentry](https://github.com/ltdung/snt-sentry)| -|[delay-constrained grant-free random access in mimo systems: distributed pilot allocation and power control](https://arxiv.org/abs/2410.17068)|[pymarl](https://github.com/oxwhirl/pymarl)| +|date|paper|code| +|---|---|---| +|2410.17068|[delay-constrained grant-free random access in mimo systems: distributed pilot allocation and power control](https://arxiv.org/abs/2410.17068)|[pymarl](https://github.com/oxwhirl/pymarl)| ## 2024-10-22 -|paper|code| -|---|---| -|[conditioning and sampling in variational diffusion models for speech super-resolution](https://arxiv.org/abs/2210.15793)|[diffwave-sr](https://github.com/yoyololicon/diffwave-sr)| -|[uncertainty-aware and reliable neural mimo receivers via modular bayesian deep learning](https://arxiv.org/abs/2302.02436)|[bayesian-learning-in-receivers-for-decoding](https://github.com/tomerraviv95/bayesian-learning-in-receivers-for-decoding)| -|[learning to reconstruct signals from binary measurements](https://arxiv.org/abs/2303.08691)|[ssbm](https://github.com/tachella/ssbm)| -|[apsense: data-driven algorithm in ppg-based sleep apnea sensing](https://arxiv.org/abs/2306.10863)|[apsense](https://github.com/iobt-vistec/apsense)| -|[equivariant bootstrapping for uncertainty quantification in imaging inverse problems](https://arxiv.org/abs/2310.11838)|[equivariant_bootstrap](https://github.com/tachella/equivariant_bootstrap)| -|[experimental analysis of the trc benchmark system](https://arxiv.org/abs/2403.07438)|[](https://github.com/maltekrack/NLtest/blob/main/TESTRIGS/01_TRChallenge/)| -|[improving galileo osnma time to first authenticated fix](https://arxiv.org/abs/2403.14739)|[osnma](https://github.com/algafix/osnma)| -|[time-of-arrival estimation and phase unwrapping of head-related transfer functions with integer linear programming](https://arxiv.org/abs/2405.06804)|[hrtf-ilp](https://github.com/yoyololicon/hrtf-ilp)| -|[medformer: a multi-granularity patching transformer for medical time-series classification](https://arxiv.org/abs/2405.19363)|[medformer](https://github.com/dl4mhealth/medformer)| -|[automatic ai model selection for wireless systems: online learning via digital twinning](https://arxiv.org/abs/2406.15819)|[DT-powered-AMS](https://github.com/qiushuo0913/DT-powered-AMS)| -|[a new framework for nonlinear kalman filters](https://arxiv.org/abs/2407.05717)|[a-new-framework-for-nonlinear-kalman-filters](https://github.com/shida-jiang/a-new-framework-for-nonlinear-kalman-filters)| -|[upper limb surface electromyography -- geometry, spectral characteristics, temporal evolution, and demographic confounds](https://arxiv.org/abs/2409.19939)|[wristEMG](https://github.com/HarshavardhanaTG/wristEMG)| -|[generative artificial intelligence (gai) for mobile communications: a diffusion model perspective](https://arxiv.org/abs/2410.06389)|[gai_comm](https://github.com/xiaoxiaxusummer/gai_comm)| -|[sensorbench: benchmarking llms in coding-based sensor processing](https://arxiv.org/abs/2410.10741)|[llm_sensor_processing](https://github.com/nesl/llm_sensor_processing)| -|[unlocking the full potential of high-density surface emg: novel non-invasive high-yield motor unit decomposition](https://arxiv.org/abs/2410.14800)|[swarm-contrastive-decomposition](https://github.com/AgneGris/swarm-contrastive-decomposition)| -|[deepvigor+: scalable and accurate semi-analytical fault resilience analysis for deep neural network](https://arxiv.org/abs/2410.15742)|[deepvigor](https://github.com/mhahmadilivany/deepvigor)| -|[blind equalization using a variational autoencoder with second order volterra channel model](https://arxiv.org/abs/2410.16125)|[volterra-vae](https://github.com/sfvnielsen/volterra-vae)| -|[diffusion model based posterior sampling for noisy linear inverse problems](https://arxiv.org/abs/2211.12343)|[dmps](https://github.com/mengxiangming/dmps)| -|[attempting the impossible: enumerating extremal submodular functions for n=6](https://arxiv.org/abs/2410.15502)|[submodular-functions-6](https://github.com/csirmaz/submodular-functions-6)| +|date|paper|code| +|---|---|---| +|2410.06389|[generative artificial intelligence (gai) for mobile communications: a diffusion model perspective](https://arxiv.org/abs/2410.06389)|[gai_comm](https://github.com/xiaoxiaxusummer/gai_comm)| +|2410.10741|[sensorbench: benchmarking llms in coding-based sensor processing](https://arxiv.org/abs/2410.10741)|[llm_sensor_processing](https://github.com/nesl/llm_sensor_processing)| +|2410.14800|[unlocking the full potential of high-density surface emg: novel non-invasive high-yield motor unit decomposition](https://arxiv.org/abs/2410.14800)|[swarm-contrastive-decomposition](https://github.com/AgneGris/swarm-contrastive-decomposition)| +|2410.15742|[deepvigor+: scalable and accurate semi-analytical fault resilience analysis for deep neural network](https://arxiv.org/abs/2410.15742)|[deepvigor](https://github.com/mhahmadilivany/deepvigor)| +|2410.16125|[blind equalization using a variational autoencoder with second order volterra channel model](https://arxiv.org/abs/2410.16125)|[volterra-vae](https://github.com/sfvnielsen/volterra-vae)| +|2410.15502|[attempting the impossible: enumerating extremal submodular functions for n=6](https://arxiv.org/abs/2410.15502)|[submodular-functions-6](https://github.com/csirmaz/submodular-functions-6)| ## 2024-10-21 -|paper|code| -|---|---| -|[gabor is enough: interpretable deep denoising with a gabor synthesis dictionary prior](https://arxiv.org/abs/2204.11146)|[cdlnet-ojsp](https://github.com/nikopj/cdlnet-ojsp)| -|[kid-ppg: knowledge informed deep learning for extracting heart rate from a smartwatch](https://arxiv.org/abs/2405.09559)|[KID-PPG](https://github.com/esl-epfl/KID-PPG)| -|[biometric authentication based on enhanced remote photoplethysmography signal morphology](https://arxiv.org/abs/2407.04127)|[rppg_biometrics](https://github.com/zhaodongsun/rppg_biometrics)| -|[convergence of manifold filter-combine networks](https://arxiv.org/abs/2410.14639)|[mfcn](https://github.com/dj408/mfcn)| -|[residual-inr: communication efficient on-device learning using implicit neural representation](https://arxiv.org/abs/2408.05617)|[residual-inr](https://github.com/sharc-lab/residual-inr)| +|date|paper|code| +|---|---|---| +|2410.14639|[convergence of manifold filter-combine networks](https://arxiv.org/abs/2410.14639)|[mfcn](https://github.com/dj408/mfcn)| ## 2024-10-16 -|paper|code| -|---|---| -|[mobile edge generation-enabled digital twin: architecture design and research opportunities](https://arxiv.org/abs/2407.02804)|[meg_dt](https://github.com/xiaoxiaxusummer/meg_dt)| -|[channel charting-based channel prediction on real-world distributed massive mimo csi](https://arxiv.org/abs/2410.11486)|[channelcharting-channelprediction](https://github.com/phillipstephan/channelcharting-channelprediction)| -|[null models for comparing information decomposition across complex systems](https://arxiv.org/abs/2410.11583)|[numit](https://github.com/alberto-liardi/numit)| +|date|paper|code| +|---|---|---| +|2410.11486|[channel charting-based channel prediction on real-world distributed massive mimo csi](https://arxiv.org/abs/2410.11486)|[channelcharting-channelprediction](https://github.com/phillipstephan/channelcharting-channelprediction)| +|2410.11583|[null models for comparing information decomposition across complex systems](https://arxiv.org/abs/2410.11583)|[numit](https://github.com/alberto-liardi/numit)| ## 2024-10-15 -|paper|code| -|---|---| -|[principled pruning of bayesian neural networks through variational free energy minimization](https://arxiv.org/abs/2210.09134)|[principledpruningbnn](https://github.com/biaslab/principledpruningbnn)| -|[bgf-yolo: enhanced yolov8 with multiscale attentional feature fusion for brain tumor detection](https://arxiv.org/abs/2309.12585)|[bgf-yolo](https://github.com/mkang315/bgf-yolo)| -|[temporal action localization for inertial-based human activity recognition](https://arxiv.org/abs/2311.15831)|[tal_for_har](https://github.com/mariusbock/tal_for_har)| -|[exploring new territory: calibration-free decoding for c-vep bci](https://arxiv.org/abs/2403.15521)|[pyntbci](https://github.com/thijor/pyntbci)| -|[channel correlation matrix extrapolation based on roughness calibration of scatterers](https://arxiv.org/abs/2409.10900)|[CCM-Extrapolation](https://github.com/zhanghl24/CCM-Extrapolation)| -|[nirvawave: an accurate and efficient near field wave propagation simulator for 6g and beyond](https://arxiv.org/abs/2409.11293)|[nirvawave](https://github.com/vahidyazdnian1378/nirvawave)| -|[orthogonal nonnegative matrix factorization with the kullback-leibler divergence](https://arxiv.org/abs/2410.07786)|[kl-onmf](https://gitlab.com/ngillis/kl-onmf)| -|[multimodal physical activity forecasting in free-living clinical settings: hunting opportunities for just-in-time interventions](https://arxiv.org/abs/2410.09643)|[movesense](https://github.com/ab9mamun/movesense)| -|[wand: wavelet analysis-based neural decomposition of mrs signals for artifact removal](https://arxiv.org/abs/2410.10427)|[wand-for-mrs](https://github.com/julianmer/wand-for-mrs)| -|[sensorbench: benchmarking llms in coding-based sensor processing](https://arxiv.org/abs/2410.10741)|[llm_sensor_processing](https://github.com/nesl/llm_sensor_processing)| -|[cone-restricted information theory](https://arxiv.org/abs/2206.04300)|[conerestrictedinformationtheory](https://github.com/chitambarlab/conerestrictedinformationtheory)| -|[diff-erank: a novel rank-based metric for evaluating large language models](https://arxiv.org/abs/2401.17139)|[Diff-eRank](https://github.com/waltonfuture/Diff-eRank)| -|[generalized measures of anticipation and responsivity in online language processing](https://arxiv.org/abs/2409.10728)|[generalized-surprisal](https://github.com/rycolab/generalized-surprisal)| -|[a deep learning based decoder for concatenated coding over deletion channels](https://arxiv.org/abs/2410.09460)|[DNN-for-Deletion-Channel](https://github.com/Bilkent-CTAR-Lab/DNN-for-Deletion-Channel)| +|date|paper|code| +|---|---|---| +|2410.07786|[orthogonal nonnegative matrix factorization with the kullback-leibler divergence](https://arxiv.org/abs/2410.07786)|[kl-onmf](https://gitlab.com/ngillis/kl-onmf)| +|2410.09643|[multimodal physical activity forecasting in free-living clinical settings: hunting opportunities for just-in-time interventions](https://arxiv.org/abs/2410.09643)|[movesense](https://github.com/ab9mamun/movesense)| +|2410.10427|[wand: wavelet analysis-based neural decomposition of mrs signals for artifact removal](https://arxiv.org/abs/2410.10427)|[wand-for-mrs](https://github.com/julianmer/wand-for-mrs)| +|2410.10741|[sensorbench: benchmarking llms in coding-based sensor processing](https://arxiv.org/abs/2410.10741)|[llm_sensor_processing](https://github.com/nesl/llm_sensor_processing)| +|2410.09460|[a deep learning based decoder for concatenated coding over deletion channels](https://arxiv.org/abs/2410.09460)|[DNN-for-Deletion-Channel](https://github.com/Bilkent-CTAR-Lab/DNN-for-Deletion-Channel)| ## 2024-10-14 -|paper|code| -|---|---| -|[brainib: interpretable brain network-based psychiatric diagnosis with graph information bottleneck](https://arxiv.org/abs/2205.03612)|[brain-and-information-bottleneck](https://github.com/sjyucnel/brain-and-information-bottleneck)| -|[biomedbench: a benchmark suite of tinyml biomedical applications for low-power wearables](https://arxiv.org/abs/2406.03886)|[biomedbench](https://github.com/esl-epfl/biomedbench)| -|[physics and deep learning in computational wave imaging](https://arxiv.org/abs/2410.08329)|[ML-NDT](https://github.com/iikka-v/ML-NDT)| -|[radarode-mtl: a multi-task learning framework with eccentric gradient alignment for robust radar-based ecg reconstruction](https://arxiv.org/abs/2410.08656)|[radarODE-MTL](https://github.com/ZYY0844/radarODE-MTL)| -|[information-theoretic measures on lattices for high-order interactions](https://arxiv.org/abs/2408.07533)|[nips2024hoi](https://github.com/neurips2024hoi/nips2024hoi)| +|date|paper|code| +|---|---|---| +|2410.08329|[physics and deep learning in computational wave imaging](https://arxiv.org/abs/2410.08329)|[ML-NDT](https://github.com/iikka-v/ML-NDT)| +|2410.08656|[radarode-mtl: a multi-task learning framework with eccentric gradient alignment for robust radar-based ecg reconstruction](https://arxiv.org/abs/2410.08656)|[radarODE-MTL](https://github.com/ZYY0844/radarODE-MTL)| ## 2024-10-11 -|paper|code| -|---|---| -|[eegunity: open-source tool in facilitating unified eeg datasets towards large-scale eeg model](https://arxiv.org/abs/2410.07196)|[eegunity](https://github.com/baizhige/eegunity)| -|[rfboost: understanding and boosting deep wifi sensing via physical data augmentation](https://arxiv.org/abs/2410.07230)|[rfboost](https://github.com/aiot-lab/rfboost)| -|[localized adaptive risk control](https://arxiv.org/abs/2405.07976)|[localized-adaptive-risk-control](https://github.com/kclip/localized-adaptive-risk-control)| -|[almost minimax optimal best arm identification in piecewise stationary linear bandits](https://arxiv.org/abs/2410.07638)|[BAI-in-PSLB](https://github.com/Y-Hou/BAI-in-PSLB)| +|date|paper|code| +|---|---|---| +|2410.07196|[eegunity: open-source tool in facilitating unified eeg datasets towards large-scale eeg model](https://arxiv.org/abs/2410.07196)|[eegunity](https://github.com/baizhige/eegunity)| +|2410.07230|[rfboost: understanding and boosting deep wifi sensing via physical data augmentation](https://arxiv.org/abs/2410.07230)|[rfboost](https://github.com/aiot-lab/rfboost)| +|2410.07638|[almost minimax optimal best arm identification in piecewise stationary linear bandits](https://arxiv.org/abs/2410.07638)|[BAI-in-PSLB](https://github.com/Y-Hou/BAI-in-PSLB)| ## 2024-10-10 -|paper|code| -|---|---| -|[kid-ppg: knowledge informed deep learning for extracting heart rate from a smartwatch](https://arxiv.org/abs/2405.09559)|[KID-PPG](https://github.com/esl-epfl/KID-PPG)| -|[trustemg-net: using representation-masking transformer with u-net for surface electromyography enhancement](https://arxiv.org/abs/2410.03843)|[TrustEMG](https://github.com/eric-wang135/TrustEMG)| -|[episodic fine-tuning prototypical networks for optimization-based few-shot learning: application to audio classification](https://arxiv.org/abs/2410.05302)|[proto-MAML](https://github.com/zdsy/proto-MAML)| -|[closed-loop phase selection in eeg-tms using bayesian optimization](https://arxiv.org/abs/2410.05747)|[BO_for_EEG-TMS_phase](https://github.com/MiriamKirchhoff/BO_for_EEG-TMS_phase)| -|[message-passing on hypergraphs: detectability, phase transitions and higher-order information](https://arxiv.org/abs/2312.00708)|[hypergraph-message-passing](https://github.com/nickruggeri/hypergraph-message-passing)| -|[accelerating error correction code transformers](https://arxiv.org/abs/2410.05911)|[aecct](https://github.com/mlaetvayn/aecct)| +|date|paper|code| +|---|---|---| +|2410.03843|[trustemg-net: using representation-masking transformer with u-net for surface electromyography enhancement](https://arxiv.org/abs/2410.03843)|[TrustEMG](https://github.com/eric-wang135/TrustEMG)| +|2410.05302|[episodic fine-tuning prototypical networks for optimization-based few-shot learning: application to audio classification](https://arxiv.org/abs/2410.05302)|[proto-MAML](https://github.com/zdsy/proto-MAML)| +|2410.05747|[closed-loop phase selection in eeg-tms using bayesian optimization](https://arxiv.org/abs/2410.05747)|[BO_for_EEG-TMS_phase](https://github.com/MiriamKirchhoff/BO_for_EEG-TMS_phase)| +|2410.05911|[accelerating error correction code transformers](https://arxiv.org/abs/2410.05911)|[aecct](https://github.com/mlaetvayn/aecct)| ## 2024-10-08 -|paper|code| -|---|---| -|[fast variational block-sparse bayesian learning](https://arxiv.org/abs/2306.00442)|[fast-variational-block-sparse-bayesian-learning](https://gitlab.com/jmoederl/fast-variational-block-sparse-bayesian-learning)| -|[cst-yolo: a novel method for blood cell detection based on improved yolov7 and cnn-swin transformer](https://arxiv.org/abs/2306.14590)|[CST-YOLO](https://github.com/mkang315/CST-YOLO)| -|[sparse learned kernels for interpretable and efficient medical time series processing](https://arxiv.org/abs/2307.05385)|[smolk](https://github.com/sullychen/smolk)| -|[real-time eeg-based emotion recognition model using principal component analysis and tree-based models for neurohumanities](https://arxiv.org/abs/2401.15743)|[neurohumanities-lab](https://github.com/miltoncandela/neurohumanities-lab)| -|[indicvoices-r: unlocking a massive multilingual multi-speaker speech corpus for scaling indian tts](https://arxiv.org/abs/2409.05356)|[indicvoices-r](https://github.com/ai4bharat/indicvoices-r)| -|[widistill: distilling large-scale wi-fi datasets with trajectory matching](https://arxiv.org/abs/2410.04073)|[widistill](https://github.com/the-sky001/widistill)| -|[large-scale gnss spreading code optimization](https://arxiv.org/abs/2410.04653)|[decor](https://github.com/Stanford-NavLab/decor)| +|date|paper|code| +|---|---|---| +|2410.04073|[widistill: distilling large-scale wi-fi datasets with trajectory matching](https://arxiv.org/abs/2410.04073)|[widistill](https://github.com/the-sky001/widistill)| +|2410.04653|[large-scale gnss spreading code optimization](https://arxiv.org/abs/2410.04653)|[decor](https://github.com/Stanford-NavLab/decor)| ## 2024-10-07 -|paper|code| -|---|---| -|[visual decoding and reconstruction via eeg embeddings with guided diffusion](https://arxiv.org/abs/2403.07721)|[eeg_image_decode](https://github.com/ncclab-sustech/eeg_image_decode)| -|[manikin-recorded cardiopulmonary sounds dataset using digital stethoscope](https://arxiv.org/abs/2410.03280)|[hls-cmds](https://github.com/torabiy/hls-cmds)| -|[an ebpf-based trace-driven emulation method for satellite networks](https://arxiv.org/abs/2408.15581)|[ebpf-trace-emu](https://github.com/yeliqseu/ebpf-trace-emu)| -|[receptors cluster in high-curvature membrane regions for optimal spatial gradient sensing](https://arxiv.org/abs/2410.03395)|[recloc](https://github.com/kirkegaardlab/recloc)| +|date|paper|code| +|---|---|---| +|2410.03280|[manikin-recorded cardiopulmonary sounds dataset using digital stethoscope](https://arxiv.org/abs/2410.03280)|[hls-cmds](https://github.com/torabiy/hls-cmds)| +|2410.03395|[receptors cluster in high-curvature membrane regions for optimal spatial gradient sensing](https://arxiv.org/abs/2410.03395)|[recloc](https://github.com/kirkegaardlab/recloc)| ## 2024-10-04 -|paper|code| -|---|---| -|[algorithms for non-negative matrix factorization on noisy data with negative values](https://arxiv.org/abs/2311.04855)|[nearly_nmf](https://github.com/dylanagreen/nearly_nmf)| -|[multi-channel masked autoencoder and comprehensive evaluations for reconstructing 12-lead ecg from arbitrary single-lead ecg](https://arxiv.org/abs/2407.11481)|[mcma](https://github.com/chenjiar3/mcma)| -|[capturing complex hand movements and object interactions using machine learning-powered stretchable smart textile gloves](https://arxiv.org/abs/2410.02221)|[SmartTextileGlove](https://github.com/arvintashakori/SmartTextileGlove)| +|date|paper|code| +|---|---|---| +|2410.02221|[capturing complex hand movements and object interactions using machine learning-powered stretchable smart textile gloves](https://arxiv.org/abs/2410.02221)|[SmartTextileGlove](https://github.com/arvintashakori/SmartTextileGlove)| diff --git a/archives/2024/11.md b/archives/2024/11.md index 329258d0..f06089c5 100644 --- a/archives/2024/11.md +++ b/archives/2024/11.md @@ -1,178 +1,117 @@ # November 2024 Archive ## 2024-11-28 -|paper|code| -|---|---| -|[over-the-air learning-based geometry point cloud transmission](https://arxiv.org/abs/2306.08730)|[SEPT](https://github.com/aprilbian/SEPT)| -|[calibrated adaptive teacher for domain adaptive intelligent fault diagnosis](https://arxiv.org/abs/2312.02826)|[cat](https://github.com/epfl-imos/cat)| -|[biometric authentication based on enhanced remote photoplethysmography signal morphology](https://arxiv.org/abs/2407.04127)|[rppg_biometrics](https://github.com/zhaodongsun/rppg_biometrics)| -|[swim: short-window cnn integrated with mamba for eeg-based auditory spatial attention decoding](https://arxiv.org/abs/2409.19884)|[swim-asad](https://github.com/windowso/swim-asad)| -|[finding "good views" of electrocardiogram signals for inferring abnormalities in cardiac condition](https://arxiv.org/abs/2411.17702)|[goodviews_ecg](https://github.com/mandiehyewon/goodviews_ecg)| -|[analytic continuation by feature learning](https://arxiv.org/abs/2411.17728)|[Analytic-Continuation-by-Feature-Learning](https://github.com/Order-inz/Analytic-Continuation-by-Feature-Learning)| -|[the more, the better? evaluating the role of eeg preprocessing for deep learning applications](https://arxiv.org/abs/2411.18392)|[eegprepro](https://github.com/medmaxlab/eegprepro)| -|[surveying the space of descriptions of a composite system with machine learning](https://arxiv.org/abs/2411.18579)|[description_space](https://github.com/murphyka/description_space)| +|date|paper|code| +|---|---|---| +|2411.17702|[finding "good views" of electrocardiogram signals for inferring abnormalities in cardiac condition](https://arxiv.org/abs/2411.17702)|[goodviews_ecg](https://github.com/mandiehyewon/goodviews_ecg)| +|2411.17728|[analytic continuation by feature learning](https://arxiv.org/abs/2411.17728)|[Analytic-Continuation-by-Feature-Learning](https://github.com/Order-inz/Analytic-Continuation-by-Feature-Learning)| +|2411.18392|[the more, the better? evaluating the role of eeg preprocessing for deep learning applications](https://arxiv.org/abs/2411.18392)|[eegprepro](https://github.com/medmaxlab/eegprepro)| +|2411.18579|[surveying the space of descriptions of a composite system with machine learning](https://arxiv.org/abs/2411.18579)|[description_space](https://github.com/murphyka/description_space)| ## 2024-11-27 -|paper|code| -|---|---| -|[bayesian kalmannet: quantifying uncertainty in deep learning augmented kalman filter](https://arxiv.org/abs/2309.03058)|[Uncertainty-extraction-in-Model-Based-DL](https://github.com/yonatandn/Uncertainty-extraction-in-Model-Based-DL)| -|[robust bayesian optimization via localized online conformal prediction](https://arxiv.org/abs/2411.17387)|[LOCBO](https://github.com/davinci003/LOCBO)| -|[fast and robust phase retrieval via deep expectation-consistent approximation](https://arxiv.org/abs/2407.09687)|[deepECpr](https://github.com/Saurav-K-Shastri/deepECpr)| +|date|paper|code| +|---|---|---| +|2411.17387|[robust bayesian optimization via localized online conformal prediction](https://arxiv.org/abs/2411.17387)|[LOCBO](https://github.com/davinci003/LOCBO)| ## 2024-11-26 -|paper|code| -|---|---| -|[efficient wireless federated learning via low-rank gradient factorization](https://arxiv.org/abs/2401.07496)|[ota-lc](https://github.com/mingzhaoguo/ota-lc)| -|[robust beamforming for ris-aided communications: gradient-based manifold meta learning](https://arxiv.org/abs/2402.10626)|[GMML](https://github.com/fenghaozhu/GMML)| -|[dero: dead reckoning based on radar odometry with accelerometers aided for robot localization](https://arxiv.org/abs/2403.05136)|[dero](https://github.com/hoangvietdo/dero)| -|[robust beamforming with gradient-based liquid neural network](https://arxiv.org/abs/2405.07291)|[GLNN](https://github.com/tp1000d/GLNN)| -|[mecg-e: mamba-based ecg enhancer for baseline wander removal](https://arxiv.org/abs/2409.18828)|[MECG-E](https://github.com/khhungg/MECG-E)| -|[robust hybrid precoding for millimeter wave mu-miso system via meta-learning](https://arxiv.org/abs/2411.15762)|[ggml](https://github.com/mistybeep/ggml)| -|[multi-sources information fusion learning for multi-points nlos localization](https://arxiv.org/abs/2401.12538)|[AMDNloc](https://github.com/Horizontal666/AMDNloc)| -|[learning personalized treatment decisions in precision medicine: disentangling treatment assignment bias in counterfactual outcome prediction and biomarker identification](https://arxiv.org/abs/2410.00509)|[selection-bias-benchmark](https://github.com/michavol/selection-bias-benchmark)| -|[run-length-limited isi-mitigation (rlim) coding for molecular communication](https://arxiv.org/abs/2411.15955)|[mcchannelcoding](https://github.com/melihsahinedu/mcchannelcoding)| +|date|paper|code| +|---|---|---| +|2411.15762|[robust hybrid precoding for millimeter wave mu-miso system via meta-learning](https://arxiv.org/abs/2411.15762)|[ggml](https://github.com/mistybeep/ggml)| +|2411.15955|[run-length-limited isi-mitigation (rlim) coding for molecular communication](https://arxiv.org/abs/2411.15955)|[mcchannelcoding](https://github.com/melihsahinedu/mcchannelcoding)| ## 2024-11-25 -|paper|code| -|---|---| -|[scalable-complexity steered response power mapping based on low-rank and sparse interpolation](https://arxiv.org/abs/2306.08514)|[lr-sp-int-srp](https://github.com/tdietzen/lr-sp-int-srp)| -|[understanding generalizability of diffusion models requires rethinking the hidden gaussian structure](https://arxiv.org/abs/2410.24060)|[Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure](https://github.com/Morefre/Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure)| -|[multipath mitigation technology-integrated gnss direct position estimation plug-in module](https://arxiv.org/abs/2411.13339)|[GPSL1-MMT-DPEmodule](https://github.com/Sergio-Vicenzo/GPSL1-MMT-DPEmodule)| -|[scalable wavelength arbitration for microring-based dwdm transceivers](https://arxiv.org/abs/2411.14810)|[wdm-simulator](https://github.com/wdmsim/wdm-simulator)| -|[cardiolab: laboratory values estimation and monitoring from electrocardiogram signals -- a multimodal deep learning approach](https://arxiv.org/abs/2411.14886)|[cardiolab](https://github.com/ai4healthuol/cardiolab)| -|[resolution-adaptive micro-doppler spectrogram for human activity recognition](https://arxiv.org/abs/2411.15057)|[resolution-adaptive-spectrogram](https://github.com/signal-park/resolution-adaptive-spectrogram)| +|date|paper|code| +|---|---|---| +|2411.13339|[multipath mitigation technology-integrated gnss direct position estimation plug-in module](https://arxiv.org/abs/2411.13339)|[GPSL1-MMT-DPEmodule](https://github.com/Sergio-Vicenzo/GPSL1-MMT-DPEmodule)| +|2411.14810|[scalable wavelength arbitration for microring-based dwdm transceivers](https://arxiv.org/abs/2411.14810)|[wdm-simulator](https://github.com/wdmsim/wdm-simulator)| +|2411.14886|[cardiolab: laboratory values estimation and monitoring from electrocardiogram signals -- a multimodal deep learning approach](https://arxiv.org/abs/2411.14886)|[cardiolab](https://github.com/ai4healthuol/cardiolab)| +|2411.15057|[resolution-adaptive micro-doppler spectrogram for human activity recognition](https://arxiv.org/abs/2411.15057)|[resolution-adaptive-spectrogram](https://github.com/signal-park/resolution-adaptive-spectrogram)| ## 2024-11-22 -|paper|code| -|---|---| -|[towards generative ray path sampling for faster point-to-point ray tracing](https://arxiv.org/abs/2410.23773)|[DiffeRT](https://github.com/jeertmans/DiffeRT)| -|[gramep: an alignment-free method based on the maximum entropy principle for identifying snps](https://arxiv.org/abs/2405.01715)|[gramep](https://github.com/omatheuspimenta/gramep)| -|[iterative decoding of short bch codes and its post-processing](https://arxiv.org/abs/2411.13876)|[Short_BCH_Decoding_OSD](https://github.com/lgw-frank/Short_BCH_Decoding_OSD)| +|date|paper|code| +|---|---|---| +|2411.13876|[iterative decoding of short bch codes and its post-processing](https://arxiv.org/abs/2411.13876)|[Short_BCH_Decoding_OSD](https://github.com/lgw-frank/Short_BCH_Decoding_OSD)| ## 2024-11-21 -|paper|code| -|---|---| -|[enhanced cross-dataset electroencephalogram-based emotion recognition using unsupervised domain adaptation](https://arxiv.org/abs/2411.12852)|[emotionrecognitionuda](https://github.com/ryersonmultimedialab/emotionrecognitionuda)| +|date|paper|code| +|---|---|---| +|2411.12852|[enhanced cross-dataset electroencephalogram-based emotion recognition using unsupervised domain adaptation](https://arxiv.org/abs/2411.12852)|[emotionrecognitionuda](https://github.com/ryersonmultimedialab/emotionrecognitionuda)| ## 2024-11-20 -|paper|code| -|---|---| -|[freezing of gait detection using gramian angular fields and federated learning from wearable sensors](https://arxiv.org/abs/2411.11764)|[fogsense](https://github.com/shovito66/fogsense)| +|date|paper|code| +|---|---|---| +|2411.11764|[freezing of gait detection using gramian angular fields and federated learning from wearable sensors](https://arxiv.org/abs/2411.11764)|[fogsense](https://github.com/shovito66/fogsense)| ## 2024-11-19 -|paper|code| -|---|---| -|[b-har: an open-source baseline framework for in depth study of human activity recognition datasets and workflows](https://arxiv.org/abs/2101.10870)|[B-HAR](https://github.com/B-HAR-HumanActivityRecognition/B-HAR)| -|[arnn: attentive recurrent neural network for multi-channel eeg signals to identify epileptic seizures](https://arxiv.org/abs/2403.03276)|[arnn](https://github.com/salim-lysiun/arnn)| -|[lightcode: light analytical and neural codes for channels with feedback](https://arxiv.org/abs/2403.10751)|[lightcode](https://github.com/sravan-ankireddy/lightcode)| +|date|paper|code| +|---|---|---| ## 2024-11-18 -|paper|code| -|---|---| -|[boosted neural decoders: achieving extreme reliability of ldpc codes for 6g networks](https://arxiv.org/abs/2405.13413)|[ldpc_error_floor](https://github.com/ghy1228/ldpc_error_floor)| -|[a hybrid artificial intelligence system for automated eeg background analysis and report generation](https://arxiv.org/abs/2411.09874)|[ai_eeeg_report](https://github.com/tcs211/ai_eeeg_report)| +|date|paper|code| +|---|---|---| +|2411.09874|[a hybrid artificial intelligence system for automated eeg background analysis and report generation](https://arxiv.org/abs/2411.09874)|[ai_eeeg_report](https://github.com/tcs211/ai_eeeg_report)| ## 2024-11-15 -|paper|code| -|---|---| -|[single-channel electroencephalography decomposition by detector-atom network and its pre-trained model](https://arxiv.org/abs/2408.02185)|[detector-atom-net](https://github.com/hgshrs/detector-atom-net)| -|[outsourcing control requires control complexity](https://arxiv.org/abs/2209.01418)|[learningrequiresintinf](https://github.com/carlottalanger/learningrequiresintinf)| -|[information-driven design of imaging systems](https://arxiv.org/abs/2405.20559)|[encodinginformation](https://github.com/waller-lab/encodinginformation)| +|date|paper|code| +|---|---|---| ## 2024-11-14 -|paper|code| -|---|---| -|[optimal vintage factor analysis with deflation varimax](https://arxiv.org/abs/2310.10545)|[optimal_deflation_varimax](https://github.com/jindiande/optimal_deflation_varimax)| -|[gradient networks](https://arxiv.org/abs/2404.07361)|[gradientnetworks](https://github.com/spronav/gradientnetworks)| -|[a deep automotive radar detector using the radelft dataset](https://arxiv.org/abs/2406.04723)|[RaDelft-Dataset](https://github.com/RaDelft/RaDelft-Dataset)| -|[inferring directed spectral information flow between mixed-frequency time series](https://arxiv.org/abs/2408.06109)|[mf-tfcca](https://github.com/qiqixian/mf-tfcca)| -|[large wireless model (lwm): a foundation model for wireless channels](https://arxiv.org/abs/2411.08872)|[lwm](https://huggingface.co/wi-lab/lwm)| -|[explainable enrichment-driven graph reasoner (edgar) for large knowledge graphs with applications in drug repurposing](https://arxiv.org/abs/2409.18659)|[edgar](https://github.com/ranking-agent/edgar)| -|[variable-length feedback codes via deep learning](https://arxiv.org/abs/2411.08481)|[DeepVLF](https://github.com/lynshao/DeepVLF)| +|date|paper|code| +|---|---|---| +|2411.08872|[large wireless model (lwm): a foundation model for wireless channels](https://arxiv.org/abs/2411.08872)|[lwm](https://huggingface.co/wi-lab/lwm)| +|2411.08481|[variable-length feedback codes via deep learning](https://arxiv.org/abs/2411.08481)|[DeepVLF](https://github.com/lynshao/DeepVLF)| ## 2024-11-13 -|paper|code| -|---|---| -|[physics-enhanced graph neural networks for soft sensing in industrial internet of things](https://arxiv.org/abs/2404.08061)|[PEGNN_SS](https://github.com/EPFL-IMOS/PEGNN_SS)| -|[soundsil-ds: deep denoising and segmentation of sound-field images with silhouettes](https://arxiv.org/abs/2411.07517)|[soundsil-ds](https://github.com/nttcslab/soundsil-ds)| -|[model reconstruction using counterfactual explanations: a perspective from polytope theory](https://arxiv.org/abs/2405.05369)|[model-reconstruction-using-counterfactuals](https://github.com/pasandissanayake/model-reconstruction-using-counterfactuals)| +|date|paper|code| +|---|---|---| +|2411.07517|[soundsil-ds: deep denoising and segmentation of sound-field images with silhouettes](https://arxiv.org/abs/2411.07517)|[soundsil-ds](https://github.com/nttcslab/soundsil-ds)| ## 2024-11-12 -|paper|code| -|---|---| -|[deep riemannian networks for end-to-end eeg decoding](https://arxiv.org/abs/2212.10426)|[eegspdnet](https://github.com/dcwil/eegspdnet)| -|[orchestration framework for open system models with autonomous riss and oblivious base stations](https://arxiv.org/abs/2304.10858)|[self-configuring-orchestration](https://github.com/victorcroisfelt/self-configuring-orchestration)| -|[mutual information estimation via $f$-divergence and data derangements](https://arxiv.org/abs/2305.20025)|[fdime](https://github.com/tonellolab/fdime)| -|[magnetic hysteresis modeling with neural operators](https://arxiv.org/abs/2407.03261)|[magnetic_hysteresis_neural_operator](https://github.com/chandratue/magnetic_hysteresis_neural_operator)| -|[fitting multiple machine learning models with performance based clustering](https://arxiv.org/abs/2411.06572)|[function-clustering](https://github.com/mefe06/function-clustering)| -|[deepcrf: deep learning-enhanced csi-based rf fingerprinting for channel-resilient wifi device identification](https://arxiv.org/abs/2411.06925)|[DeepCRF_TIFS](https://github.com/Oriseven/DeepCRF_TIFS)| -|[ultra-marginal feature importance: learning from data with causal guarantees](https://arxiv.org/abs/2204.09938)|[umfi](https://github.com/hydroml/umfi)| -|[universal exact compression of differentially private mechanisms](https://arxiv.org/abs/2405.20782)|[poissonprivaterepr](https://github.com/cheuktingli/poissonprivaterepr)| -|[understanding the role of equivariance in self-supervised learning](https://arxiv.org/abs/2411.06508)|[understanding-essl](https://github.com/kaotty/understanding-essl)| +|date|paper|code| +|---|---|---| +|2411.06572|[fitting multiple machine learning models with performance based clustering](https://arxiv.org/abs/2411.06572)|[function-clustering](https://github.com/mefe06/function-clustering)| +|2411.06925|[deepcrf: deep learning-enhanced csi-based rf fingerprinting for channel-resilient wifi device identification](https://arxiv.org/abs/2411.06925)|[DeepCRF_TIFS](https://github.com/Oriseven/DeepCRF_TIFS)| +|2411.06508|[understanding the role of equivariance in self-supervised learning](https://arxiv.org/abs/2411.06508)|[understanding-essl](https://github.com/kaotty/understanding-essl)| ## 2024-11-11 -|paper|code| -|---|---| -|[pan-tompkins++: a robust approach to detect r-peaks in ecg signals](https://arxiv.org/abs/2211.03171)|[Pan-Tompkins-Plus-Plus](https://github.com/Niaz-Imtiaz/Pan-Tompkins-Plus-Plus)| -|[unmasking the role of remote sensors in comfort, energy and demand response](https://arxiv.org/abs/2404.15368)|[sensors4singlezonesystems](https://github.com/inferlab/sensors4singlezonesystems)| -|[csi-gpt: integrating generative pre-trained transformer with federated-tuning to acquire downlink massive mimo channels](https://arxiv.org/abs/2406.03438)|[csi-gpt](https://github.com/bit-zy/csi-gpt)| -|[exploiting the structure of two graphs with graph neural networks](https://arxiv.org/abs/2411.05119)|[io-gnn](https://github.com/vmtenorio/io-gnn)| -|[zipnn: lossless compression for ai models](https://arxiv.org/abs/2411.05239)|[zipnn](https://github.com/zipnn/zipnn)| +|date|paper|code| +|---|---|---| +|2411.05119|[exploiting the structure of two graphs with graph neural networks](https://arxiv.org/abs/2411.05119)|[io-gnn](https://github.com/vmtenorio/io-gnn)| +|2411.05239|[zipnn: lossless compression for ai models](https://arxiv.org/abs/2411.05239)|[zipnn](https://github.com/zipnn/zipnn)| ## 2024-11-08 -|paper|code| -|---|---| -|[robust low-cost drone detection and classification in low snr environments](https://arxiv.org/abs/2406.18624)|[noisy-drone-rf-signal-classification-v2](https://github.com/sgluege/noisy-drone-rf-signal-classification-v2)| -|[a new framework for nonlinear kalman filters](https://arxiv.org/abs/2407.05717)|[a-new-framework-for-nonlinear-kalman-filters](https://github.com/shida-jiang/a-new-framework-for-nonlinear-kalman-filters)| -|[advancing free-space optical communication system architecture: performance analysis of varied optical ground station network configurations](https://arxiv.org/abs/2410.23470)|[fso-simulation](https://github.com/connor-a-casey/fso-simulation)| -|[higher-order gnns meet efficiency: sparse sobolev graph neural networks](https://arxiv.org/abs/2411.04570)|[S2-GNN](https://github.com/jhonygiraldo/S2-GNN)| -|[semantic-aware resource management for c-v2x platooning via multi-agent reinforcement learning](https://arxiv.org/abs/2411.04672)|[semantic-aware-resource-management-for-c-v2x-platooning-via-multi-agent-reinforcement-learning](https://github.com/qiongwu86/semantic-aware-resource-management-for-c-v2x-platooning-via-multi-agent-reinforcement-learning)| -|[efficient channel estimation with shorter pilots in ris-aided communications: using array geometries and interference statistics](https://arxiv.org/abs/2411.04753)|[RIS-shorter-pilots](https://github.com/ozlemtugfedemir/RIS-shorter-pilots)| +|date|paper|code| +|---|---|---| +|2411.04570|[higher-order gnns meet efficiency: sparse sobolev graph neural networks](https://arxiv.org/abs/2411.04570)|[S2-GNN](https://github.com/jhonygiraldo/S2-GNN)| +|2411.04672|[semantic-aware resource management for c-v2x platooning via multi-agent reinforcement learning](https://arxiv.org/abs/2411.04672)|[semantic-aware-resource-management-for-c-v2x-platooning-via-multi-agent-reinforcement-learning](https://github.com/qiongwu86/semantic-aware-resource-management-for-c-v2x-platooning-via-multi-agent-reinforcement-learning)| +|2411.04753|[efficient channel estimation with shorter pilots in ris-aided communications: using array geometries and interference statistics](https://arxiv.org/abs/2411.04753)|[RIS-shorter-pilots](https://github.com/ozlemtugfedemir/RIS-shorter-pilots)| ## 2024-11-07 -|paper|code| -|---|---| -|[reconfigurable massive mimo: precoding design and channel estimation in the electromagnetic domain](https://arxiv.org/abs/2405.02823)|[pra](https://github.com/kekeyingbit/pra)| -|[r-nerf: neural radiance fields for modeling ris-enabled wireless environments](https://arxiv.org/abs/2405.11541)|[R-NeRF](https://github.com/HUSTGSNeRF/R-NeRF)| -|[adversarial attacks on neural networks through canonical riemannian foliations](https://arxiv.org/abs/2203.00922)|[curvnetattack](https://github.com/eliot-tron/curvnetattack)| -|[towards entropic constraints on quantum speedups](https://arxiv.org/abs/2411.03439)|[QI_Research](https://github.com/DylanJVA/QI_Research)| -|[soft reverse reconciliation for discrete modulations](https://arxiv.org/abs/2411.04063)|[qam-reconciliation](https://github.com/moriglia/qam-reconciliation)| -|[learned codes for broadcast channels with feedback](https://arxiv.org/abs/2411.04083)|[gbcf](https://github.com/zyy-cc/gbcf)| +|date|paper|code| +|---|---|---| +|2411.03439|[towards entropic constraints on quantum speedups](https://arxiv.org/abs/2411.03439)|[QI_Research](https://github.com/DylanJVA/QI_Research)| +|2411.04063|[soft reverse reconciliation for discrete modulations](https://arxiv.org/abs/2411.04063)|[qam-reconciliation](https://github.com/moriglia/qam-reconciliation)| +|2411.04083|[learned codes for broadcast channels with feedback](https://arxiv.org/abs/2411.04083)|[gbcf](https://github.com/zyy-cc/gbcf)| ## 2024-11-06 -|paper|code| -|---|---| -|[a framework for real-time volcano-seismic event recognition based on multi-station seismograms and semantic segmentation models](https://arxiv.org/abs/2410.20595)|[volcano-seismic-segmentation](https://github.com/camilo-espinosa/volcano-seismic-segmentation)| -|[filternet: harnessing frequency filters for time series forecasting](https://arxiv.org/abs/2411.01623)|[filternet](https://github.com/aikunyi/filternet)| -|[nmformer: a transformer for noisy modulation classification in wireless communication](https://arxiv.org/abs/2411.02428)|[NMformer](https://github.com/atik666/NMformer)| -|[conditional vendi score: an information-theoretic approach to diversity evaluation of prompt-based generative models](https://arxiv.org/abs/2411.02817)|[conditional-vendi](https://github.com/mjalali/conditional-vendi)| +|date|paper|code| +|---|---|---| +|2411.01623|[filternet: harnessing frequency filters for time series forecasting](https://arxiv.org/abs/2411.01623)|[filternet](https://github.com/aikunyi/filternet)| +|2411.02428|[nmformer: a transformer for noisy modulation classification in wireless communication](https://arxiv.org/abs/2411.02428)|[NMformer](https://github.com/atik666/NMformer)| +|2411.02817|[conditional vendi score: an information-theoretic approach to diversity evaluation of prompt-based generative models](https://arxiv.org/abs/2411.02817)|[conditional-vendi](https://github.com/mjalali/conditional-vendi)| ## 2024-11-05 -|paper|code| -|---|---| -|[spectral clustering via orthogonalization-free methods](https://arxiv.org/abs/2305.10356)|[distributedlevp.jl](https://github.com/qiyuanpang/distributedlevp.jl)| -|[synthesizing eeg signals from event-related potential paradigms with conditional diffusion models](https://arxiv.org/abs/2403.18486)|[Conditional-EEG-Diffusion](https://github.com/guido151/Conditional-EEG-Diffusion)| -|[refining adhd diagnosis with eeg: the impact of preprocessing and temporal segmentation on classification accuracy](https://arxiv.org/abs/2407.08316)|[refining-adhd-diagnosis-with-eeg-preprocesing-and-temporal-segmentation](https://gitlab.com/lucentia/refining-adhd-diagnosis-with-eeg-preprocesing-and-temporal-segmentation)| -|[towards generative ray path sampling for faster point-to-point ray tracing](https://arxiv.org/abs/2410.23773)|[DiffeRT](https://github.com/jeertmans/DiffeRT)| -|[understanding generalizability of diffusion models requires rethinking the hidden gaussian structure](https://arxiv.org/abs/2410.24060)|[Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure](https://github.com/Morefre/Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure)| -|[enhancing glucose level prediction of icu patients through irregular time-series analysis and integrated representation](https://arxiv.org/abs/2411.01418)|[MITST](https://github.com/zavareh89/MITST)| -|[multimodal trustworthy semantic communication for audio-visual event localization](https://arxiv.org/abs/2411.01991)|[MU_SC_for_VQA](https://github.com/dimlight13/MU_SC_for_VQA)| +|date|paper|code| +|---|---|---| +|2411.01418|[enhancing glucose level prediction of icu patients through irregular time-series analysis and integrated representation](https://arxiv.org/abs/2411.01418)|[MITST](https://github.com/zavareh89/MITST)| +|2411.01991|[multimodal trustworthy semantic communication for audio-visual event localization](https://arxiv.org/abs/2411.01991)|[MU_SC_for_VQA](https://github.com/dimlight13/MU_SC_for_VQA)| ## 2024-11-04 -|paper|code| -|---|---| -|[pay less but get more: a dual-attention-based channel estimation network for massive mimo systems with low-density pilots](https://arxiv.org/abs/2303.00986)|[dacen](https://github.com/bgzhou/dacen)| -|[du-in: discrete units-guided mask modeling for decoding speech from intracranial neural signals](https://arxiv.org/abs/2405.11459)|[du-in](https://github.com/liulab-repository/du-in)| -|[hrrpgraphnet: make hrrps to be graphs for efficient target recognition](https://arxiv.org/abs/2407.08236)|[HRRPGraphNet](https://github.com/MountainChenCad/HRRPGraphNet)| -|[semantic knowledge distillation for onboard satellite earth observation image classification](https://arxiv.org/abs/2411.00209)|[snt-sentry](https://github.com/ltdung/snt-sentry)| -|[multi-group proportional representation in retrieval](https://arxiv.org/abs/2407.08571)|[multigroup-proportional-representation](https://github.com/alex-oesterling/multigroup-proportional-representation)| +|date|paper|code| +|---|---|---| +|2411.00209|[semantic knowledge distillation for onboard satellite earth observation image classification](https://arxiv.org/abs/2411.00209)|[snt-sentry](https://github.com/ltdung/snt-sentry)| ## 2024-11-01 -|paper|code| -|---|---| -|[advancing free-space optical communication system architecture: performance analysis of varied optical ground station network configurations](https://arxiv.org/abs/2410.23470)|[fso-simulation](https://github.com/connor-a-casey/fso-simulation)| -|[a peaceman-rachford splitting approach with deep equilibrium network for channel estimation](https://arxiv.org/abs/2410.23752)|[PR-DEN](https://github.com/wushitong1234/PR-DEN)| -|[generative ai-powered plugin for robust federated learning in heterogeneous iot networks](https://arxiv.org/abs/2410.23824)|[gaudi-fl](https://github.com/NAVER-INTEL-Co-Lab/gaudi-fl)| -|[cough-e: a multimodal, privacy-preserving cough detection algorithm for the edge](https://arxiv.org/abs/2410.24066)|[Cough-E](https://github.com/esl-epfl/Cough-E)| -|[computation with quantum reed-muller codes and their mapping onto 2d atom arrays](https://arxiv.org/abs/2410.23263)|[RM127](https://github.com/gongaa/RM127)| +|date|paper|code| +|---|---|---| diff --git a/archives/2024/12.md b/archives/2024/12.md index a9dc3b1e..3e3dc6e0 100644 --- a/archives/2024/12.md +++ b/archives/2024/12.md @@ -1,34 +1,16 @@ # December 2024 Archive ## 2024-12-04 -|paper|code| -|---|---| -|[pitn: physics-informed temporal networks for cuffless blood pressure estimation](https://arxiv.org/abs/2408.08488)|[acl-pitn](https://github.com/zest86/acl-pitn)| +|date|paper|code| +|---|---|---| ## 2024-12-03 -|paper|code| -|---|---| -|[robust graph filter identification and graph denoising from signal observations](https://arxiv.org/abs/2210.08488)|[graph_denoising](https://github.com/reysam93/graph_denoising)| -|[recurrences reveal shared causal drivers of complex time series](https://arxiv.org/abs/2301.13516)|[shrec](https://github.com/williamgilpin/shrec)| -|[kronecker-structured sparse vector recovery with application to irs-mimo channel estimation](https://arxiv.org/abs/2310.07869)|[dsr](https://github.com/yanbinhe/dsr)| -|[doorinet: door heading prediction through inertial deep learning](https://arxiv.org/abs/2402.09427)|[doorinet](https://github.com/ansfl/doorinet)| -|[sky-gvio: an enhanced gnss/ins/vision navigation with fcn-based sky-segmentation in urban canyon](https://arxiv.org/abs/2404.11070)|[sky-view-images](https://github.com/whuwangjr/sky-view-images)| -|[soundscape captioning using sound affective quality network and large language model](https://arxiv.org/abs/2406.05914)|[soundscaper](https://github.com/yuanbo2020/soundscaper)| -|[understanding generalizability of diffusion models requires rethinking the hidden gaussian structure](https://arxiv.org/abs/2410.24060)|[Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure](https://github.com/Morefre/Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure)| -|[snake-inspired mobile robot positioning with hybrid learning](https://arxiv.org/abs/2411.17430)|[MoRPINet](https://github.com/ansfl/MoRPINet)| -|[automatic differentiation-based full waveform inversion with flexible workflows](https://arxiv.org/abs/2412.00486)|[ADFWI](https://github.com/liufeng2317/ADFWI)| -|[pruned convolutional attention network based wideband spectrum sensing with sub-nyquist sampling](https://arxiv.org/abs/2412.00562)|[PCA-WSSNet](https://github.com/AI4CogComm/PCA-WSSNet)| -|[rotation invariant quantization for model compression](https://arxiv.org/abs/2303.03106)|[riq](https://github.com/ehaleva/riq)| -|[task-aware distributed source coding under dynamic bandwidth](https://arxiv.org/abs/2305.15523)|[task-aware-distributed-source-coding](https://github.com/utaustin-swarmlab/task-aware-distributed-source-coding)| -|[a truly concurrent semantics for reversible ccs](https://arxiv.org/abs/2309.14011)|[reversible-ccs-as-nets](https://github.com/hmelgra/reversible-ccs-as-nets)| +|date|paper|code| +|---|---|---| +|2412.00486|[automatic differentiation-based full waveform inversion with flexible workflows](https://arxiv.org/abs/2412.00486)|[ADFWI](https://github.com/liufeng2317/ADFWI)| +|2412.00562|[pruned convolutional attention network based wideband spectrum sensing with sub-nyquist sampling](https://arxiv.org/abs/2412.00562)|[PCA-WSSNet](https://github.com/AI4CogComm/PCA-WSSNet)| ## 2024-12-02 -|paper|code| -|---|---| -|[a time-causal and time-recursive analogue of the gabor transform](https://arxiv.org/abs/2308.14512)|[pygabor](https://github.com/tonylindeberg/pygabor)| -|[robust stochastically-descending unrolled networks](https://arxiv.org/abs/2312.15788)|[unrolledglow](https://github.com/smrhadou/unrolledglow)| -|[unleashing the power of data tsunami: a comprehensive survey on data assessment and selection for instruction tuning of language models](https://arxiv.org/abs/2408.02085)|[fantastic-data-engineering](https://github.com/yuleiqin/fantastic-data-engineering)| -|[scaling transformers for low-bitrate high-quality speech coding](https://arxiv.org/abs/2411.19842)|[stable-codec](https://github.com/Stability-AI/stable-codec)| -|[scalable exploration via ensemble++](https://arxiv.org/abs/2407.13195)|[ensemble_plus_plus](https://github.com/szrlee/ensemble_plus_plus)| -|[fast mutual information computation for large binary datasets](https://arxiv.org/abs/2411.19702)|[bulk-MI](https://github.com/aofalcao/bulk-MI)| +|date|paper|code| +|---|---|---| diff --git a/daily_arxiv.py b/daily_arxiv.py index 54e92f21..c003ee80 100644 --- a/daily_arxiv.py +++ b/daily_arxiv.py @@ -36,6 +36,9 @@ def get_daily_code(DateToday,cats): _id = v["id"] paper_title = " ".join(v["title"].split()) paper_url = v["url"] + paper_date = v.get("published", DateToday) + if isinstance(paper_date, datetime.datetime): + paper_date = paper_date.strftime("%Y-%m-%d") url = base_url + _id try: r = requests.get(url).json() @@ -44,7 +47,7 @@ def get_daily_code(DateToday,cats): repo_url = r["official"]["url"] repo_name = repo_url.split("/")[-1] - content[_id] = f"|[{paper_title}]({paper_url})|[{repo_name}]({repo_url})|\n" + content[_id] = f"|{paper_date}|[{paper_title}]({paper_url})|[{repo_name}]({repo_url})|\n" except Exception as e: print(f"exception: {e} with id: {_id}") data = {DateToday:content} @@ -78,8 +81,8 @@ def ensure_archive_dirs(): # Create base archives dir pathlib.Path(archive_base).mkdir(exist_ok=True) - # Create directories for all years from 2020 to current year - for year in range(2020, current_year + 1): + # Create directories for all years from 2021 to current year + for year in range(2021, current_year + 1): year_dir = os.path.join(archive_base, str(year)) pathlib.Path(year_dir).mkdir(exist_ok=True) @@ -128,23 +131,32 @@ def json_to_md(filename): with open("README.md", "w") as f: # Write header and overview f.write("# Daily ArXiv\n\n") - f.write("HelloGitHub shares interesting, entry-level GitHub projects. Updated monthly on the 28th in the form of a monthly magazine. ") - f.write("Content includes: interesting and entry-level projects, open source books, practical projects, enterprise projects, etc., ") - f.write("allowing you to experience the charm of open source in a very short time and fall in love with open source!\n\n") + f.write("A curated collection of arXiv papers with open-source implementations, specifically focusing on Signal Processing (eess.SP) ") + f.write("and Information Theory (cs.IT) categories. This repository is designed to serve researchers and practitioners in information ") + f.write("and communication systems by providing easy access to papers that come with their source code implementations.\n\n") f.write("## Overview\n") - f.write("This project automatically analyzes papers from specific categories on arXiv daily using GitHub Actions, ") - f.write("identifying papers that have released their source code and appending them to this repository.\n\n") + f.write("This project automatically tracks and analyzes papers from eess.SP (Electrical Engineering and Systems Science - Signal Processing) ") + f.write("and cs.IT (Computer Science - Information Theory) categories on arXiv daily using GitHub Actions. It specifically identifies ") + f.write("and catalogs papers that have released their source code, making it easier for researchers in information and communication ") + f.write("systems to find implementable research work.\n\n") + + f.write("The main features include:\n") + f.write("- Daily updates of papers with open-source implementations\n") + f.write("- Focus on signal processing and information theory research\n") + f.write("- Automatic tracking and organization\n\n") # Write latest updates - f.write("## Latest Updates (Last 7 Days)\n") + f.write("## Latest Updates \n") + yymm = f"{str(today.year)[2:]}{today.month:02d}" for day, day_content in latest_entries: if not day_content: continue f.write(f"### {day}\n") - f.write("|paper|code|\n" + "|---|---|\n") + f.write("|date|paper|code|\n" + "|---|---|---|\n") for k, v in day_content.items(): - f.write(v) + if k.startswith(yymm): + f.write(f"|{k}{v}") f.write("\n") # Write archive links @@ -158,16 +170,17 @@ def json_to_md(filename): for year_month, entries in entries_by_month.items(): year, month = year_month.split("/") archive_file = f"archives/{year}/{int(month):02d}.md" - + yymm = f"{year[2:]}{month}" with open(archive_file, "w") as f: f.write(f"# {datetime.date(int(year), int(month), 1).strftime('%B %Y')} Archive\n\n") for day, day_content in entries: if not day_content: continue f.write(f"## {day}\n") - f.write("|paper|code|\n" + "|---|---|\n") + f.write("|date|paper|code|\n" + "|---|---|---|\n") for k, v in day_content.items(): - f.write(v) + if k.startswith(yymm): + f.write(f"|{k}{v}") f.write("\n") print("Finished generating markdown files") @@ -175,7 +188,7 @@ def json_to_md(filename): if __name__ == "__main__": DateToday = datetime.date.today() - N = 5 # 往前查询的天数 + N = 1 # 往前查询的天数 data_all = [] for i in range(1,N): day = str(DateToday + timedelta(-i))