Chainer is a flexible framework for neural networks. One of the major goals is flexibility, so it must enable us to write complex architectures simply and intuitively.
More info here
ref Chainer.wiki - Chainer Wiki
- Chainer Offical Guides - Chainer guides in the offical document
- hido/chainer-handson - Chainer Hands-on
- iwiwi/chainer-handson - Chainer Hands-on(JP CPU only)
- mitmul/chainer-handson - Chainer Hands-on
- mitmul/chainer-notebooks - Chainer Jupyter Notebooks
- ChainerRL - ChainerRL is a deep reinforcement learning library built on top of Chainer.
- ChainerCV - Versatile set of tools for Deep Learning based Computer Vision
- ChainerMN - Scalable distributed deep learning with Chainer
- ChainerUI - ChainerUI is a visualization and management tool for Chainer.
- PaintsChainer - Paints Chainer is line drawing colorizer using chainer.
- chainer/models - Models and examples built with Chainer
- chainer-LSGAN - Least Squares Generative Adversarial Network implemented in Chainer
- chainer-gogh - Implementation of "A neural algorithm of Artistic style"
- chainer-graph-cnn - Chainer implementation of 'Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering' (https://arxiv.org/abs/1606.09375)
- chainer-segnet - SegNet implementation & experiments in Chainer
- chainer-pix2pix - chainer implementation of pix2pix
- chainer-ADDA - Adversarial Discriminative Domain Adaptation
- chainer-gan-lib - Various GANs implementation
- tgan - Temporal Generative Adversarial Nets
- odashi/chainer_examples - Machine Translation, word segmentation, and language model
- odashi/chainer_rnnlm.py - RNN Language Model
- odashi/chainer_encoder_decoder.py - Neural Encoder-Decoder Machine Translation
- prajdabre/chainer_examples - LSTM variants
- yusuketomoto/chainer-char-rnn - Recurrent neural network (RNN)
- mlpnlp/mlpnlp-nmt - LSTM encoder-decoder with attention mechanism
- unnonouno/chainer-memnn - End-to-end memory networks
- jekbradbury/qrnn.py - QRNN
- tscohen/GrouPy - Group Equivariant Convolutional Neural Networks
- mitmul/chainer-fast-rcnn - Fast R-CNN
- mitmul/chainer-faster-rcnn - Faster R-CNN
- mitmul/chainer-cifar10 - Cifar10
- mitmul/DeepPose - Deep pose
- mitmul/chainer-conv-vis - Convolution Filter Visualization
- mitmul/chainer-imagenet-vgg - VGG
- mitmul/chainer-segnet - SegNet
- mitmul/PSPNet - Pyramid Scene Parsing Network
- apple2373/chainer-simple-fast-rnn - Fast R-CNN
- apple2373/chainer_stylenet - StyleNet (A Neural Algorithm of Artistic Style)
- apple2373/chainer_caption_generation - Show and Tell
- mrkn/chainer-srcnn - Image super-resolution
- Hi-king/chainer_superresolution - Image super-resolution
- darashi/chainer-example-overfeat-classify - Overfeat
- RyotaKatoh/chainer-Variational-AutoEncoder - Variational autoencoder (VAE)
- yasunorikudo/chainer-ResNet - ResNet
- yasunorikudo/chainer-DenseNet - DenseNet
- yasunorikudo/chainer-ResDrop - ResDrop
- yusuketomoto/chainer-fast-neuralstyle - Perceptual Losses for Real-Time Style Transfer and Super-Resolution
- rezoo/illustration2vec - illustration2vec
- chainer-prednet - Deep Predictive Coding Networks
- hillbig/binary_net - BinaryNet
- stitchfix/fauxtograph - Variational Auto-Encoder (VAE), Generative Adversarial Nets (GAN), VAE-GAN
- rezoo/data.py - Generative Adversarial Nets (GAN)
- mattya/chainer-gogh - StyleNet (A Neural Algorithm of Artistic Style)
- mattya/chainer-DCGAN - Deep Convolutional Generative Adversarial Network (DCGAN)
- mattya/chainer-fluid - Fluid simulation
- ktnyt/chainer_ca.py - Convolutional Autoencoder
- tochikuji/chainer-libDNN - Stacked Denoising Autoencoder
- masaki-y/ram - Recurrent Attention Model
- wkentaro/fcn - Fully Convolutional Networks
- hvy/chainer-gan-denoising-feature-matching - Generative Adversarial Networks with Denoising Feature Matching
- hvy/chainer-visualization - Visualizing and Understanding Convolutional Networks
- hvy/chainer-gan-trainer - Chainer GAN Trainer
- musyoku/wasserstein-gan - WGAN
- weihua916/imsat - IMSAT
- Hakuyume/chainer-ssd - SSD
- leetenki/YOLOv2 - YOLOv2
- leetenki/YOLOtiny_v2 - YOLOtiny_v2
- yuyu2172/deformable-conv - Deformable-conv
- dsanno/chainer-dfi - Deep Feature Interpolation for Image Content Changes
- dsanno/chainer-dfi - Deep Feature Interpolation for Image Content Changes
- osmr/imgclsmob - Collection of classification models pretrained on the ImageNet-1K
- ugo-nama-kun/DQN-chainer - Deep Q-Network (DQN)
- crcrpar/chainer-VAE - Variational AutoEncoder
- musyoku/LSGAN - LSGAN
- musyoku/began - BEGAN
- musyoku/adversarial-autoencoder - adversarial-autoencoder
- musyoku/unrolled-gan - unrolled-ga
- musyoku/improved-gan- improved-gan
- musyoku/variational-autoencoder - Semi-Supervised Learning with Deep Generative Models
- musyoku/adgm - Auxiliary Deep Generative Models
- musyoku/ddgm - Deep Directed Generative Models with Energy-Based Probability Estimation
- musyoku/minibatch_discrimination - Minibatch discrimination
- musyoku/wavenet - wavenet
- musyoku/IMSAT - IMSAT
- musyoku/vat - VAT
- musyoku/mnist-oneshot - mnist-oneshot
- mitmul/chainer-siamese - Siamese Network
- mitmul/chainer-svm - Support Vector Machine (SVM)
- Introduction to Chainer: Neural Networks in Python
- The DIY Guide to Chainer
- CHAINER CHARACTER EMBEDDINGS
- A Fontastic Voyage: Generative Fonts with Adversarial Networks
- uei/Deel; A High level deep neural network description language
- uei/DEEPstation
- shi3z/chainer_imagenet_tools
- lucidfrontier45/scikit-chainer
- tochikuji/chainer-libDNN
- musyoku/weight-normalization - Weight Normalization Layer for Chainer
- musyoku/chainer-sequential - chainer-sequential
- musyoku/recurrent-batch-normalization - Recurrent Batch Normalization
- hitsgub/extra-chainer - Implements novel methods
(in Japanese)
- Chainer Beginner's Hands-On: 01 (2018/12/01), 02 (2018/02/16)
- Chainer の Trainer 解説とNStepLSTM について Published on Mar 15, 2017
- Chainer Meetup #04 Published on Feb 23, 2017
- 1014：深層学習フレームワークChainerの導入と化合物活性予測への応用 Published on Dec 2, 2015
- GP-GAN: Towards Realistic High-Resolution Image Blending
- Conference: arXiv only
- Codes: wuhuikai/GP-GAN
- Temporal Generative Adversarial Nets
- Conference: arXiv only
- Reasoning with Memory Augmented Neural Networks for Language Comprehension
- Conference: arXiv only
- PMI Matrix Approximations with Applications to Neural Language Modeling
- Conference: arXiv only
- Neural Tree Indexers for Text Understanding
- Conference: arXiv only
- Codes: NTI
- Neural Semantic Encoders
- Conference: arXiv only
- Networked Intelligence: Towards Autonomous Cyber Physical Systems
- Conference: arXiv only
- Modeling the dynamics of human brain activity with recurrent neural networks
- Conference: arXiv only
- A Deep-Learning Approach for Operation of an Automated Realtime Flare Forecast
- Conference: arXiv only
- Convolutional Neural Networks using Logarithmic Data Representation
- Conference: arXiv only
- context2vec: Learning Generic Context Embedding with Bidirectional LSTM
- Conference: CoNLL 2016
- Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec
- Conference: CoNLL 2016
- Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition
- Conference: ECCV 2016 Workshop
- comments: "3rd place in Looking at People ECCV Challenge"
- Learning Joint Representations of Videos and Sentences with Web Image Search
- Conference: ECCV 2016 Workshop
- Incorporating Discrete Translation Lexicons into Neural Machine Translation
- Conference: EMNLP 2016
- Controlling Output Length in Neural Encoder-Decoders
- Conference: EMNLP 2016
- Insertion Position Selection Model for Flexible Non-Terminals in Dependency Tree-to-Tree Machine Translation
- Conference: EMNLP 2016
- Learning Representations Using Complex-Valued Nets
- Conference: ICLR 2016
- Dynamic Coattention Networks For Qustion Answering
- Conference: ICLR 2017 under review
- SqueezeNet: AlexNet-level Accuracy with 50x Fewer Parameters and < 0.5MB Model Size
- Conference: ICLR 2017 under review
- Quasi-Recurrent Neural Networks
- Conference: ICLR 2017 under review
- Steerable CNNs
- Conference: ICLR 2017
- comments: Chainer is not referred in the paper, but the authors kindly informed us.
- f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
- Conference: NIPS 2016 Workshop
- QSGD: Randomized Quantization for Communication-Optimal Stochastic Gradient Descent
- Conference: OPT 2016
- Evaluation of Deep Learning based Pose Estimation for Sign Language Recognition
- Conference: PETRA 2016
- Machine-learning Selection of Optical Transients in Subaru/Hyper Suprime-Cam Survey
- Conference: PASJ 2016
- comments: PASJ: Publications of the Astronomical Society of Japan
- A Deep-Learning Approach for Operation of an Automated Realtime Flare Forecast
- Conference: Space Weather 2016
- Dynamic Entity Representation with Max-pooling Improves Machine Reading
- Conference: NAACL 2016
- Feature-based Model versus Convolutional Neural Network for Stance Detection
- Conference: SemEval 2016
- Cross-Lingual Image Caption Generation
- Conference: ACL 2016
- Composing Distributed Representations of Relational Patterns
- Conference: ACL 2016
- Generating Natural Language Descriptions for Semantic Representations of Human Brain Activity
- Conference: ACL 2016
- MetaMind Neural Machine Translation System for WMT 2016
- Conference: WMT 2016
- Group Equivariant Convolutional Networks
- Conference: ICML 2016
- Codes: GitHub
- comments: Chainer is not referred in the paper, but the authors kindly informed us.
- Robocodes: Towards Generative Street Addresses from Satellite Imagery
- Conference: CVPR 2017 Workshop
- Chainer document - An introduction to Chainer
- Chainer blogs
- Introduction to Chainer: Neural Networks in Python
- The DIY Guide to Chainer
- CHAINER CHARACTER EMBEDDINGS
- A Fontastic Voyage: Generative Fonts with Adversarial Networks
- Chainerによる実践深層学習 by 新納浩幸