Follow the newest research on incremental learning
- Continual Learning for Natural Language Generation in Task-oriented Dialog Systems(EMNLP, 2020) [paper]
- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks (NeurIPS2020) [paper] [code]
- Meta-Consolidation for Continual Learning (NeurIPS2020) [paper]
- Understanding the Role of Training Regimes in Continual Learning (NeurIPS2020) [paper]
- Continual Learning with Node-Importance based Adaptive Group Sparse Regularization (NeurIPS2020) [paper]
- Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning (NeurIPS2020) [paper]
- Coresets via Bilevel Optimization for Continual Learning and Streaming (NeurIPS2020) [paper]
- RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning (NeurIPS2020) [paper]
- Continual Deep Learning by Functional Regularisation of Memorable Past (NeurIPS2020) [paper]
- Dark Experience for General Continual Learning: a Strong, Simple Baseline (NeurIPS2020) [paper] [code]
- GAN Memory with No Forgetting (NeurIPS2020) [paper]
- Calibrating CNNs for Lifelong Learning (NeurIPS2020) [paper]
- ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation(RecSys, 2020) [paper]
- Initial Classifier Weights Replay for Memoryless Class Incremental Learning (BMVC2020) [paper]
- Adversarial Continual Learning (ECCV2020) [paper] [code]
- REMIND Your Neural Network to Prevent Catastrophic Forgetting (ECCV2020) [paper] [code]
- Incremental Meta-Learning via Indirect Discriminant Alignment (ECCV2020) [paper]
- Memory-Efficient Incremental Learning Through Feature Adaptation (ECCV2020) [paper]
- PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning (ECCV2020) [paper] [code]
- Reparameterizing Convolutions for Incremental Multi-Task Learning Without Task Interference (ECCV2020) [paper]
- Learning latent representions across multiple data domains using Lifelong VAEGAN (ECCV2020) [paper]
- Online Continual Learning under Extreme Memory Constraints (ECCV2020) [paper]
- Class-Incremental Domain Adaptation (ECCV2020) [paper]
- More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning (ECCV2020) [paper]
- Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation (ECCV2020) [paper]
- GDumb: A Simple Approach that Questions Our Progress in Continual Learning (ECCV2020) [paper]
- Imbalanced Continual Learning with Partitioning Reservoir Sampling (ECCV2020) [paper]
- Topology-Preserving Class-Incremental Learning (ECCV2020) [paper]
- GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems (CIKM2020) [paper]
- OvA-INN: Continual Learning with Invertible Neural Networks (IJCNN2020) [paper]
- XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning (ICLM2020) [paper]
- Optimal Continual Learning has Perfect Memory and is NP-HARD (ICML2020) [paper]
- Neural Topic Modeling with Continual Lifelong Learning (ICML2020) [paper]
- Continual Learning with Knowledge Transfer for Sentiment Classification (ECML-PKDD2020) [paper] [code]
- Semantic Drift Compensation for Class-Incremental Learning (CVPR2020) [paper] [code]
- Few-Shot Class-Incremental Learning (CVPR2020) [paper]
- Modeling the Background for Incremental Learning in Semantic Segmentation (CVPR2020) [paper]
- Incremental Few-Shot Object Detection (CVPR2020) [paper]
- Incremental Learning In Online Scenario (CVPR2020) [paper]
- Maintaining Discrimination and Fairness in Class Incremental Learning (CVPR2020) [paper]
- Conditional Channel Gated Networks for Task-Aware Continual Learning (CVPR2020) [paper]
- Continual Learning with Extended Kronecker-factored Approximate Curvature (CVPR2020) [paper]
- iTAML : An Incremental Task-Agnostic Meta-learning Approach (CVPR2020) [paper] [code]
- Mnemonics Training: Multi-Class Incremental Learning without Forgetting (CVPR2020) [paper] [code]
- ScaIL: Classifier Weights Scaling for Class Incremental Learning (WACV2020) [paper]
- Accepted papers(ICLR2020) [paper]
- Brain-inspired replay for continual learning with artificial neural networks (Natrue Communications 2020) [paper] [code]
Incremental Learners for Continual Learning https://github.com/arthurdouillard/incremental_learning.pytorch