Being aware of different training and test settings.
- Continual learning: A comparative study on how to defy forgetting in classification tasks (arXiv 2019) [paper]
- Continual Lifelong Learning with Neural Networks: A Review (arXiv 2018) [paper]
- Random Path Selection for Incremental Learning (NeurIPS2019) [paper]
- Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild (ICCV2019) [paper]
- Continual Learning by Asymmetric Loss Approximation with Single-Side Overestimation (ICCV2019) [paper]
- Lifelong GAN: Continual Learning for Conditional Image Generation (ICCV2019) [paper]
- Continual learning of context-dependent processing in neural networks (Nature Machine Intelligence 2019) [paper] [code]
- Large Scale Incremental Learning (CVPR2019) [paper] [code]
- Learning a Unified Classifier Incrementally via Rebalancing (CVPR2019) [paper] [code]
- Learning Without Memorizing (CVPR2019) [paper]
- Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning (CVPR2019) [paper]
- Task-Free Continual Learning (CVPR2019) [paper]
- Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting (ICML2019) [paper]
- Efficient Lifelong Learning with A-GEM (ICLR2019) [paper] [code]
- Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference (ICLR2019) [paper] [code]
- Overcoming Catastrophic Forgetting via Model Adaptation (ICLR2019) [paper]
- A comprehensive, application-oriented study of catastrophic forgetting in DNNs (ICLR2019) [paper]
- Incremental Learning Techniques for Semantic Segmentation (ICCVW2019) [paper] [code]
- Memory Replay GANs: learning to generate images from new categories without forgetting (NIPS2018) [paper] [code]
- Reinforced Continual Learning (NIPS2018) [paper] [code]
- Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting (NIPS2018) [paper]
- Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting (R-EWC) (ICPR2018) [paper] [code]
- Exemplar-Supported Generative Reproduction for Class Incremental Learning (BMVC2018) [paper] [code]
- DeeSIL: Deep-Shallow Incremental Learning (ECCV2018) [paper]
- End-to-End Incremental Learning (ECCV2018) [paper][code]
- Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence (ECCV2018)[paper]
- Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights (ECCV2018) [paper] [code]
- Memory Aware Synapses: Learning what (not) to forget (ECCV2018) [paper] [code]
- Lifelong Learning via Progressive Distillation and Retrospection (ECCV2018) [paper]
- PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning (CVPR2018) [paper] [code]
- Overcoming Catastrophic Forgetting with Hard Attention to the Task (ICML2018) [paper] [code]
- Lifelong Learning with Dynamically Expandable Networks (ICLR2018) [paper]
- FearNet: Brain-Inspired Model for Incremental Learning (ICLR2018) [paper]
- Overcoming catastrophic forgetting in neural networks (EWC) (PNAS2017) [paper] [code] [code]
- Continual Learning Through Synaptic Intelligence (ICML2017) [paper] [code]
- Gradient Episodic Memory for Continual Learning (NIPS2017) [paper] [code]
- iCaRL: Incremental Classifier and Representation Learning (CVPR2017) [paper] [code]
- Continual Learning with Deep Generative Replay (NIPS2017) [paper] [code]
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (NIPS2017) [paper] [code]
- Expert Gate: Lifelong Learning with a Network of Experts (CVPR2017) [paper]
- Encoder Based Lifelong Learning (ICCV2017) [paper]