Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

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2018 Preprint Clear all

2018
Three continual learning scenarios and a case for generative replayGido M. van de Ven, A. ToliasPreprint
2018
Interpretable Continual LearningTameem Adel, C. Nguyen, Richard E. Turner … Adrian WellerPreprint
2018
Learning to remember: Dynamic Generative Memory for Continual LearningOleksiy Ostapenko, M. Puscas, T. Klein, Moin NabiPreprint
2018
Activity Regularization for Continual LearningQ. Pham, S. HoiPreprint
2018
Continual Learning via Explicit Structure LearningXilai Li, Yingbo Zhou, Tianfu Wu … Caiming XiongPreprint
2018
O VERCOMING CATASTROPHIC FORGETTING THROUGH WEIGHT CONSOLIDATION AND LONG-TERM MEMORYShixian Wen, L. IttiPreprint
2018
StackNet: Stacking Parameters for Continual learningJangho Kim, Jeesoo Kim, Nojun KwakPreprint
2018
On catastrophic forgetting in Generative Adversarial NetworksHoang Thanh-Tung, T. TranPreprint
2018
Continual Learning for Deep Dense PredictionSanket LokegaonkarPreprint
2018
Information Theory Based Measurement Measuring Diversity of Link Weight for Mitigate Catastrophic Forgetting in Neural Network Learning LODLu Chen, M. MurataPreprint
2018
Progressive prune network for memory efficient continual learningJ. Nicholls, Sakyasingha DasguptaPreprint
2018
Natural Variational Continual LearningHanna TseranPreprint
2018
Continual Learning with Generative Replay via Discriminative Variational AutoencoderWoo-Young KangPreprint
2018
Continual Learning Through Expandable Elastic Weight ConsolidationAndrew Jones, Nathan SpraguePreprint
2018
Overcoming Catastrophic Forgetting in Neural Machine TranslationGregory KellPreprint
2018
Incremental Segmentation on Private Data without Catastrophic ForgettingTao Hu, PekingPreprint
2018
3 Our Proposal : Reinforced Continual LearningJu XuPreprint
2018
Developing Toward Generality : Overcoming Catastrophic Forgetting with Developmental CompressionShawn BeaulieuPreprint
2018
Developing Toward Generality: Combating Catastrophic Forgetting with Developmental CompressionShawn BeaulieuPreprint
2018
Exemplar-Supported Generative Reproduction for Class Incremental Learning Supplementary MaterialChen HePreprint
2018
Generative Adversarial Networks and Continual Learning ∗Kevin J Liang, Chunyuan Li, Guoyin Wang, L. CarinPreprint
2018
Not-so-Catastrophic Forgetting in Deep Reinforcement Learning on Sequential AtariGiacomo SpiglerPreprint
2018
Preventing Catastrophic Forgetting in an Online Learning SettingAyon Borthakur, M. Einhorn, Nikhil DhawanPreprint
2018
Tackling Transfer Learning and Catastrophic Forgetting Using Asynchronous Methods for Deep Reinforcement LearningJoao G. RibeiroPreprint
2018
Using Deep Learning to create a Universal Game Player Tackling Transfer Learning and Catastrophic Forgetting Using Asynchronous Methods for Deep Reinforcement LearningJoao G. RibeiroPreprint

About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.