Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

227 papers of 4,574 · showing 201–227Sort Recent · Most cited
  1. 2019
    Compacting, Picking and Growing for Unforgetting Continual LearningSteven C. Y. Hung, Cheng-Hao Tu, Cheng‐En Wu … Chu-Song ChenNeurIPS
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  2. 2021
    BooVAE: Boosting Approach for Continual Learning of VAEAnna Kuzina, Evgenii Egorov, Evgeny BurnaevNeurIPS · Yandex (Russia) · Skolkovo Institute of Science and Technology
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  3. 2019
    Visualizing the PHATE of Neural NetworksScott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal MishneNeurIPS · Yale University · Princeton University · +1
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  4. 2019
    Episodic Memory in Lifelong Language LearningCyprien de Masson d’Autume, Sebastian Ruder, Lingpeng Kong, Dani YogatamaNeurIPS
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  5. 2019
    An Adaptive Random Path Selection Approach for Incremental Learning.Jathushan Rajasegaran, Munawar Hayat, Salman Khan … Ming–Hsuan YangNeurIPS
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  6. 2019
    Meta-Learning Representations for Continual LearningKhurram Javed, Martha WhiteNeurIPS · University of Alberta
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  7. 2019
    Uncertainty-based Continual Learning with Adaptive RegularizationHongjoon Ahn, Sungmin Cha, Dong-Gyu Lee, Taesup MoonNeurIPS · Sungkyunkwan University
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  8. 2019
    Improving and Understanding Variational Continual LearningSiddharth Swaroop, Cuong V. Nguyen, Thang D. Bui, Richard E. TurnerNeurIPS
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  9. 2019
    Three scenarios for continual learningGido M. van de Ven, Andreas S. ToliasNeurIPS
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  10. 2019
    Gradient based sample selection for online continual learningRahaf Aljundi, Min Lin, Baptiste Goujaud, Yoshua BengioNeurIPS · KU Leuven · National University of Singapore · +1
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  11. 2019
    Continual Learning in PracticeTom Diethe, Tom Borchert, Eno Thereska … Neil D. LawrenceNeurIPS · Amazon (Germany)
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  12. 2019
    A Unifying Bayesian View of Continual LearningSebastian Farquhar, Yarin GalNeurIPS · University of Oxford
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  13. 2019
    Superposition of Many Models into OneBrian Cheung, A. L. Terekhov, Yubei Chen … Bruno A. OlshausenNeurIPS · University of California, Berkeley
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  14. 2018PDF ↗
  15. 2019
    Experience Replay for Continual LearningDavid Rolnick, Arun Ahuja, Jonathan Schwarz … Greg WayneNeurIPS · California University of Pennsylvania · University of Pennsylvania · +1
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  16. 2018
    Continual Classification Learning Using Generative ModelsFrantzeska Lavda, Jason Ramapuram, Magda Gregorová, Alexandros KalousisNeurIPS
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  17. 2018
    Life-Long Disentangled Representation Learning with Cross-Domain Latent HomologiesAlessandro Achille, Tom Eccles, Löıc Matthey … Irina HigginsNeurIPS
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  18. 2018
    Reinforced Continual LearningJu Xu, Zhanxing ZhuNeurIPS
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  19. 2018
    Distributed Weight Consolidation: A Brain Segmentation Case StudyPatrick McClure, Charles Zheng, Jakub Kaczmarzyk … Francisco PereiraNeurIPS · National Institutes of Health · Massachusetts Institute of Technology
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  20. 2018
    Online Structured Laplace Approximations For Overcoming Catastrophic ForgettingHippolyt Ritter, Aleksandar Botev, David BarberNeurIPS
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  21. 2018
    HOUDINI: Lifelong Learning as Program SynthesisLazar Valkov, Dipak Chaudhari, Akash Srivastava … Swarat ChaudhuriNeurIPS · Indian Institute of Technology Bombay · IBM (United States) · +2
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  22. 2018
    Task Agnostic Continual Learning Using Online Variational BayesChen Zeno, Itay Golan, Elad Hoffer, Daniel SoudryNeurIPS
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  23. 2017
    Gradient Episodic Memory for Continual LearningDavid López-Paz, Marc’Aurelio RanzatoNeurIPS · Max Planck Society · Max Planck Innovation · +1
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  24. 2017
    Continual Learning with Deep Generative ReplayHanul Shin, Jung Kwon Lee, Jaehong Kim, Jiwon KimNeurIPS · Seoul National University · Samsung (South Korea)
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  25. 2017
    Streaming Sparse Gaussian Process ApproximationsThang D. Bui, Cuong V. Nguyen, Richard E. TurnerNeurIPS · University of Cambridge
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  26. 2017
    Overcoming Catastrophic Forgetting by Incremental Moment MatchingSang-Woo Lee, Jin-Hwa Kim, Jae-Hyun Jun … Byoung‐Tak ZhangNeurIPS · Seoul National University · Naver (South Korea)
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  27. 2013
    Sequential Transfer in Multi-armed Bandit with Finite Set of ModelsMohammad Gheshlaghi Azar, Alessandro Lazaric, Emma BrunskillNeurIPS · Carnegie Mellon University · Laboratoire d'Informatique Fondamentale de Lille
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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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times, and only papers with a PDF we can point you at, so every title opens the paper itself. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.