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.

15 papers of 11,817Sort Recent · Most cited
  1. 2026
    Forager: a lightweight testbed for continual learning with partial observability in RLSteven Tang, Xin Xiong, Anna Hakhverdyan … Adam WhitearXiv
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  2. 2025
    Rethinking the Foundations for Continual Reinforcement LearningEsraa Elelimy, David Szepesvari, Martha White, Michael BowlingarXiv
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  3. 2024
    Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay BuffersG. Vasan, Mohamed Elsayed, Alireza Azimi … A. MahmoodNeurIPS
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  4. 2024
    Position: Lifetime tuning is incompatible with continual reinforcement learningGolnaz Mesbahi, P. Panahi, Olya Mastikhina … Adam WhiteICML
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  5. 2024PDF ↗
  6. 2023
    Measuring and Mitigating Interference in Reinforcement LearningVincent Liu, Han Wang, Ruo Yu Tao … Martha WhiteCoLLAs
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  7. 2022
    Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with MomentumKirby Banman, Liam Peet-Pare, Nidhi Hegde … Martha WhiteICLR
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  8. 2020
    Towards a practical measure of interference for reinforcement learningVincent Liu, Adam White, Hengshuai Yao, Martha WhitearXiv
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  9. 2020
    Learning Causal Models OnlineKhurram Javed, Martha White, Yoshua BengioarXiv
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  10. 2019PDF ↗
  11. 2019
    Is Fast Adaptation All You Need?Khurram Javed, Hengshuai Yao, Martha WhitearXiv
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  12. 2018
    The Utility of Sparse Representations for Control in Reinforcement LearningVincent Liu, Raksha Kumaraswamy, Lei Le, Martha WhiteAAAI · University of Alberta · Indiana University Bloomington
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  13. 2019
    Meta-Learning Representations for Continual LearningKhurram Javed, Martha WhiteNeurIPS · University of Alberta
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  14. 2018
    The Barbados 2018 List of Open Issues in Continual LearningTom Schaul, Hado van Hasselt, Joseph Modayil … Doina PrecuparXiv
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  15. 2017
    Stable predictive representations with general value functions for continual learningM. Schlegel, Adam White, Martha WhiteContinual Learning and Deep Networks at the Neural Inform…
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.