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.

36 papers of 11,817Sort Recent · Most cited
  1. 2020
  2. 2020
  3. 2020
    Author response: Can sleep protect memories from catastrophic forgetting?Oscar C. González, Yury Sokolov, Giri P. Krishnan … Maxim BazhenovPreprint · University of California San Diego
  4. 2020
    Combining Variational Continual Learning with FiLM LayersNoel Loo, S. Swaroop, Richard E. TurnerPreprint
  5. 2020
  6. 2020
    Continual Learning Using Multi-view Task Conditional Neural NetworksHonglin Li, Payam M. Barnaghi, Shirin Enshaeifar, F. GanzPreprint
  7. 2020
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  12. 2020
    Incremental Learning: Deep Neural NetworksR. Garimella, J. Prasanna, Maha Lakshmi Bairaju, Manasa JagannadanPreprint
  13. 2020
    Safety-Oriented Stability Biases for Continual LearningAshish Gaurav, Jaeyoung Lee, Vahdat Abdelzad, Sachin VernekarPreprint
  14. 2020
    Continual Learning on Incremental Simulations for Real-World Robotic Manipulation TasksJosip Josifovski, M. Malmir, Noah Klarmann, Alois KnollPreprint
  15. 2020
  16. 2020
    Chaotic Continual LearningTouraj Laleh, Mojtaba Faramarzi, I. Rish, Sarath ChandarPreprint
  17. 2020
    Logical Composition for Lifelong Reinforcement LearningGeraud Nangue Tasse, Steven James, Benjamin RosmanPreprint
  18. 2020
  19. 2020
    Active Continual Learning for Planning and NavigationA. H. Qureshi, Yinglong Miao, Michael C. YipPreprint
  20. 2020
    Can Expressive Posterior Approximations Improve Variational Continual Learning?S. Auddy, Jakob J. Hollenstein, Matteo Saveriano … J. PiaterPreprint
  21. 2020
  22. 2020
    A General Framework for Continual Learning of Compositional StructuresJorge Armando Mendez Mendez, Eric EatonPreprint
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  30. 2020
    Incremental Learning with Bayesian Neural NetworksPolitecnico di Torino, E. FicarraPreprint
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  36. 2020
    Supplementary Material for Few-Shot Class-Incremental LearningXiaoyu Tao, Xiaopeng Hong, Xinyuan Chang … Peng ChengPreprint
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.