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.

4 papers of 11,817Sort Recent · Most cited
  1. 2022
    Is Multi-Task Learning an Upper Bound for Continual Learning?Zihao Wu, Huy Tran, Hamed Pirsiavash, Soheil KolouriICASSP · Vanderbilt University · University of California, Davis
    PDF ↗
  2. 2022
    Lifelong Reinforcement Learning with Modulating MasksEseoghene Ben-Iwhiwhu, Saptarshi Nath, Praveen K. Pilly … Andrea SoltoggioTrans. Mach. Learn. Res.
    PDF ↗
  3. 2022
    Biological underpinnings for lifelong learning machinesDhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb … Hava T. SiegelmannNature Machine Intelligence · The University of Texas at San Antonio · Intelligent Systems Research (United States) · +24
  4. 2022
    Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural ActivationsAli Abbasi, Parsa Nooralinejad, Vladimir Braverman … Soheil KolouriCoLLAs
    PDF ↗
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.