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.

3 papers of 11,817Sort Recent · Most cited
  1. 2022
    Continual task learning in natural and artificial agentsTimo Flesch, Andrew Saxe, Christopher SummerfieldTrends in Neurosciences · University of Oxford · Sainsbury Laboratory · +3
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  2. 2022
    Modelling continual learning in humans with Hebbian context gating and exponentially decaying task signalsTimo Flesch, Dávid Nagy, Andrew Saxe, Christopher SummerfieldPLOS · University of Oxford · HUN-REN Wigner Research Centre for Physics · +5
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  3. 2018
    Comparing continual task learning in minds and machinesTimo Flesch, Jan Balaguer, Ronald Dekker … Christopher SummerfieldPNAS · University of Oxford · Google DeepMind (United Kingdom)
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.