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
    Activity Subspaces in Medial Prefrontal Cortex Distinguish States of the WorldSilvia Maggi, Mark D. HumphriesJournal of Neuroscience · University of Nottingham
  2. 2018
    Robust Associative Learning Is Sufficient to Explain the Structural and Dynamical Properties of Local Cortical CircuitsDanke Zhang, Chi Zhang, Armen StepanyantsJournal of Neuroscience · Northeastern University
  3. 2017
    Loss of Plasticity in the D2-Accumbens Pallidal Pathway Promotes Cocaine SeekingJasper A. Heinsbroek, Daniela Neuhofer, William C. Griffin … Peter W. KalivasJournal of Neuroscience · Museu da Amazonia · Medical University of South Carolina · +1
  4. 2011
    Dopaminergic genes predict individual differences in susceptibility to confirmation biasBradley B. Doll, Kent E. Hutchison, Michael J. FrankJournal of Neuroscience · Brown University · University of New Mexico · +2
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.