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.

6 papers of 11,817Sort Recent · Most cited
  1. 2022
    Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part VDanai Koutra, Claudia Plant, Manuel Gomez-Rodriguez … Francesco BonchiSpringer LNCS · University of Michigan · University of Vienna · +2
    PDF ↗
  2. 2021
    DANICE: Domain adaptation without forgetting in neural image compressionSudeep Katakol, Luis Herranz, Fei Yang, Marta MrakCVPR · University of Michigan · Umbo Computer Vision (United Kingdom) · +1
    PDF ↗
  3. 2021
    How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of InterpolationEkdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert P. DickCoLLAs · University of Michigan
    PDF ↗
  4. 2019
    Overcoming Catastrophic Forgetting With Unlabeled Data in the WildKibok Lee, Kimin Lee, Jinwoo Shin, Honglak LeeICCV · Korea Advanced Institute of Science and Technology · University of Michigan · +1
    PDF ↗
  5. 2018
    Good Trouble: Post-tenure Interruptions to Our Academic ‘Routines’Nick TobierMetropolitan Universities · University of Michigan
  6. 2018
    Retaining identity: Creativity and caregivingAnne Mondro, Cathleen M Connell, Lydia Li, Elaine Wrisley ReedDementia · University of Michigan · Michigan Medicine
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.