Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

4 papers of 8,653Sort Recent · Most cited
  1. 2011
    Evolution of heterogeneous ensembles through dynamic particle swarm optimization for video-based face recognitionJean-François Connolly, Éric Granger, Robert SabourinPattern Recognition · Université du Québec à Montréal · École de Technologie Supérieure
  2. 2011
    Incremental Learning From Stream DataHaibo He, Sheng Chen, Kang Li, Xin XuIEEE Transactions · University of Rhode Island · Stevens Institute of Technology · +3
  3. 2011
    Towards semi-supervised learning of semantic spatial conceptsJesús Martínez-Gómez, Barbara CaputoICRA · Idiap Research Institute
  4. 2011
    A Cognitive Model for Generalization during Sequential LearningAshish Gupta, Lovekesh Vig, David C. NoelleJournal of Robotics · Vanderbilt University · Jawaharlal Nehru University · +1
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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.