Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

6 papers of 6,984Sort Recent · Most cited
  1. 2021
    CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future DirectionsVincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodríguez … Davide MaltoniArtificial Intelligence · University of Bologna · Mila - Quebec Artificial Intelligence Institute · +7
    PDF ↗
  2. 2021
    Behavior Self-Organization Supports Task Inference for Continual Robot LearningMuhammad Burhan Hafez, Stefan WermterIROS · Universität Hamburg · Hamburg University of Technology
    PDF ↗
  3. 2021
    Learning Then, Learning Now, and Every Second in Between: Lifelong Learning With a Simulated Humanoid RobotAleksej Logacjov, Matthias Kerzel, Stefan WermterFrontiers · Universität Hamburg
  4. 2021
    Avalanche: an End-to-End Library for Continual LearningVincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu … Davide MaltoniCVPR · University of Pisa · University of Bologna · +12
    PDF ↗
  5. 2021
    DRILL: Dynamic Representations for Imbalanced Lifelong LearningKyra Ahrens, Fares Abawi, Stefan WermterSpringer LNCS · Universität Hamburg
    PDF ↗
  6. 2021
    Lifelong Learning from Event-based DataVadym Gryshchuk, Cornelius Weber, Chu Kiong Loo, Stefan WermterESANN 2021 proceedings · Universität Hamburg · University of Malaya
    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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.