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
    Balancing the Stability-Plasticity Dilemma with Online Stability Tuning for Continual LearningAnton Lee, Heitor Murilo Gomes, Yaqian ZhangIJCNN · University of Waikato · Victoria University of Wellington
  2. 2021
    Improving the performance of bagging ensembles for data streams through mini-batchingGuilherme Weigert Cassales, Heitor Murilo Gomes, Albert Bifet … Hermes SengerInformation Sciences · Universidade Federal de São Carlos · University of Waikato · +1
    PDF ↗
  3. 2020
    River: machine learning for streaming data in PythonJacob Montiel, Max Halford, Saulo Martiello Mastelini … Albert BifetJMLR · University of Waikato · Universidade de São Paulo · +14
    PDF ↗
  4. 2019
    Stochastic Gradient TreesHenry Gouk, Bernhard Pfahringer, Eibe FrankMachine Learning · University of Edinburgh · University of Waikato
    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 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.