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.

3 papers of 11,817Sort Recent · Most cited
  1. 2020
    An Accelerated Continual Learning with Demand Prediction based Scheduling in Edge-Cloud ComputingChangha Lee, Seong-Hwan Kim, Chan‐Hyun YounICDM · Korea Advanced Institute of Science and Technology
  2. 2020
    An Accelerated Edge Cloud System for Energy Data Stream Processing Based on Adaptive Incremental Deep Learning SchemeSeong-Hwan Kim, Changha Lee, Chan‐Hyun YounIEEE Access · Korea Advanced Institute of Science and Technology
  3. 2019
    Imbalanced-Free Memory Selection Scheme Based Continual Learning by Using K-means ClusteringChangha Lee, Minsu Jeon, Eunju Yang … Chan‐Hyun YounInternational Conference on Information and Communication… · Korea Advanced Institute of Science and Technology
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.