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. 2021
    Else-Net: Elastic Semantic Network for Continual Action Recognition from Skeleton DataTianjiao Li, Qiuhong Ke, Hossein Rahmani … Jun LiuICCV · Singapore University of Technology and Design · The University of Melbourne · +2
  2. 2020
    Continual Learning of Multiple Memories in Mechanical NetworksMenachem Stern, Matthew B. Pinson, Arvind MuruganPhysical Review X · University of Chicago · The University of Melbourne
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  3. 2019
    Forget Me Not: Reducing Catastrophic Forgetting for Domain Adaptation in Reading ComprehensionYing Xu, Xu Zhong, Antonio Jimeno Yepes, Jey Han LauIJCNN · IBM Research - Australia · The University of Melbourne
    PDF ↗
  4. 2018
    Task Runtime Prediction in Scientific Workflows Using an Online Incremental Learning ApproachMuhammad Hafizhuddin Hilman, Maria A. Rodriguez, Rajkumar BuyyaInternational Conference on Utility and Cloud Computing · The University of Melbourne
    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.