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.

7 papers of 11,817Sort Recent · Most cited
  1. 2024
    Graph Continual Learning with Debiased Lossless Memory ReplayChaoxi Niu, Guan-Song Pang, Ling ChenEuropean Conference on Artificial Intelligence
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  2. 2024
    Informed Spectral Normalized Gaussian Processes for Trajectory PredictionChristian Schlauch, Christian Wirth, Nadja KleinEuropean Conference on Artificial Intelligence
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  3. 2024
    GUIDE: Guidance-based Incremental Learning with Diffusion ModelsBartosz Cywi'nski, Kamil Deja, Tomasz Trzcinski … Lukasz Kuci'nskiEuropean Conference on Artificial Intelligence
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  4. 2024
    Natural Mitigation of Catastrophic Interference: Continual Learning in Power-Law Learning EnvironmentsAtith Gandhi, Raj Sanjay Shah, Vijay Marupudi, Sashank VarmaEuropean Conference on Artificial Intelligence
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  5. 2024
    Learning After Learning: Positive Backward Transfer in Continual LearningWernsen Wong, Yun Sing Koh, Gill DobbieEuropean Conference on Artificial Intelligence
  6. 2024
    Bridging Continual Learning of Motion and Self-Supervised RepresentationsMatteo Tiezzi, Simone Marullo, Alessandro Betti … S. MelacciEuropean Conference on Artificial Intelligence
  7. 2024
    Prompt-Based Domain Incremental Learning with Modular Classification LayerBo-Yu Wang, Yue Ma, Qinru QiuEuropean Conference on Artificial Intelligence
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.