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.

14 papers of 11,817Sort Recent · Most cited
  1. 2023
    First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental LearningA. Panos, Yuriko Kobe, Daniel Olmeda Reino … Richard E. TurnerICCV
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  2. 2023
    Improving Continual Learning by Accurate Gradient Reconstructions of the PastErik Daxberger, S. Swaroop, Kazuki Osawa … Mohammad Emtiyaz KhanTrans. Mach. Learn. Res.
  3. 2021
    Continual Novelty DetectionRahaf Aljundi, Daniel Olmeda Reino, Nikolay Chumerin, Richard E. TurnerCoLLAs
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  4. 2020
    Generalized Variational Continual LearningNoel Loo, Siddharth Swaroop, Richard E. TurnerICLR · University of Cambridge
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  5. 2020
    Combining Variational Continual Learning with FiLM LayersNoel Loo, S. Swaroop, Richard E. TurnerPreprint
  6. 2020
    Continual Deep Learning by Functional Regularisation of Memorable PastPingbo Pan, Siddharth Swaroop, Alexander Immer … Mohammad Emtiyaz KhanNeurIPS
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  7. 2019
    Continual Learning with Adaptive Weights (CLAW)Tameem Adel, Han Zhao, Richard E. TurnerICLR
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  8. 2019
    Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive ProcessesJames Requeima, Jonathan Gordon, John Bronskill … Richard E. TurnerNeurIPS · University of Cambridge · Google (United States)
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  9. 2019
    Practical Deep Learning with Bayesian PrinciplesKazuki Osawa, Siddharth Swaroop, Anirudh Jain … Mohammad Emtiyaz KhanNeurIPS
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  10. 2019
    Improving and Understanding Variational Continual LearningSiddharth Swaroop, Cuong V. Nguyen, Thang D. Bui, Richard E. TurnerNeurIPS
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  11. 2018
    Partitioned Variational Inference: A unified framework encompassing federated and continual learningThang D. Bui, Cuong V. Nguyen, Siddharth Swaroop, Richard E. TurnerarXiv
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  12. 2018
    Interpretable Continual LearningTameem Adel, C. Nguyen, Richard E. Turner … Adrian WellerPreprint
  13. 2017
    Streaming Sparse Gaussian Process ApproximationsThang D. Bui, Cuong V. Nguyen, Richard E. TurnerNeurIPS · University of Cambridge
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  14. 2017
    Variational Continual Learning in Deep ModelsCuong V Nguyen, Yingzhen Li, Thang D. Bui, Richard E. TurnerPreprint
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.