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.

12 papers of 11,817Sort Recent · Most cited
  1. 2019
    Using Hindsight to Anchor Past Knowledge in Continual LearningArslan Chaudhry, Albert Gordo, Puneet K. Dokania … David López-PazAAAI · University of Oxford · Meta (Israel)
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  2. 2019
    Gated Linear NetworksJoel Veness, Tor Lattimore, David Budden … Marcus HütterAAAI · Google DeepMind (United Kingdom)
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  3. 2019
    Towards Making the Most of BERT in Neural Machine TranslationJiacheng Yang, Mingxuan Wang, Hao Zhou … Lei LiAAAI · Shanghai Jiao Tong University
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  4. 2019
    Proximal Distilled Evolutionary Reinforcement LearningCristian Bodnar, Ben Day, Píetro LióAAAI · University of Cambridge
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  5. 2019
    Just Ask: An Interactive Learning Framework for Vision and Language NavigationTa-Chung Chi, Minmin Shen, Mihail Eric … Dilek Hakkani-TürAAAI · Carnegie Mellon University
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  6. 2019
    Overcoming Catastrophic Forgetting by Neuron-level Plasticity ControlInyoung Paik, Sangjun Oh, Tae-Yeong Kwak, Injung KimAAAI · Handong Global University
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  7. 2019
    Generative Continual Concept LearningMohammad Rostami, Soheil Kolouri, Praveen K. Pilly, James L. McClellandAAAI · California University of Pennsylvania · HRL Laboratories (United States) · +1
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  8. 2019
    DeGAN : Data-Enriching GAN for Retrieving Representative Samples from a Trained ClassifierSravanti Addepalli, Gaurav Kumar Nayak, Anirban Chakraborty, Venkatesh Babu RadhakrishnanAAAI · Indian Institute of Science Bangalore
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  9. 2019
    Lifelong Learning with a Changing Action SetYash Chandak, Georgios Theocharous, Chris Nota, Philip S. ThomasAAAI · University of Massachusetts Amherst · Adobe Systems (United States)
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  10. 2019
    Incremental multi-domain learning with network latent tensor factorizationAdrian Bulat, Jean Kossaifi, Georgios Tzimiropoulos, Maja PantićAAAI · Samsung (United States)
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  11. 2019
    Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural NetworksYadan Luo, Zi Huang, Zheng Zhang … Yang YangAAAI · The University of Queensland · Harbin Institute of Technology · +1
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  12. 2019
    Gamma-Nets: Generalizing Value Estimation over TimescaleCraig Sherstan, Shibhansh Dohare, James MacGlashan … Patrick M. PilarskiAAAI · University of Alberta
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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.