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.

21 papers of 11,817Sort Recent · Most cited
  1. 2024
    Statistical Context Detection for Deep Lifelong Reinforcement LearningJeffery Dick, Saptarshi Nath, Christos Peridis … Andrea SoltoggioCoLLAs
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  2. 2024
    A collective AI via lifelong learning and sharing at the edgeAndrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman … Soheil KolouriNature Machine Intelligence
  3. 2023
    CovarNav: Machine Unlearning via Model Inversion and Covariance NavigationAli Abbasi, Chayne Thrash, Elaheh Akbari … Soheil KolouriarXiv
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  4. 2023
    BrainWash: A Poisoning Attack to Forget in Continual LearningAli Abbasi, Parsa Nooralinejad, Hamed Pirsiavash, Soheil KolouriCVPR
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  5. 2023
    Sharing Lifelong Reinforcement Learning Knowledge via Modulating MasksSaptarshi Nath, Christos Peridis, Eseoghene Ben-Iwhiwhu … Andrea SoltoggioCoLLAs
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  6. 2022
    Is Multi-Task Learning an Upper Bound for Continual Learning?Zihao Wu, Huy Tran, Hamed Pirsiavash, Soheil KolouriICASSP · Vanderbilt University · University of California, Davis
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  7. 2023PDF ↗
  8. 2023
    A Domain-Agnostic Approach for Characterization of Lifelong Learning SystemsMegan M. Baker, Alexander New, Mario Aguilar-Simon … Gautam K. VallabhaNeural Networks
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  9. 2023
    Multi-Agent Lifelong Implicit Neural LearningSoheil Kolouri, Ali Abbasi, Soroush Abbasi Koohpayegani … Hamed PirsiavashIEEE Signal Processing Letters
  10. 2022
    Lifelong Reinforcement Learning with Modulating MasksEseoghene Ben-Iwhiwhu, Saptarshi Nath, Praveen K. Pilly … Andrea SoltoggioTrans. Mach. Learn. Res.
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  11. 2022
    Biological underpinnings for lifelong learning machinesDhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb … Hava T. SiegelmannNature Machine Intelligence · The University of Texas at San Antonio · Intelligent Systems Research (United States) · +24
  12. 2022
    Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural ActivationsAli Abbasi, Parsa Nooralinejad, Vladimir Braverman … Soheil KolouriCoLLAs
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  13. 2021
    Lifelong Learning with Sketched Structural RegularizationHaoran Li, Aditya Krishnan, Jingfeng Wu … Vladimir BravermanMachine Learning
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  14. 2020
    Detecting Changes and Avoiding Catastrophic Forgetting in Dynamic Partially Observable EnvironmentsJeffery Dick, Paweł Ładosz, Eseoghene Ben-Iwhiwhu … Andrea SoltoggioFrontiers · Loughborough University · Teikyo University · +1
  15. 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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  16. 2019
    Collaborative Learning Through Shared Collective Knowledge and Local ExpertiseJavad Mohammadi, Soheil KolouriIEEE 29th International Workshop on Machine Learning for… · Carnegie Mellon University · HRL Laboratories (United States)
  17. 2019
    Complementary Learning for Overcoming Catastrophic Forgetting Using Experience ReplayMohammad Rostami, Soheil Kolouri, Praveen K. PillyIJCAI · California University of Pennsylvania · University of Pennsylvania · +1
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  18. 2019
    Continual Learning Using World Models for Pseudo-RehearsalNicholas A. Ketz, Soheil Kolouri, Praveen K. PillyPreprint
  19. 2019
    Using World Models for Pseudo-Rehearsal in Continual LearningNicholas Ketz, Soheil Kolouri, Praveen K. PillyarXiv · HRL Laboratories (United States)
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  20. 2019
    Attention-Based Structural-PlasticitySoheil Kolouri, Nicholas Ketz, Xinyun Zou … Praveen K. PillyarXiv · HRL Laboratories (United States)
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  21. 2017
    Multi-Agent Distributed Lifelong Learning for Collective Knowledge AcquisitionMohammad Rostami, Soheil Kolouri, Kyungnam Kim, Eric EatonAdaptive Agents and Multi-Agent Systems · University of Pennsylvania · HRL Laboratories (United States)
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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.