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.

23 papers of 11,817Sort Recent · Most cited
  1. 2022
    Rethinking Few-Shot Class-Incremental Learning With Open-Set Hypothesis in Hyperbolic GeometryYawen Cui, Zitong Yu, Wei Peng … Li LiuIEEE Trans. Multimedia · University of Oulu · Great Bay University · +3
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  2. 2022
    Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable SimulationMengxi Li, Rika Antonova, Dorsa Sadigh, Jeannette BohgICRA · Stanford University
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  3. 2022
    Representational drift: Emerging theories for continual learning and experimental future directions.Laura Driscoll, Lea Duncker, Christopher D. HarveyCurrent Opinion in Neurobiology · Stanford University · Howard Hughes Medical Institute · +1
  4. 2021
    Rethinking Architecture Design for Tackling Data Heterogeneity in Federated LearningLiangqiong Qu, Yuyin Zhou, Paul Pu Liang … Daniel L. RubinCVPR · Stanford University · University of California, Santa Cruz · +2
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  5. 2021
    Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic EnvironmentsAbhiram Iyer, Karan Grewal, Akash Velu … Subutai AhmadFrontiers · Carnegie Mellon University · Stanford University · +1
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  6. 2021
    From partners to populations: A hierarchical Bayesian account of coordination and conventionRobert D. Hawkins, Michael Franke, Michael C. Frank … Noah D. GoodmanPsychological Review · Princeton University · Osnabrück University · +3
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  7. 2021
    DyStaB: Unsupervised Object Segmentation via Dynamic-Static Bootstrapping*Yanchao Yang, Brian Lai, Stefano SoattoCVPR · Stanford University
  8. 2020
    Reset-Free Lifelong Learning with Skill-Space PlanningKevin Lü, Aditya Grover, Pieter Abbeel, Igor MordatchICLR · University of California, Berkeley · Stanford University · +1
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  9. 2020
    An Efficient ADMM-Aided Deep Learning-Based Signal Detector for Uplink Massive MIMOHongji Huang, J.M. Cioffi, Seyyed Ali HashemiIEEE International Conference on Communications Workshops… · Massachusetts Institute of Technology · Stanford University
  10. 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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  11. 2019
    Model primitives for hierarchical lifelong reinforcement learningBohan Wu, Jayesh K. Gupta, Mykel J. KochenderferAutonomous Agents and Multi-Agent Systems · Columbia University · Stanford University
  12. 2019
    Continual Adaptation for Efficient Machine CommunicationRobert D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. GoodmanCoNLL · Princeton University · Department of Physics, Mathematics and Informatics · +1
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  13. 2019
    Continuous Meta-Learning without TasksJ. Michael Harrison, Apoorva Sharma, Chelsea Finn, Marco PavonearXiv · Stanford University · University of California, Berkeley
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  14. 2020
    Generative Memory for Lifelong LearningXin Su, Shangqi Guo, Tian Tan, Feng ChenTNNLS · Beijing Advanced Sciences and Innovation Center · Tsinghua University · +1
  15. 2019
    Continual learning improves Internet video streamingFrancis Y. Yan, Hudson Ayers, Chenzhi Zhu … Keith WinsteinNetworked Systems Design and Implementation · Stanford University · Tsinghua University
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  16. 2019
    Online Meta-LearningChelsea Finn, Aravind Rajeswaran, Sham M. Kakade, Sergey LevineICML · Stanford University · University of Washington · +3
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  17. 2019
    Task representations in neural networks trained to perform many cognitive tasksGuangyu Robert Yang, Madhura R. Joglekar, Hui Song … Xiao‐Jing WangNature Neuroscience · New York University · Columbia University · +5
  18. 2018
    Learning to Learn without Forgetting By Maximizing Transfer and Minimizing InterferenceMatthew Riemer, Ignacio Cases, Robert Ajemian … Gerald TesauroICLR · IBM (United States) · Stanford University · +2
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  19. 2017
    Trial without Error: Towards Safe Reinforcement Learning via Human InterventionWilliam S. Saunders, Girish Sastry, Andreas Stuhlmüller, Owain EvansAdaptive Agents and Multi-Agent Systems · University of Oxford · Stanford University
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  20. 2017
    Modular Continual Learning in a Unified Visual EnvironmentKevin Feigelis, Blue Sheffer, Daniel YaminsICLR · Rutgers, The State University of New Jersey · Stanford University
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  21. 2017
    Improved multitask learning through synaptic intelligenceFriedemann Zenke, Ben Poole, Surya GanguliarXiv · Stanford University
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  22. 2016
    Spatially Regularized Streaming Sensor SelectionChangsheng Li, Wei Fan, Weishan Dong … Xin ZhangAAAI · IBM Research (China) · Stanford University · +3
  23. 2015
    Modeling dative alternations of individual childrenAntal van den Bosch, Joan BresnanSixth Workshop on Cognitive Aspects of Computational Lang… · Radboud University Nijmegen · Radboud University Medical Center · +2
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.