Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

25 papers of 8,653Sort Recent · Most cited
  1. 2020PDF ↗
  2. 2020
    Firefly Neural Architecture Descent: a General Approach for Growing Neural NetworksLemeng Wu, Bo Liu, Peter Stone, Qiang LiuNeurIPS · The University of Texas at Austin
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  3. 2020
    A Combinatorial Perspective on Transfer LearningJianan Wang, Eren Sezener, David Budden … Joel VenessNeurIPS · Google (United States)
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  4. 2020
    Continual Learning in Low-rank Orthogonal SubspacesArslan Chaudhry, Naeemullah Khan, Puneet K. Dokania, Philip H. S. TorrNeurIPS · University of Oxford
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  5. 2020
    Meta-Consolidation for Continual LearningK J Joseph, Vineeth N BalasubramanianNeurIPS · Indian Institute of Technology Hyderabad
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  6. 2020
    La-MAML: Look-ahead Meta Learning for Continual LearningGunshi Gupta, Karmesh Yadav, Liam PaullNeurIPS · Carnegie Mellon University · Université de Montréal
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  7. 2020
    Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without ForgettingJorge A. Mendez, Boyu Wang, Eric EatonNeurIPS · California University of Pennsylvania · University of Pennsylvania · +1
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  8. 2020
    RATT: Recurrent Attention to Transient Tasks for Continual Image CaptioningRiccardo Del Chiaro, Bartłomiej Twardowski, Andrew D. Bagdanov, Joost van de WeijerNeurIPS
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  9. 2020
    Meta-Learning through Hebbian Plasticity in Random NetworksElias Najarro, Sebastian RisiNeurIPS · IT University of Copenhagen
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  10. 2020
    Supermasks in SuperpositionMitchell Wortsman, Vivek Ramanujan, Rosanne Liu … Ali FarhadiNeurIPS
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  11. 2020
    Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian ProcessesMengdi Xu, Wenhao Ding, Jiacheng Zhu … Ding ZhaoNeurIPS · Carnegie Mellon University · Tsinghua University · +1
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  12. 2020
    Learning to Learn with Feedback and Local PlasticityJack Lindsey, Ashok Litwin-KumarNeurIPS · Columbia University
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  13. 2020
    GAN Memory with No ForgettingYulai Cong, Miaoyun Zhao, Jianqiao Li … Lawrence CarinNeurIPS · Duke University
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  14. 2020
    Understanding the Role of Training Regimes in Continual LearningSeyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, Hassan GhasemzadehNeurIPS
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  15. 2020
    Gaussian Gated Linear NetworksDavid Budden, Adam Marblestone, Eren Sezener … Joel VenessNeurIPS · Google (United States)
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  16. 2020
    Coresets via Bilevel Optimization for Continual Learning and StreamingZalán Borsos, Mojmír Mutný, Andreas KrauseNeurIPS · ETH Zurich
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  17. 2020
    Continual Deep Learning by Functional Regularisation of Memorable PastPingbo Pan, Siddharth Swaroop, Alexander Immer … Mohammad Emtiyaz KhanNeurIPS
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  18. 2020
    Dark Experience for General Continual Learning: a Strong, Simple BaselinePietro Buzzega, Matteo Boschini, Angelo Porrello … Simone CalderaraNeurIPS · University of Modena and Reggio Emilia
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  19. 2020
    Continual Learning with Node-Importance based Adaptive Group Sparse RegularizationSangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup MoonNeurIPS · Sungkyunkwan University
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  20. 2020
    Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual LearningM. Caccia, Pau Rodríguez, Оleksiy Ostapenko … Laurent CharlinNeurIPS
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  21. 2020
    Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual LearningMassimo Caccia, Pau Rodríguez López, Oleksiy Ostapenko … Laurent CharlinNeurIPS
  22. 2020
    Organizing recurrent network dynamics by task-computation to enable continual learningLea Duncker, Laura N. Driscoll, K. Shenoy … David SussilloNeurIPS
  23. 2020
    Calibrating CNNs for Lifelong LearningPravendra Singh, V. Verma, Pratik Mazumder … Piyush RaiNeurIPS
  24. 2020
    Mitigating Forgetting in Online Continual Learning via Instance-Aware ParameterizationHung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan … Min SunNeurIPS
  25. 2020
    Continuous Meta-Learning without TasksJ. Michael Harrison, Apoorva Sharma, Chelsea Finn, Marco PavoneNeurIPS · Stanford University · University of California, Berkeley
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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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.