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.

10 papers of 11,817Sort Recent · Most cited
  1. 2019
    Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversionHongxu Yin, Pavlo Molchanov, Jose M. Álvarez … Jan KautzCVPR · Princeton University · University of Illinois Urbana-Champaign
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  2. 2019
    Maintaining Discrimination and Fairness in Class Incremental LearningBowen Zhao, Xi Xiao, Guojun Gan … Shu‐Tao XiaCVPR · Peng Cheng Laboratory · Tsinghua University
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  3. 2019
    Lifelong Machine Learning with Deep Streaming Linear Discriminant AnalysisTyler L. Hayes, Christopher KananCVPR · Rochester Institute of Technology
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  4. 2019
    Rehearsal-Free Continual Learning over Small Non-I.I.D. BatchesVincenzo Lomonaco, Davide Maltoni, Lorenzo PellegriniCVPR · University of Bologna
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  5. 2019
    Sequential Mastery of Multiple Visual Tasks: Networks Naturally Learn to Learn and Forget to ForgetGuy Davidson, Michael C. MozerCVPR · Supélec · University of Applied Sciences and Arts of Southern Switzerland · +2
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  6. 2019
    Large Scale Incremental LearningYue Wu, Yinpeng Chen, Lijuan Wang … Yun FuCVPR · Northeastern University · Universidad del Noreste · +2
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  7. 2019
    Learning a Unified Classifier Incrementally via RebalancingSaihui Hou, Xinyu Pan, Chen Change Loy … Dahua LinCVPR · University of Science and Technology of China · XLAB (Slovenia) · +3
  8. 2019
    Learning to Remember: A Synaptic Plasticity Driven Framework for Continual LearningOleksiy Ostapenko, Mihai Puscas, Tassilo Klein … Moin NabiCVPR · Humboldt-Universität zu Berlin · University of Trento · +1
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  9. 2019
    Incremental Object Learning From Contiguous ViewsStefan Stojanov, Samarth Mishra, Ngoc Anh Thai … James M. RehgCVPR · Georgia Institute of Technology · Indiana University Bloomington
  10. 2019
    Uncertainty-Guided Continual Learning in Bayesian Neural Networks - Extended AbstractSayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus RohrbachCVPR
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.