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.

24 papers of 8,653Sort Recent · Most cited
  1. 2021
    Online Continual Learning Under Domain ShiftQ. Pham, Chenghao Liu, S. HoiPreprint
  2. 2021
  3. 2021
  4. 2021
  5. 2021
  6. 2021
    C-COMA: A Continual Reinforcement Learning Model for Dynamic Multiagent EnvironmentsIncheol Kim, Kyu-Jung Jung, ⋅. I. Kim, 철 정규열†⋅김인Preprint
  7. 2021
  8. 2021
  9. 2021
  10. 2021
    Continual Learning with Memory CascadesD. Kappel, F. Negri, Christian TetzlaffPreprint
  11. 2021
  12. 2021
  13. 2021
  14. 2021
  15. 2021
    Lifelong Robot LearningE. Oztop, Emre UgurPreprint
  16. 2021
    MAML-CL: Edited Model-Agnostic Meta-Learning for Continual LearningMarcin Andrychowicz, Misha Denil, Sergio Gómez … Longxiang GaoPreprint
  17. 2021
  18. 2021
  19. 2021
  20. 2021
  21. 2021
    Supplementary Material: Rectification-based Knowledge Retention for Continual LearningPravendra Singh, Pratik Mazumder, Piyush Rai, Vinay P. NamboodiriPreprint
  22. 2021
    Supplementary Materials for "Generative vs Discriminative: Rethinking The Meta-Continual Learning"Mohammadamin Banayeeanzade, Rasoul Mirzaiezadeh, Hosein Hasani, M. BaghshahPreprint
  23. 2021
    Supplementary: Essentials for Class Incremental LearningSudhanshu Mittal, Silvio Galesso, T. BroxPreprint
  24. 2021
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.