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. 2019
    Lifelong Neural Predictive Coding: Learning Cumulatively Online without ForgettingAlex Ororbia, Ankur Mali, C Lee Giles, Daniel KiferNeurIPS
    PDF ↗
  2. 2019
    Random Path Selection for Continual LearningJathushan Rajasegaran, Munawar Hayat, Salman Hameed Khan … Ling ShaoNeurIPS
  3. 2019
    Self-supervised GAN: Analysis and Improvement with Multi-class Minimax GameNgoc-Trung Tran, Viet-Hung Tran, Ngoc-Bao Nguyen … Ngai‐Man CheungNeurIPS
    PDF ↗
  4. 2019
    Continual Unsupervised Representation LearningDushyant Rao, Francesco Visin, Andrei Rusu … Raia HadsellNeurIPS · Carnegie Mellon University · Google (United States) · +2
    PDF ↗
  5. 2019
    Compacting, Picking and Growing for Unforgetting Continual LearningSteven C. Y. Hung, Cheng-Hao Tu, Cheng‐En Wu … Chu-Song ChenNeurIPS
    PDF ↗
  6. 2019
    BooVAE: Boosting Approach for Continual Learning of VAEAnna Kuzina, E. Egorov, Evgeny BurnaevNeurIPS
    PDF ↗
  7. 2019
    Visualizing the PHATE of Neural NetworksScott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal MishneNeurIPS · Yale University · Princeton University · +1
    PDF ↗
  8. 2019
    Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive ProcessesJames Requeima, Jonathan Gordon, John Bronskill … Richard E. TurnerNeurIPS · University of Cambridge · Google (United States)
    PDF ↗
  9. 2019
    Practical Deep Learning with Bayesian PrinciplesKazuki Osawa, Siddharth Swaroop, Anirudh Jain … Mohammad Emtiyaz KhanNeurIPS
    PDF ↗
  10. 2019
    Episodic Memory in Lifelong Language LearningCyprien de Masson d’Autume, Sebastian Ruder, Lingpeng Kong, Dani YogatamaNeurIPS
    PDF ↗
  11. 2019
    Random Path Selection for Incremental LearningJathushan Rajasegaran, Munawar Hayat, Salman Hameed Khan … Ling ShaoNeurIPS
  12. 2019
    An Adaptive Random Path Selection Approach for Incremental Learning.Jathushan Rajasegaran, Munawar Hayat, Salman Khan … Ming–Hsuan YangNeurIPS
    PDF ↗
  13. 2019
    Meta-Learning Representations for Continual LearningKhurram Javed, Martha WhiteNeurIPS · University of Alberta
    PDF ↗
  14. 2019
    Uncertainty-based Continual Learning with Adaptive RegularizationHongjoon Ahn, Sungmin Cha, Dong-Gyu Lee, Taesup MoonNeurIPS · Sungkyunkwan University
    PDF ↗
  15. 2019
    Improving and Understanding Variational Continual LearningSiddharth Swaroop, Cuong V. Nguyen, Thang D. Bui, Richard E. TurnerNeurIPS
    PDF ↗
  16. 2019
    Gradient based sample selection for online continual learningRahaf Aljundi, Min Lin, Baptiste Goujaud, Yoshua BengioNeurIPS · KU Leuven · National University of Singapore · +1
    PDF ↗
  17. 2019
    Convolution with even-sized kernels and symmetric paddingShuang Wu, Guanrui Wang, Pei Tang … Luping ShiNeurIPS
    PDF ↗
  18. 2019
    Continual Learning in PracticeTom Diethe, Tom Borchert, Eno Thereska … Neil D. LawrenceNeurIPS · Amazon (Germany)
    PDF ↗
  19. 2019
  20. 2019
  21. 2019
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.