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.

311 papers of 8,653 · showing 251–300Sort Recent · Most cited
  1. 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
    PDF ↗
  2. 2020
    RATT: Recurrent Attention to Transient Tasks for Continual Image CaptioningRiccardo Del Chiaro, Bartłomiej Twardowski, Andrew D. Bagdanov, Joost van de WeijerNeurIPS
    PDF ↗
  3. 2020
    Meta-Learning through Hebbian Plasticity in Random NetworksElias Najarro, Sebastian RisiNeurIPS · IT University of Copenhagen
    PDF ↗
  4. 2021PDF ↗
  5. 2020
    Supermasks in SuperpositionMitchell Wortsman, Vivek Ramanujan, Rosanne Liu … Ali FarhadiNeurIPS
    PDF ↗
  6. 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
    PDF ↗
  7. 2020
    Learning to Learn with Feedback and Local PlasticityJack Lindsey, Ashok Litwin-KumarNeurIPS · Columbia University
    PDF ↗
  8. 2020
    GAN Memory with No ForgettingYulai Cong, Miaoyun Zhao, Jianqiao Li … Lawrence CarinNeurIPS · Duke University
    PDF ↗
  9. 2020
    Understanding the Role of Training Regimes in Continual LearningSeyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, Hassan GhasemzadehNeurIPS
    PDF ↗
  10. 2020
    Gaussian Gated Linear NetworksDavid Budden, Adam Marblestone, Eren Sezener … Joel VenessNeurIPS · Google (United States)
    PDF ↗
  11. 2020
    Coresets via Bilevel Optimization for Continual Learning and StreamingZalán Borsos, Mojmír Mutný, Andreas KrauseNeurIPS · ETH Zurich
    PDF ↗
  12. 2020
    Continual Deep Learning by Functional Regularisation of Memorable PastPingbo Pan, Siddharth Swaroop, Alexander Immer … Mohammad Emtiyaz KhanNeurIPS
    PDF ↗
  13. 2020
    Dark Experience for General Continual Learning: a Strong, Simple BaselinePietro Buzzega, Matteo Boschini, Angelo Porrello … Simone CalderaraNeurIPS · University of Modena and Reggio Emilia
    PDF ↗
  14. 2020
    Continual Learning with Node-Importance based Adaptive Group Sparse RegularizationSangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup MoonNeurIPS · Sungkyunkwan University
    PDF ↗
  15. 2020
    Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual LearningM. Caccia, Pau Rodríguez, Оleksiy Ostapenko … Laurent CharlinNeurIPS
    PDF ↗
  16. 2020
    Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual LearningMassimo Caccia, Pau Rodríguez López, Oleksiy Ostapenko … Laurent CharlinNeurIPS
  17. 2020
    Organizing recurrent network dynamics by task-computation to enable continual learningLea Duncker, Laura N. Driscoll, K. Shenoy … David SussilloNeurIPS
  18. 2020
    Calibrating CNNs for Lifelong LearningPravendra Singh, V. Verma, Pratik Mazumder … Piyush RaiNeurIPS
  19. 2020
    Mitigating Forgetting in Online Continual Learning via Instance-Aware ParameterizationHung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan … Min SunNeurIPS
  20. 2020
    Continuous Meta-Learning without TasksJ. Michael Harrison, Apoorva Sharma, Chelsea Finn, Marco PavoneNeurIPS · Stanford University · University of California, Berkeley
    PDF ↗
  21. 2019
    Random Path Selection for Continual LearningJathushan Rajasegaran, Munawar Hayat, Salman Hameed Khan … Ling ShaoNeurIPS
  22. 2019
    Continual Unsupervised Representation LearningDushyant Rao, Francesco Visin, Andrei Rusu … Raia HadsellNeurIPS · Carnegie Mellon University · Google (United States) · +2
    PDF ↗
  23. 2019
    Compacting, Picking and Growing for Unforgetting Continual LearningSteven C. Y. Hung, Cheng-Hao Tu, Cheng‐En Wu … Chu-Song ChenNeurIPS
    PDF ↗
  24. 2021
    BooVAE: Boosting Approach for Continual Learning of VAEAnna Kuzina, Evgenii Egorov, Evgeny BurnaevNeurIPS · Yandex (Russia) · Skolkovo Institute of Science and Technology
    PDF ↗
  25. 2019
    Visualizing the PHATE of Neural NetworksScott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal MishneNeurIPS · Yale University · Princeton University · +1
    PDF ↗
  26. 2019
    Episodic Memory in Lifelong Language LearningCyprien de Masson d’Autume, Sebastian Ruder, Lingpeng Kong, Dani YogatamaNeurIPS
    PDF ↗
  27. 2019
    Random Path Selection for Incremental LearningJathushan Rajasegaran, Munawar Hayat, Salman Hameed Khan … Ling ShaoNeurIPS
  28. 2019
    An Adaptive Random Path Selection Approach for Incremental Learning.Jathushan Rajasegaran, Munawar Hayat, Salman Khan … Ming–Hsuan YangNeurIPS
    PDF ↗
  29. 2019
    Meta-Learning Representations for Continual LearningKhurram Javed, Martha WhiteNeurIPS · University of Alberta
    PDF ↗
  30. 2019
    Uncertainty-based Continual Learning with Adaptive RegularizationHongjoon Ahn, Sungmin Cha, Dong-Gyu Lee, Taesup MoonNeurIPS · Sungkyunkwan University
    PDF ↗
  31. 2019
    Improving and Understanding Variational Continual LearningSiddharth Swaroop, Cuong V. Nguyen, Thang D. Bui, Richard E. TurnerNeurIPS
    PDF ↗
  32. 2019
    Three scenarios for continual learningGido M. van de Ven, Andreas S. ToliasNeurIPS
    PDF ↗
  33. 2019
    Gradient based sample selection for online continual learningRahaf Aljundi, Min Lin, Baptiste Goujaud, Yoshua BengioNeurIPS · KU Leuven · National University of Singapore · +1
    PDF ↗
  34. 2019
    Continual Learning in PracticeTom Diethe, Tom Borchert, Eno Thereska … Neil D. LawrenceNeurIPS · Amazon (Germany)
    PDF ↗
  35. 2019
    A Unifying Bayesian View of Continual LearningSebastian Farquhar, Yarin GalNeurIPS · University of Oxford
    PDF ↗
  36. 2019
    Superposition of Many Models into OneBrian Cheung, A. L. Terekhov, Yubei Chen … Bruno A. OlshausenNeurIPS · University of California, Berkeley
    PDF ↗
  37. 2019
  38. 2019
  39. 2019
  40. 2019
    Reconciling meta-learning and continual learning with online mixtures of tasksGhassen Jerfel, Erin Grant, T. Griffiths, K. HellerNeurIPS
  41. 2018PDF ↗
  42. 2019
    Experience Replay for Continual LearningDavid Rolnick, Arun Ahuja, Jonathan Schwarz … Greg WayneNeurIPS · California University of Pennsylvania · University of Pennsylvania · +1
    PDF ↗
  43. 2018
    Continual Classification Learning Using Generative ModelsFrantzeska Lavda, Jason Ramapuram, Magda Gregorová, Alexandros KalousisNeurIPS
    PDF ↗
  44. 2018
    Life-Long Disentangled Representation Learning with Cross-Domain Latent HomologiesAlessandro Achille, Tom Eccles, Löıc Matthey … Irina HigginsNeurIPS
    PDF ↗
  45. 2018
    Reinforced Continual LearningJu Xu, Zhanxing ZhuNeurIPS
    PDF ↗
  46. 2018
    Distributed Weight Consolidation: A Brain Segmentation Case StudyPatrick McClure, Charles Zheng, Jakub Kaczmarzyk … Francisco PereiraNeurIPS · National Institutes of Health · Massachusetts Institute of Technology
    PDF ↗
  47. 2018
    Online Structured Laplace Approximations For Overcoming Catastrophic ForgettingHippolyt Ritter, Aleksandar Botev, David BarberNeurIPS
    PDF ↗
  48. 2018
    HOUDINI: Lifelong Learning as Program SynthesisLazar Valkov, Dipak Chaudhari, Akash Srivastava … Swarat ChaudhuriNeurIPS · Indian Institute of Technology Bombay · IBM (United States) · +2
    PDF ↗
  49. 2018
    Task Agnostic Continual Learning Using Online Variational BayesChen Zeno, Itay Golan, Elad Hoffer, Daniel SoudryNeurIPS
    PDF ↗
  50. 2017
    Gradient Episodic Memory for Continual LearningDavid López-Paz, Marc’Aurelio RanzatoNeurIPS · Max Planck Society · Max Planck Innovation · +1
    PDF ↗
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.