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.

20 papers of 11,817Sort Recent · Most cited
  1. 2026
    DC Shipboard Microgrid Control Using Online Multilayer Neural Network Lifelong LearningMohsenizonoozi Shahed, Behzad Farzanegan, S. JagannathanAmerican Control Conference
  2. 2026
  3. 2026
  4. 2025
  5. 2025
  6. 2025
    Safe Optimal Control of Quadrotor Formations Using Multilayer Neural Networks and Continual LearningEhsan Soleimani, Irfan Ahmad Ganie, S. JagannathanInternational Journal of Adaptive Control and Signal Proc…
  7. 2024
    Lifelong Safe Optimal Adaptive Tracking Control of Nonlinear Strict‐Feedback Discrete‐Time SystemsBehzad Farzanegan, S. JagannathanInternational Journal of Adaptive Control and Signal Proc…
  8. 2024
    Online Continual Safe Reinforcement Learning-based Optimal Control of Mobile Robot FormationsI. Ganie, S. JagannathanConference on Control Technology and Applications
  9. 2024
  10. 2024
    Optimal Tracking of Uncertain Linear Discrete-Time Systems Using Trajectory-Dependent Lifelong Q-learningMaxwell Geiger, Vignesh Narayanan, S. JagannathanAmerican Control Conference
  11. 2024
  12. 2024
  13. 2024
  14. 2023
  15. 2023
  16. 2023
  17. 2023
  18. 2023
  19. 2023
  20. 2022
    Optimal Adaptive Output Regulation of Uncertain Nonlinear Discrete-time Systems using Lifelong Concurrent LearningRohollah Moghadam, Behzad Farzanegan, S. Jagannathan, Ponnammal NatarajanIEEE 61st Conference on Decision and Control (CDC) · California State University, Sacramento · Missouri University of Science and Technology · +1
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.