Continual Learning

Continual Learning is a machine learning paradigm in which a model (or autonomous agent) learns from a non-stationary stream of data or sequence of tasks by updating its parameters incrementally over time while retaining and integrating previously acquired knowledge without having simultaneous access to all past data.

1.4K

Publications

106.1K

Citations

4.1K

Authors

970

Institutions

Publications per year

2017–2026

1K

Authors

4.1K

  1. VL
    Vincenzo Lomonaco

    University of Bologna, Italy

    29 publications · 1.9K citations

    20

    h-index

  2. DM
    Davide Maltoni

    University of Bologna, Italy

    20 publications · 1.5K citations

    17

    h-index

  3. BL
    Bing Liu

    China University of Mining and Technology, China

    14 publications · 570 citations

    14

    h-index

  4. TT
    Tinne Tuytelaars

    KU Leuven, Belgium

    14 publications · 3.7K citations

    13

    h-index

  5. RA
    Rahaf Aljundi

    KU Leuven, Belgium

    12 publications · 2.9K citations

    12

    h-index

1–5 of 4.1K

Venues

  1. arXiv (Cornell University)

    Repository · 290 publications · 14.9K citations

    58

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 35 publications · 3.1K citations

    26

    h-index

  3. 24

    h-index

  4. Neurocomputing

    26 publications · 1.4K citations

    22

    h-index

  5. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 25 publications · 3.8K citations

    22

    h-index

1–5