Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 6,984Sort Recent · Most cited
  1. 2023
    AdaER: An Adaptive Experience Replay Approach for Continual Lifelong LearningXingyu Li, Bo Tang, Haifeng LiNeurocomputing · Tulane University · Worcester Polytechnic Institute · +1
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  2. 2023
    Class Incremental Learning based on Identically Distributed Parallel One-Class ClassifiersWenju Sun, Qingyong Li, Jing Zhang … Yangli‐ao GengNeurocomputing · Beijing Jiaotong University
  3. 2023
    GFR: Generic feature representations for class incremental learningZhichuan Wang, Linfeng Xu, Zihuan Qiu … Hongliang LiNeurocomputing · University of Electronic Science and Technology of China
  4. 2023
    Continuous transfer of neural network representational similarity for incremental learningSongsong Tian, Weijun Li, Xin Ning … Prayag TiwariNeurocomputing · Chinese Academy of Sciences · Institute of Semiconductors · +2
  5. 2023
    Mutual mentor: Online contrastive distillation network for general continual learningQiang Wang, Zhong Ji, Jin Li, Yanwei PangNeurocomputing · Tianjin University · Shanghai Center for Brain Science and Brain-Inspired Technology
  6. 2023
    Projected Latent Distillation for Data-Agnostic Consolidation in Distributed Continual LearningAntonio Carta, Andrea Cossu, Vincenzo Lomonaco … Joost van de WeijerNeurocomputing
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  7. 2023
    Task-aware network: Mitigation of task-aware and task-free performance gap in online continual learningYong Woo Hong, Hyeran Byun, Sungho ParkNeurocomputing · Yonsei University
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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.