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.

7 papers of 8,653Sort Recent · Most cited
  1. 2023
    Semi-Supervised Generalized Source-Free Domain Adaptation (SSG-SFDA)Jiayu An, Changming Zhao, Dongrui WuIJCNN · Huazhong University of Science and Technology
  2. 2023
    Continual Learning with Pretrained Backbones by Tuning in the Input SpaceSimone Marullo, Matteo Tiezzi, Marco Gori … Tinne TuytelaarsIJCNN · University of Siena · University of Florence · +1
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  3. 2023
    Non-exemplar Class-incremental Learning via Dual Augmentation and Dual DistillationKe Song, Quan Xia, Zhaoyong QiuIJCNN · Northwestern Polytechnical University
  4. 2023
    Deep Inversion Method for Attacking Lifelong Learning Neural NetworksBoyuan Du, Yuanlong Yu, Huaping LiuIJCNN · Fuzhou University · Tsinghua University
  5. 2023
    Online Continual Learning for Control of Mobile RobotsAndriy Sarabakha, Zhongzheng Qiao, Savitha Ramasamy, Ponnuthurai Nagaratnam SuganthanIJCNN · Nanyang Technological University · Agency for Science, Technology and Research · +2
  6. 2023
    Angular Penalty for Few-Shot Incremental 3D Object LearningBingtao Ma, Yang CongIJCNN · Shenyang Institute of Automation · Chinese Academy of Sciences · +1
  7. 2023
    Deep Hashing Capable of Adding New Dataset without Class LabelsYe Chenyang, Hisashi KogaIJCNN · University of Electro-Communications
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.