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.

19 papers of 6,984Sort Recent · Most cited
  1. 2023
    Task-Distributionally Robust Data-Free Meta-LearningZixuan Hu, Yongxian Wei, Li Shen … Dacheng TaoTPAMI · Nanyang Technological University · Tsinghua–Berkeley Shenzhen Institute · +6
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  2. 2023
    Distributionally Robust Memory Evolution With Generalized Divergence for Continual LearningZhenyi Wang, Li Shen, Tiehang Duan … Mingchen GaoTPAMI · University of Maryland, College Park · Jingdong (China) · +2
  3. 2023
    Incremental Learning for Simultaneous Augmentation of Feature and ClassChenping Hou, Shilin Gu, Chao Xu, Yuhua QianTPAMI · National University of Defense Technology · Shanxi University
  4. 2023
  5. 2023
    Cross Domain Lifelong Learning Based on Task SimilarityShuojin Yang, Zhanchuan CaiTPAMI · Macau University of Science and Technology
  6. 2023PDF ↗
  7. 2023
    Learnable Distribution Calibration for Few-Shot Class-Incremental LearningBinghao Liu, Boyu Yang, Lingxi Xie … Qixiang YeTPAMI · University of Chinese Academy of Sciences · Huawei Technologies (China)
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  8. 2023
    Variational Data-Free Knowledge Distillation for Continual LearningXiaorong Li, Shipeng Wang, Jian Sun, Zongben XuTPAMI · Xi'an Jiaotong University
  9. 2023
    CRNet: A Fast Continual Learning Framework With Random TheoryDepeng Li, Zhigang ZengTPAMI · Beijing Academy of Artificial Intelligence
  10. 2023
    Continual Image Deraining With Hypergraph Convolutional NetworksXueyang Fu, Jie Xiao, Yurui Zhu … Zheng-Jun ZhaTPAMI · University of Science and Technology of China
  11. 2023
    Multi-Label Classification via Adaptive Resonance Theory-Based ClusteringNaoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao IshibuchiTPAMI · Osaka Metropolitan University · University of Malaya · +1
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  12. 2023
    Class-Incremental Continual Learning Into the eXtended DER-VerseMatteo Boschini, Lorenzo Bonicelli, Pietro Buzzega … Simone CalderaraTPAMI · University of Modena and Reggio Emilia
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  13. 2023
    Few-Shot Class-Incremental Learning by Sampling Multi-Phase TasksDa-Wei Zhou, Han-Jia Ye, Liang Ma … De-Chuan ZhanTPAMI · Nanjing University
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  14. 2023
    Hierarchical Prototype Networks for Continual Graph Representation LearningXikun Zhang, Dongjin Song, Dacheng TaoTPAMI · The University of Sydney · University of Connecticut
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  15. 2023
    Dynamic Support Network for Few-Shot Class Incremental LearningBoyu Yang, Mingbao Lin, Yunxiao Zhang … Qixiang YeTPAMI · University of Chinese Academy of Sciences · Xiamen University · +2
  16. 2023
    Uncertainty-aware Contrastive Distillation for Incremental Semantic SegmentationGuanglei Yang, Enrico Fini, Dan Xu … Elisa RicciTPAMI · Harbin Institute of Technology · University of Trento · +2
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  17. 2023
    Continual Learning for Blind Image Quality AssessmentWeixia Zhang, Dingquan Li, Chao Ma … Kede MaTPAMI · Shanghai Jiao Tong University · Peng Cheng Laboratory · +1
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  18. 2023
    Meta-Reinforcement Learning in Non-Stationary and Dynamic EnvironmentsZhenshan Bing, David Lerch, Kai Huang, Alois KnollTPAMI · Technical University of Munich · Sun Yat-sen University · +1
  19. 2023
    Dynamic Self-Supervised Teacher-Student Network LearningFei Ye, Adrian G. BorşTPAMI · University of York
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.