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.

16 papers of 8,653Sort Recent · Most cited
  1. 2024
    Physics-Informed Explainable Continual Learning on GraphsCiyuan Peng, Tao Tang, Qiuyang Yin … Charų C. AggarwalTNNLS · Federation University · Anshan Normal University · +1
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  2. 2024
    Online Active Continual Learning for Robotic Lifelong Object RecognitionXiangli Nie, Zhiguang Deng, Mingdong He … Zheng TangTNNLS · Chinese Academy of Sciences · Beijing Academy of Artificial Intelligence · +5
  3. 2024
    Optimal Adaptive Tracking Control of Partially Uncertain Nonlinear Discrete-Time Systems Using Lifelong Hybrid LearningBehzad Farzanegan, Rohollah Moghadam, S. Jagannathan, N. PappaTNNLS · Missouri University of Science and Technology · California State University, Sacramento · +2
  4. 2024
    Ricci Curvature-Based Graph Sparsification for Continual Graph Representation LearningXikun Zhang, Dongjin Song, Dacheng TaoTNNLS · The University of Sydney · University of Connecticut
  5. 2024
    Lifelong Learning With Cycle Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiTNNLS · Shanghai Zhangjiang Laboratory · Tsinghua University · +5
  6. 2024
    Overcoming Catastrophic Forgetting in Continual Learning by Exploring Eigenvalues of Hessian MatrixYajing Kong, Liu Liu, Huanhuan Chen … Dacheng TaoTNNLS · The University of Sydney · University of Science and Technology of China · +2
  7. 2024
    Lifelong Generative Adversarial AutoencoderFei Ye, Adrian G. BorşTNNLS · University of York
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  8. 2024
    Efficient Bayesian Policy Reuse With a Scalable Observation Model in Deep Reinforcement LearningJinmei Liu, Zhi Wang, Chunlin Chen, Daoyi DongTNNLS · Nanjing University · University of Canberra · +1
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  9. 2024
    Dynamics-Adaptive Continual Reinforcement Learning via Progressive ContextualizationTiantian Zhang, Zichuan Lin, Yuxing Wang … Xiu LiTNNLS · Tencent (China) · Tsinghua University · +1
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  10. 2024
    Uncertainty-Aware Distillation for Semi-Supervised Few-Shot Class-Incremental LearningYawen Cui, Wanxia Deng, Haoyu Chen, Li LiuTNNLS · University of Oulu · National University of Defense Technology
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  11. 2024
    Class-Incremental Learning Method With Fast Update and High Retainability Based on Broad Learning SystemJie Du, Peng Liu, Chi‐Man Vong … C. L. Philip ChenTNNLS · Shenzhen University Health Science Center · University of Macau · +2
  12. 2024
    Open-Ended Online Learning for Autonomous Visual PerceptionHaibin Yu, Yang Cong, Gan Sun … Jiahua DongTNNLS
  13. 2024
    Power Law in Deep Neural Networks: Sparse Network Generation and Continual Learning With Preferential AttachmentFan Feng, Lu Hou, Qi She … James T. KwokTNNLS · City University of Hong Kong · Hong Kong University of Science and Technology
  14. 2024
    Deep Class-Incremental Learning From Decentralized DataXiaohan Zhang, Songlin Dong, Jinjie Chen … Xiaopeng HongTNNLS · Xi'an Jiaotong University · Huawei Technologies (China) · +1
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  15. 2024
    Incremental Embedding Learning With Disentangled Representation TranslationKun Wei, Da Chen, Yuhong Li … Dacheng TaoTNNLS · Xidian University · Alibaba Group (China) · +1
  16. 2024
    Self-Growing Binary Activation Network: A Novel Deep Learning Model With Dynamic ArchitectureZe-Yang Zhang, Yidong Chen, Changle ZhouTNNLS · Xiamen 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. 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.