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.

112 papers of 8,653 · showing 51–100Sort Recent · Most cited
  1. 2018
    Enhancing CNN Incremental Learning Capability with an Expanded NetworkShanshan Cai, Zhuwei Xu, Zhichao Huang … C.‐C. Jay KuoIEEE International Conference on Multimedia and Expo (ICME) · University of Southern California · Tsinghua University
  2. 2018
    Fast Factorization-free Kernel Learning for Unlabeled Chunk Data StreamsYi Wang, Nan Xue, Xin Fan … Zhongxuan LuoIJCAI · Dalian University of Technology · University of Rochester
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  3. 2018
    Lifelong Metric LearningGan Sun, Yang Cong, Ji Liu … Haibin YuIEEE Trans. Cybernetics · Shenyang Institute of Automation · University of Chinese Academy of Sciences · +3
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  4. 2018
    Evaluating and Characterizing Incremental Learning from Non-Stationary DataAlejandro Cervantes, Christian Gagné, Pedro Isasi, Marc ParizeauarXiv
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  5. 2018
    Meta Continual LearningRisto Vuorio, Dong-Yeon Cho, Daejoong Kim, Jiwon KimarXiv
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  6. 2018PDF ↗
  7. 2018
    PackNet: Adding Multiple Tasks to a Single Network by Iterative PruningArun Mallya, Svetlana LazebnikCVPR · University of Illinois Urbana-Champaign
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  8. 2018
    New Metrics and Experimental Paradigms for Continual LearningTyler L. Hayes, Ronald Kemker, Nathan D. Cahill, Christopher KananCVPR · Rochester Institute of Technology
  9. 2018
    Subset Replay Based Continual Learning for Scalable Improvement of Autonomous SystemsPratik Prabhanjan Brahma, Adrienne OthonCVPR · Volkswagen Group (United States)
  10. 2018
    Adaptive Matrix Sketching and Clustering for Semisupervised Incremental LearningZilin Zhang, Yan Li, Zhengwen Zhang … Meiguo GaoIEEE Signal Processing Letters · Beijing Institute of Technology
  11. 2018
    Learn to Detect Objects IncrementallyLinting Guan, Yan Wu, Junqiao Zhao, Chen YeIEEE Intelligent Vehicles Symposium (IV) · Tongji University
  12. 2018
    Deep Face Detector Adaptation Without Negative Transfer or Catastrophic ForgettingMuhammad Abdullah Jamal, Haoxiang Li, Boqing GongCVPR · University of Central Florida · Adobe Systems (United States) · +1
  13. 2018
    Incremental Learning in Deep Convolutional Neural Network VIA Adaptive RegularizationSihyeon Seong, Pyunghwan Ahn, Jiwhan Kim, Junmo KimIEEE International Conference on Consumer Electronics - A… · Korea Advanced Institute of Science and Technology
  14. 2018
    Reinforced Continual LearningJu Xu, Zhanxing ZhuNeurIPS
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  15. 2018
    Distributed Weight Consolidation: A Brain Segmentation Case StudyPatrick McClure, Charles Zheng, Jakub Kaczmarzyk … Francisco PereiraNeurIPS · National Institutes of Health · Massachusetts Institute of Technology
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  16. 2018
    Towards Robust Evaluations of Continual LearningSebastian Farquhar, Yarin GalICML · University of Oxford
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  17. 2018
    Online Structured Laplace Approximations For Overcoming Catastrophic ForgettingHippolyt Ritter, Aleksandar Botev, David BarberNeurIPS
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  18. 2018PDF ↗
  19. 2018
    Progress & Compress : A scalable framework for continual learningJonathan Schwarz, Jelena Luketina, Wojciech Marian Czarnecki … Raia HadsellICML
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  20. 2018
    Measuring Catastrophic Forgetting in Neural NetworksRonald Kemker, Marc McClure, Angelina Abitino … Christopher KananAAAI · Rochester Institute of Technology · Swarthmore College
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  21. 2018
    Selective Experience Replay for Lifelong LearningDavid Isele, Akansel CosgunAAAI · Honda (United States) · University of Pennsylvania · +1
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  22. 2018
    Active Lifelong Learning With "Watchdog"Gan Sun, Yang Cong, Xiaowei XuAAAI · Shenyang Institute of Automation · Chinese Academy of Sciences · +2
  23. 2018
    Labeled Memory Networks for Online Model AdaptationShiv Shankar, Sunita SarawagiAAAI · Indian Institute of Technology Bombay
  24. 2018
    Lifelong Learning Networks: Beyond Single Agent Lifelong LearningMohammad Rostami, Eric EatonAAAI · California University of Pennsylvania
  25. 2018
    Dynamic Few-Shot Visual Learning Without ForgettingSpyros Gidaris, Nikos KomodakisCVPR
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  26. 2018
    Differentiable plasticity: training plastic neural networks with backpropagationThomas Miconi, Jeff Clune, Kenneth O. StanleyICML · Neurosciences Institute · University of Wyoming · +1
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  27. 2018
    HOUDINI: Lifelong Learning as Program SynthesisLazar Valkov, Dipak Chaudhari, Akash Srivastava … Swarat ChaudhuriNeurIPS · Indian Institute of Technology Bombay · IBM (United States) · +2
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  28. 2018
    Task Agnostic Continual Learning Using Online Variational BayesChen Zeno, Itay Golan, Elad Hoffer, Daniel SoudryNeurIPS
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  29. 2018
    Mitigate catastrophic forgetting for continuously learning linked open data using modularityLu Chen, Masayuki MurataInternational Conference on Innovation in Artificial Inte… · The University of Osaka
  30. 2018
    Memory-based Parameter AdaptationPablo Sprechmann, Siddhant M. Jayakumar, Jack W. Rae … Charles BlundellICLR · Google (United States)
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  31. 2018
    One Big Net For EverythingJuergen SchmidhuberarXiv
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  32. 2018
    Unicorn: Continual Learning with a Universal, Off-policy AgentDaniel J. Mankowitz, Augustin Žídek, André Barreto … Tom SchaularXiv
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  33. 2018PDF ↗
  34. 2018
    Continual Reinforcement Learning with Complex SynapsesChristos Kaplanis, Murray Shanahan, Claudia ClopathICML · Imperial College London
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  35. 2018
    Bayesian Incremental Learning for Deep Neural NetworksMax Kochurov, Timur Garipov, Dmitry Podoprikhin … Dmitry VetrovICLR · Skolkovo Institute of Science and Technology · Samsung (South Korea) · +1
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  36. 2018
    Guided Policy Search for Sequential Multitask LearningFangzhou Xiong, Biao Sun, Xu Yang … Zhiyong LiuIEEE Transactions · University of Chinese Academy of Sciences · University of Science and Technology Beijing · +4
  37. 2018
  38. 2018
    Pseudo-Recursal: Solving the Catastrophic Forgetting Problem in Deep Neural NetworksCraig Atkinson, Brendan McCane, Lech Szymanski, Anthony RobinsarXiv
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  39. 2018
    Incremental Classifier Learning with Generative Adversarial NetworksYue Wu, Yinpeng Chen, Lijuan Wang … Yun FuarXiv
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  40. 2018
    A novel random forests based class incremental learning method for activity recognitionChunyu Hu, Yiqiang Chen, Lisha Hu, Xiaohui PengPattern Recognition · Chinese Academy of Sciences · Institute of Computing Technology · +2
  41. 2018PDF ↗
  42. 2018
    Focused learning promotes continual task performance in humansTimo Flesch, Jan Balaguer, Ronald Dekker … Christopher SummerfieldbioRxiv · University of Oxford · Science Oxford
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  43. 2018
    Overcoming catastrophic forgetting with hard attention to the taskJoan Serrà, Dídac Surís, Marius Miron, Alexandros KaratzoglouICML
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  44. 2018
    Memory Aware Synapses: Learning what (not) to forgetRahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny … Tinne TuytelaarsECCV · IMEC · KU Leuven · +2
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  45. 2018
    Riemannian Walk for Incremental Learning: Understanding Forgetting and IntransigenceArslan Chaudhry, Puneet K. Dokania, Thalaiyasingam Ajanthan, Philip H. S. TorrECCV · University of Oxford
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  46. 2018
    End-to-End Incremental LearningFrancisco M. Castro, Manuel J. Marín‐Jiménez, Nicolás Guil … Karteek AlahariECCV · Universidad de Málaga · University of Córdoba · +5
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  47. 2018
    Lifelong Machine Learning, Second EditionZhiyuan Chen, Bing LiuMachine Learning · Google (United States) · University of Illinois Chicago
  48. 2018
    Lifelong Learning via Progressive Distillation and RetrospectionSaihui Hou, Xinyu Pan, Chen Change Loy … Dahua LinECCV · University of Science and Technology of China · Chinese University of Hong Kong · +1
  49. 2018PDF ↗
  50. 2018
    Catastrophic Forgetting: Still a Problem for DNNsBenedikt Pfülb, Alexander Gepperth, Syahrul Afzal Che Abdullah, Axel KilianSpringer LNCS · Fulda University of Applied Sciences
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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.