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.

370 papers of 6,984 · showing 101–150Sort Recent · Most cited
  1. 2020
    Internet of emotional people: Towards continual affective computing cross cultures via audiovisual signalsJing Han, Zixing Zhang, Maja Pantić, Björn W. SchullerFuture Generation Computer Systems · University of Augsburg · Imperial College London
  2. 2020
    SLER: Self-generated long-term experience replay for continual reinforcement learningChunmao Li, Li Yang, Yin-Liang ZHAO … Xupeng GengApplied Intelligence
  3. 2020
    Deep online classification using pseudo-generative modelsA. G. Besedin, Pierre Blanchart, Michel Crucianu, Marin FerecatuComputer Vision and Image Understanding · Conservatoire National des Arts et Métiers · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · +2
  4. 2020
    Emergence of Stable Synaptic Clusters on Dendrites Through Synaptic RewiringThomas Limbacher, Robert LegensteinFrontiers · Graz University of Technology
  5. 2020
    Meta Continual Learning via Dynamic ProgrammingKrishnan, R., Prasanna BalaprakasharXiv · Argonne National Laboratory
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  6. 2020
    Can sleep protect memories from catastrophic forgetting?Oscar C González, Yury Sokolov, Giri P Krishnan … Maxim BazhenoveLife · University of California San Diego
  7. 2020
    Continual Learning for Affective Robotics: Why, What and How?Nikhil Churamani, Sinan Kalkan, Hatice GüneşIEEE International Conference on Robot and Human Interact… · University of Cambridge · Middle East Technical University
  8. 2020
    Dynamically Growing Neural Network Architecture for Lifelong Deep Learning on the EdgeDuvindu Piyasena, Miyuru Thathsara, Sathursan Kanagarajah … Meiqing WuInternational Conference on Field-Programmable Logic and… · Nanyang Technological University
  9. 2020
    Lifelong NavigationBo Liu, Xuesu Xiao, Peter StonearXiv · The University of Texas at Austin
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  10. 2020
    La-MAML: Look-ahead Meta Learning for Continual LearningGunshi Gupta, Karmesh Yadav, Liam PaullNeurIPS · Carnegie Mellon University · Université de Montréal
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  11. 2020PDF ↗
  12. 2020
    Boosting Deep Open World Recognition by ClusteringDario Fontanel, Fabio Cermelli, Massimiliano Mancini … Barbara CaputoRA-L · Politecnico di Torino · Italian Institute of Technology · +4
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  13. 2020
  14. 2020
    Multilayer Neuromodulated Architectures for Memory-Constrained Online Continual LearningSandeep Madireddy, Ángel Yanguas-Gil, Prasanna BalaprakasharXiv · Argonne National Laboratory
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  15. 2020
    Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without ForgettingJorge A. Mendez, Boyu Wang, Eric EatonNeurIPS · California University of Pennsylvania · University of Pennsylvania · +1
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  16. 2020
    Lifelong Learning using Eigentasks: Task Separation, Skill Acquisition, and Selective TransferAswin Raghavan, Jesse Hostetler, Indranil Sur … Ajay DivakaranarXiv · SRI International
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  17. 2020
    RATT: Recurrent Attention to Transient Tasks for Continual Image CaptioningRiccardo Del Chiaro, Bartłomiej Twardowski, Andrew D. Bagdanov, Joost van de WeijerNeurIPS
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  18. 2020
    Disentanglement of Color and Shape Representations for Continual LearningDavid Berga, Marc Masana, Joost van de WeijerarXiv
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  19. 2020
    Online Continual Learning from Imbalanced DataA. Chrysakis, Marie-Francine MoensICML
  20. 2020
    Batch-level Experience Replay with Review for Continual LearningZheda Mai, Hyunwoo Kim, Jihwan Jeong, Scott SannerarXiv · University of Toronto
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  21. 2020PDF ↗
  22. 2020
    Towards a practical measure of interference for reinforcement learningVincent Liu, Adam White, Hengshuai Yao, Martha WhitearXiv
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  23. 2020
    Meta-Learning through Hebbian Plasticity in Random NetworksElias Najarro, Sebastian RisiNeurIPS · IT University of Copenhagen
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  24. 2020PDF ↗
  25. 2020
    Pseudo-Rehearsal for Continual Learning with Normalizing FlowsJary Pomponi, Simone Scardapane, Aurelio UnciniarXiv · Sapienza University of Rome
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  26. 2020
    On Class Orderings for Incremental LearningMarc Masana, Bartłomiej Twardowski, Joost van de WeijerarXiv
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  27. 2020
    Eliminating Catastrophic Interference with Biased CompetitionAmelia Elizabeth Pollard, Jonathan ShapiroarXiv
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  28. 2020
    Catastrophic forgetting and mode collapse in GANsHoang Thanh-Tung, Truyen TranIJCNN · Deakin University · Allen Institute for Artificial Intelligence
  29. 2020
    Lifelong Zero-Shot LearningKun Wei, Cheng Deng, Xu YangIJCAI · Xidian University
  30. 2020
    Forget Me Not: Reducing Catastrophic Forgetting for Domain Adaptation in Reading ComprehensionYing Xu, Xu Zhong, Antonio Jimeno Yepes, Jey Han LauIJCNN · IBM Research - Australia · The University of Melbourne
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  31. 2020
    Continual Learning with Gated Incremental Memories for sequential data processingAndrea Cossu, Antonio Carta, Davide BacciuIEEE International Joint Conference on Neural Network · University of Pisa
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  32. 2020
    Memory Augmented Neural Model for Incremental Session-based RecommendationFei Mi, Boi FaltingsIJCAI · École Polytechnique Fédérale de Lausanne
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  33. 2020PDF ↗
  34. 2020
    Enabling Continual Learning with Differentiable Hebbian PlasticityVithursan Thangarasa, Thomas Miconi, Graham W. TaylorIEEE International Joint Conference on Neural Network · Vector Institute · University of Guelph · +1
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  35. 2020
    OvA-INN: Continual Learning with Invertible Neural NetworksGuillaume Hocquet, Olivier Bichler, Damien QuerliozIJCNN · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · Laboratoire d'Intégration des Systèmes et des Technologies · +2
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  36. 2020
    GPU-based State Adaptive Random Forest for Evolving Data StreamsOcean Wu, Yun Sing Koh, Giovanni RusselloIJCNN · University of Auckland
  37. 2020
    Online Knowledge Acquisition with the Selective Inherited ModelXiaocong Du, Shreyas Kolala Venkataramanaiah, Zheng Li … Yu CaoIJCNN · Arizona State University · Oak Ridge National Laboratory
  38. 2020
    Few-Shot Class-Incremental Learning via Feature Space CompositionHanbin Zhao, Yongjian Fu, Xue-Wei Li … Xi LiarXiv
  39. 2020
    Author response: Can sleep protect memories from catastrophic forgetting?Oscar C. González, Yury Sokolov, Giri P. Krishnan … Maxim BazhenovPreprint · University of California San Diego
  40. 2020
    Incremental Learning of Multi-Domain Image-to-Image TranslationsDaniel Stanley Tan, Yong-Xiang Lin, Kai‐Lung HuaIEEE TCSVT · National Taiwan University of Science and Technology
  41. 2020
    Gradient Based Memory Editing for Task-Free Continual LearningXisen Jin, Arka Sadhu, Junyi Du, Xiang RenarXiv
  42. 2020
    Supermasks in SuperpositionMitchell Wortsman, Vivek Ramanujan, Rosanne Liu … Ali FarhadiNeurIPS
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  43. 2020
    Storing Encoded Episodes as Concepts for Continual LearningAli Ayub, Alan R. WagnerarXiv · Pennsylvania State University
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  44. 2020
    Bookworm continual learning: beyond zero-shot learning and continual learningKai Wang, Luis Herranz, Anjan Dutta, Joost van de WeijerarXiv · Universitat Autònoma de Barcelona
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  45. 2020PDF ↗
  46. 2020
  47. 2020
    Continual Learning in Recurrent Neural Networks with HypernetworksBenjamin Ehret, Christian Henning, Maria R. Cervera … Benjamin F. GrewearXiv · ETH Zurich
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  48. 2020
    Automatic Recall Machines: Internal Replay, Continual Learning and the BrainXu Ji, João F. Henriques, Tinne Tuytelaars, Andrea VedaldiarXiv
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  49. 2020
    Generalisation Guarantees for Continual Learning with Orthogonal Gradient DescentMehdi Bennani, Thang Doan, Masashi SugiyamaarXiv · École Nationale Supérieure des Mines de Paris · McGill University · +1
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  50. 2020
    Neural Topic Modeling with Continual Lifelong LearningPankaj Gupta, Yatin Chaudhary, Thomas A. Runkler, Schütze, HinrichICML · Siemens (Germany) · Technical University of Munich · +2
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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. 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.