Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

17 papers of 11,817Sort Recent · Most cited
  1. 2022
    Dynamic Consolidation for Continual LearningHang Li, Chen Ma, Xi Chen, Xue LiuNeural Computation · McGill University · City University of Hong Kong
  2. 2022
    Machine learning-based incremental learning in interactive domain modellingRijul Saini, Gunter Mussbacher, Jin Guo, Jörg KienzleInternational Conference on Model Driven Engineering Lang… · McGill University
  3. 2021
    Composable Sparse Fine-Tuning for Cross-Lingual TransferAlan Ansell, Edoardo Maria Ponti, Anna Korhonen, Ivan VulićACL · University of Cambridge · Language Science (South Korea) · +2
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  4. 2021
    SPeCiaL: Self-Supervised Pretraining for Continual LearningLucas Caccia, Joëlle PineauSpringer LNCS · McGill University
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  5. 2021
    Impact Patterns of Combining Model Pruning and Continual Learning on Model PerformanceXueyang Zhang, Hang Li, Xi Chen, Xue LiuIEEE Third International Conference on Cognitive Machine… · McGill University
  6. 2021
    Learning offline: memory replay in biological and artificial reinforcement learningEmma L. Roscow, Raymond Chua, Rui Ponte Costa … Nathan F. LeporaTrends in Neurosciences · Centre de Recerca Matemàtica · McGill University · +2
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  7. 2021
    TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph CompletionJiapeng Wu, Yishi Xu, Yingxue Zhang … Jackie Chi Kit CheungSIGIR · McGill University · Université de Montréal · +1
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  8. 2020
    FoCL: Feature-Oriented Continual Learning for Generative ModelsQicheng Lao, Mehrzad Mortazavi, Marzieh S. Tahaei … Mohammad HavaeiPattern Recognition · Sichuan University · West China Medical Center of Sichuan University · +3
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  9. 2021
    Understanding Capacity Saturation in Incremental LearningShenyang Huang, Vincent François-Lavet, Guillaume RabusseauCanadian Conference on Artificial Intelligence · Centre Universitaire de Mila · McGill University · +3
  10. 2021
    A Consciousness-Inspired Planning Agent for Model-Based Reinforcement LearningMingde Zhao, Zhen Liu, Sitao Luan … Yoshua BengioarXiv · Dalian University of Technology · Université de Montréal · +1
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  11. 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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  12. 2020
    Deep Reinforcement and InfoMax LearningBogdan Mazoure, Rémi Tachet des Combes, Thang Doan … R Devon HjelmNeurIPS · McGill University
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  13. 2020
    Evaluating Logical Generalization in Graph Neural NetworksKoustuv Sinha, Shagun Sodhani, Joëlle Pineau, William L. HamiltonarXiv · McGill University
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  14. 2019
    Online Learned Continual Compression with Stacked Quantization ModuleLucas Caccia, Eugene Belilovsky, M. Caccia, Joëlle PineauarXiv · McGill University · Meta (Israel)
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  15. 2019
    Online Continual Learning with Maximally Interfered RetrievalRahaf Aljundi, Lucas Caccia, Eugene Belilovsky … Tinne TuytelaarsarXiv · McGill University · Université de Montréal · +1
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  16. 2019
    A Connectionist Model of the Development of Velocity, Time, and Distance ConceptsDavid Buckingham, Thomas R. ShultzCognitive Science · McGill University
  17. 2019
    Building Knowledge for AI Agents with Reinforcement LearningDoina PrecupAdaptive Agents and Multi-Agents Systems · McGill 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. 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.