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.

28 papers of 11,817Sort Recent · Most cited
  1. 2022
    Federated Continual Learning for Socially Aware RoboticsLuke Guerdan, Hatice GüneşIEEE International Conference on Robot and Human Interact… · Carnegie Mellon University · University of Cambridge
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  2. 2022
    Three types of incremental learningGido M. van de Ven, Tinne Tuytelaars, Andreas S. ToliasNature Machine Intelligence · Baylor College of Medicine · University of Cambridge · +2
  3. 2022
    Continual Learning for Affective Robotics: A Proof of Concept for WellbeingNikhil Churamani, Minja Axelsson, Atahan Çaldır, Hatice GüneşInternational Conference on Affective Computing and Intel… · University of Cambridge · Özyeğin University
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  4. 2020
    Mind Your Manners! A Dataset and a Continual Learning Approach for Assessing Social Appropriateness of Robot ActionsJonas Tjomsland, Sinan Kalkan, Hatice GüneşFrontiers · University of Cambridge · Middle East Technical University
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  5. 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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  6. 2020
    CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future DirectionsVincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodríguez … Davide MaltoniArtificial Intelligence · University of Bologna · Mila - Quebec Artificial Intelligence Institute · +7
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  7. 2021
    Provable Lifelong Learning of RepresentationsXinyuan Cao, Weiyang Liu, Santosh VempalaAISTATS · Georgia Institute of Technology · University of Cambridge
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  8. 2021
    Exploring System Performance of Continual Learning for Mobile and Embedded Sensing ApplicationsYoung D. Kwon, Jagmohan Chauhan, Abhishek Kumar … Cecilia MascoloTyöväentutkimus Vuosikirja · University of Cambridge · University of Southampton
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  9. 2021
    Behavioral Experiments for Understanding Catastrophic ForgettingSamuel J. Bell, Neil D. LawrencearXiv · University of Cambridge
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  10. 2021
    FastICARL: Fast Incremental Classifier and Representation Learning with Efficient Budget Allocation in Audio Sensing ApplicationsYoung D. Kwon, Jagmohan Chauhan, Cecilia MascoloInterspeech · University of Cambridge · University of Southampton
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  11. 2020
    InfoMax-GAN: Improved Adversarial Image Generation via Information Maximization and Contrastive LearningKwot Sin Lee, Ngoc-Trung Tran, Ngai‐Man CheungWACV · University of Cambridge · Snap (United States) · +1
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  12. 2021
    Elastic weight consolidation for better bias inoculationJames Thorne, Andreas VlachosEACL · University of Cambridge
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  13. 2020
    Generalized Variational Continual LearningNoel Loo, Siddharth Swaroop, Richard E. TurnerICLR · University of Cambridge
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  14. 2020
    Brain-inspired replay for continual learning with artificial neural networksGido M. van de Ven, Hava T. Siegelmann, Andreas S. ToliasNature Communications · Baylor College of Medicine · University of Cambridge · +3
  15. 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
  16. 2020
    Continual Learning for Affective ComputingNikhil ChuramaniarXiv · University of Cambridge
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  17. 2020
    A mathematical model for storage and recovery of motor actions in the spinal cordDavid Parker, Vipin SrivastavabioRxiv · University of Cambridge · University of Hyderabad
  18. 2019
    Proximal Distilled Evolutionary Reinforcement LearningCristian Bodnar, Ben Day, Píetro LióAAAI · University of Cambridge
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  19. 2020
    Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation ProblemDanielle Saunders, Bill ByrneACL · University of Cambridge
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  20. 2020
    Emergent Communication Pretraining for Few-Shot Machine TranslationYaoyiran Li, Edoardo Maria Ponti, Ivan Vulić, Anna KorhonenCOLING · Tallinn University of Technology · University of Cambridge · +1
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  21. 2019
    Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive ProcessesJames Requeima, Jonathan Gordon, John Bronskill … Richard E. TurnerNeurIPS · University of Cambridge · Google (United States)
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  22. 2019
    Ultra-local adaptation due to genetic accommodationSyuan‐Jyun Sun, Andrew M. Catherall, Sónia Pascoal … Rebecca M. KilnerbioRxiv · University of Cambridge · Michigan State University · +1
  23. 2017
    Variational Continual LearningTurner, RE, Thang D. Bui, Yingzhen Li, Cuong, NguyenICLR · University of Cambridge
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  24. 2019
    Rates of Convergence for Sparse Variational Gaussian Process RegressionDavid R. Burt, Carl Edward Rasmussen, Mark van der WilkICML · University of Cambridge · Imperial College London
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  25. 2019
    Meta-Learning Improves Lifelong Relation ExtractionAbiola Obamuyide, Andreas VlachosWorkshop on Representation Learning for NLP (RepL4NLP-2019) · University of Cambridge · PRG S&Tech (South Korea) · +1
  26. 2018
    Ensemble Incremental Random Vector Functional Link Network for Short-term Crude Oil Price ForecastingXueheng Qiu, Ponnuthurai Nagaratnam Suganthan, A. J. Gehan AmaratungaIEEE Symposium Series on Computational Intelligence (SSCI) · Nanyang Technological University · University of Cambridge
  27. 2017
    Streaming Sparse Gaussian Process ApproximationsThang D. Bui, Cuong V. Nguyen, Richard E. TurnerNeurIPS · University of Cambridge
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  28. 2014
    Overcoming Catastrophic Interference in Connectionist Networks Using Gram-Schmidt OrthogonalizationVipin Srivastava, Suchitra Sampath, David ParkerPLOS · University of Hyderabad · University of Cambridge
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.