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.

10 papers of 11,817Sort Recent · Most cited
  1. 2022
    Memory Population in Continual Learning via Outlier EliminationJulio Hurtado, Alain Raymond-Sáez, Vladimir Araujo … Davide BacciuICCV · University of Pisa · Pontificia Universidad Católica de Chile · +1
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  3. 2022
    Continual Learning for Human State MonitoringFederico Matteoni, Andrea Cossu, Claudio Gallicchio … Davide BacciuThe European Symposium on Artificial Neural Networks
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  5. 2022
    Continual Pre-Training Mitigates Forgetting in Language and VisionAndrea Cossu, Tinne Tuytelaars, Antonio Carta … Davide BacciuNeural Networks
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  6. 2022
    Generative Negative Replay for Continual LearningGabriele Graffieti, Davide Maltoni, Lorenzo Pellegrini, Vincenzo LomonacoNeural Networks
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  7. 2022
    Practical Recommendations for Replay-based Continual Learning MethodsGabriele Merlin, Vincenzo Lomonaco, Andrea Cossu … Davide BacciuSpringer LNCS · University of Pisa · Scuola Normale Superiore
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  8. 2022
    Avalanche RL: a Continual Reinforcement Learning LibraryNicoló Lucchesi, Antonio Carta, Vincenzo Lomonaco, Davide BacciuSpringer LNCS · University of Pisa
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  9. 2022
    Populating Memory in Continual Learning with Consistency Aware SamplingJ. Hurtado, Alain Raymond-Sáez, Vladimir Araujo … D. BacciuPreprint
  10. 2022
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.