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.

9 papers of 8,653Sort Recent · Most cited
  1. 2021
    Remembering for the Right Reasons: Explanations Reduce Catastrophic ForgettingSayna Ebrahimi, S. Petryk, Akash Gokul … Trevor DarrellICLR
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  2. 2020
    Adversarial Continual LearningSayna Ebrahimi, Franziska Meier, Roberto Calandra … Marcus RohrbachECCV · Berkeley College · Meta (United States) · +2
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  3. 2020
    Uncertainty-guided Continual Learning with Bayesian Neural NetworksSayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus RohrbachICLR · University of California, Berkeley · King Abdullah University of Science and Technology · +1
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  4. 2019
    On Tiny Episodic Memories in Continual LearningArslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny … M. RanzatoPreprint
  5. 2019
    Continual Learning with Tiny Episodic MemoriesArslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny … Marc’Aurelio RanzatoarXiv · University of Oxford
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  6. 2019
    Uncertainty-Guided Continual Learning in Bayesian Neural Networks - Extended AbstractSayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus RohrbachCVPR
  7. 2019
    Efficient Lifelong Learning with A-GEMArslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, Mohamed ElhoseinyICLR
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  8. 2019
    Selfless Sequential LearningRahaf Aljundi, Marcus Rohrbach, Tinne TuytelaarsICLR
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  9. 2018
    Memory Aware Synapses: Learning what (not) to forgetRahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny … Tinne TuytelaarsECCV · IMEC · KU Leuven · +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. 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.