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.

112 papers of 6,984 · showing 101–112Sort Recent · Most cited
  1. 2020
    Reparameterizing Convolutions for Incremental Multi-Task Learning without Task InterferenceMenelaos Kanakis, David Brüggemann, Suman Saha … Luc Van GoolECCV · ETH Zurich · KU Leuven
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  2. 2020PDF ↗
  3. 2020
    Online Continual Learning under Extreme Memory ConstraintsEnrico Fini, Stéphane Lathuilière, Enver Sangineto … Elisa RicciECCV · University of Trento · Télécom Paris · +2
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  4. 2020
    Class-Incremental Domain AdaptationJogendra Nath Kundu, Rahul Venkatesh, Naveen Venkat … R. Venkatesh BabuECCV · Indian Institute of Science Bangalore
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  5. 2020
    Piggyback GAN: Efficient Lifelong Learning for Image Conditioned GenerationMengyao Zhai, Lei Chen, Jiawei He … Greg MoriECCV · Simon Fraser University · Collège Boréal
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  6. 2020
    Incremental Few-Shot Meta-learning via Indirect Discriminant AlignmentQing Liu, Orchid Majumder, Alessandro Achille … Stefano SoattoECCV · Johns Hopkins University · Amazon (United States)
  7. 2018PDF ↗
  8. 2018
    Memory Aware Synapses: Learning what (not) to forgetRahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny … Tinne TuytelaarsECCV · IMEC · KU Leuven · +2
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  9. 2018
    Riemannian Walk for Incremental Learning: Understanding Forgetting and IntransigenceArslan Chaudhry, Puneet K. Dokania, Thalaiyasingam Ajanthan, Philip H. S. TorrECCV · University of Oxford
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  10. 2018
    End-to-End Incremental LearningFrancisco M. Castro, Manuel J. Marín‐Jiménez, Nicolás Guil … Karteek AlahariECCV · Universidad de Málaga · University of Córdoba · +5
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  11. 2018
    Lifelong Learning via Progressive Distillation and RetrospectionSaihui Hou, Xinyu Pan, Chen Change Loy … Dahua LinECCV · University of Science and Technology of China · Chinese University of Hong Kong · +1
  12. 2016
    Learning without ForgettingAuthors pendingECCV
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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.