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.

18 papers of 8,653Sort Recent · Most cited
  1. 2016
    A Growing Long-term Episodic & Semantic MemoryMarc Pickett, Rami Al‐Rfou, Louis Shao, Chris TararXiv
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  2. 2016
    Incremental One-Class Models for Data ClassificationTakoua Kefi, Riadh Ksantini, Mohamed Kaâniche, Adel BouhoulaarXiv
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  3. 2016PDF ↗
  4. 2016
    Less-forgetting Learning in Deep Neural NetworksHeechul Jung, Jeongwoo Ju, Minju Jung, Junmo KimarXiv
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  5. 2016
    Progressive Neural NetworksAndrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins … Raia HadsellarXiv
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  6. 2016
    Incremental learning of perceptual and conceptual representations and the puzzle of neural repetition suppressionStephen J. GottsPsychonomic Bulletin & Review · National Institutes of Health · National Institute of Mental Health
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  7. 2016
    Active Long Term Memory NetworksTommaso Furlanello, Jiaping Zhao, Andrew Saxe … Bosco S. TjanarXiv
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  8. 2016
    One-shot Learning with Memory-Augmented Neural NetworksAdam Santoro, Sergey Bartunov, Matthew Botvinick … Timothy LillicraparXiv
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  9. 2016
    Online Open World RecognitionRocco De Rosa, Thomas Mensink, Barbara CaputoarXiv
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  10. 2016
    Semantic video labeling by developmental visual agentsMarco Gori, Marco Lippi, Marco Maggini, Stefano MelacciComputer Vision and Image Understanding · University of Siena · University of Bologna
  11. 2016
    Towards Lifelong Object Learning by Integrating Situated Robot Perception and Semantic Web MiningYoung Jay, Valerio Basile, Kunze Lars … Nick HawesFrontiers · University of Birmingham · Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis
  12. 2016
    Comparing Incremental Learning Strategies for Convolutional Neural NetworksVincenzo Lomonaco, Davide MaltoniSpringer LNCS · University of Bologna
  13. 2016
    Analytical Incremental Learning: Fast Constructive Learning Method for Neural NetworkSyukron Abu Ishaq Alfarozi, Noor Akhmad Setiawan, Teguh Bharata Adji … Masanori SugimotoSpringer LNCS · Universitas Gadjah Mada · King Mongkut's Institute of Technology Ladkrabang · +1
  14. 2016
    Continual Learning through Evolvable Neural Turing MachinesBenno Lüders, Mikkel Schläger, S. RisiNeurIPS
  15. 2016
  16. 2016
    Learning without ForgettingAuthors pendingECCV
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  17. 2016PDF ↗
  18. 2016
    Net2Net: Accelerating Learning via Knowledge TransferTianqi Chen, Ian Goodfellow, Jonathon ShlensICLR · University of Washington · Google (United States)
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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.