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.

6 papers of 11,817Sort Recent · Most cited
  1. 2022
    Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic SegmentationDipam Goswami, René Schuster, Joost van de Weijer, Didier StrickerWACV · German Research Centre for Artificial Intelligence · Birla Institute of Technology and Science, Pilani · +2
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  2. 2021
    Inverse Dirichlet weighting enables reliable training of physics informed neural networksSuryanarayana Maddu, Dominik Sturm, Christian L. Müller, Ivo F. SbalzariniMachine Learning Science and Technology · German Research Centre for Artificial Intelligence · Center for Systems Biology Dresden · +11
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  3. 2021
    Online Model Adaptation of Autonomous Underwater Vehicles with LSTM NetworksMiguel Bande Firvida, Bilal WehbeOCEANS 2021: San Diego – Porto · German Research Centre for Artificial Intelligence
  4. 2020
    Sequential Targeting: an incremental learning approach for data imbalance in text classificationJoel Jang, Yoonjeon Kim, Kyoung-Ho Choi, Sungho SuhExpert Systems with Applications · Korea Advanced Institute of Science and Technology · Naver (South Korea) · +1
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  5. 2019
    A Framework for On-line Learning of Underwater Vehicles Dynamic ModelsBilal Wehbe, Marc Hildebrandt, Frank KirchnerICRA · University of Bremen · German Research Centre for Artificial Intelligence
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  6. 2013
    Incremental learning of skill collections based on intrinsic motivationJan Hendrik Metzen, Frank KirchnerFrontiers · University of Bremen · German Research Centre for Artificial Intelligence
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.