Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 4,574Sort Recent · Most cited
  1. 2025
    CODE-CL: Conceptor-Based Gradient Projection for Deep Continual LearningMarco Paul E. Apolinario, Sakshi Choudhary, Kaushik RoyICCV · Purdue University West Lafayette
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  2. 2023
    Saliency Guided Experience Packing for Replay in Continual LearningGobinda Saha, Kaushik RoyWACV · Purdue University West Lafayette
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  3. 2021
    SPACE: Structured Compression and Sharing of Representational Space for Continual LearningGobinda Saha, Isha Garg, Aayush Ankit, Kaushik RoyIEEE Access · Purdue University West Lafayette
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  4. 2020PDF ↗
  5. 2019
    Incremental Learning in Deep Convolutional Neural Networks Using Partial Network SharingSyed Shakib Sarwar, Aayush Ankit, Kaushik RoyIEEE Access · Purdue University West Lafayette
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  6. 2020
    Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learningDeboleena Roy, Priyadarshini Panda, Kaushik RoyNeural Networks · Purdue University West Lafayette
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  7. 2017
    ASP: Learning to Forget With Adaptive Synaptic Plasticity in Spiking Neural NetworksPriyadarshini Panda, Jason M. Allred, Shriram Ramanathan, Kaushik RoyIEEE Journal on Emerging and Selected Topics in Circuits… · Purdue University West Lafayette
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  8. 2017
    Habituation based synaptic plasticity and organismic learning in a quantum perovskiteFan Zuo, Priyadarshini Panda, Michele Kotiuga … Shriram RamanathanNature Communications · Purdue University West Lafayette · Rutgers, The State University of New Jersey · +3
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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, and only papers with a PDF we can point you at, so every title opens the paper itself. 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.