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.

5 papers of 8,653Sort Recent · Most cited
  1. 2024
    Adversarially Diversified Rehearsal Memory (ADRM): Mitigating Memory Overfitting Challenge in Continual LearningHikmat Khan, Ghulam Rasool, Nidhal BouaynayaIJCNN · Rowan University · Moffitt Cancer Center
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  2. 2024
    Brain-Inspired Continual Learning: Robust Feature Distillation and Re-Consolidation for Class Incremental LearningHikmat Khan, Nidhal Bouaynaya, Ghulam RasoolIEEE Access · Rowan University · Moffitt Cancer Center
  3. 2023
    Variational Density Propagation Continual LearningChristopher F. Angelini, Nidhal Bouaynaya, Ghulam RasoolInternational Symposium on Image and Signal Processing an… · Rowan University · Moffitt Cancer Center
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  4. 2023
    The Importance of Robust Features in Mitigating Catastrophic ForgettingHikmat Ullah Khan, Nidhal Bouaynaya, Ghulam RasoolIEEE Symposium on Computers and Communications (ISCC) · Rowan University · Moffitt Cancer Center
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  5. 2022
    Adversarially Robust Continual LearningHikmat Ullah Khan, Nidhal Bouaynaya, Ghulam RasoolIJCNN · Rowan University · Moffitt Cancer Center
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.