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.

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Nikola Kasabov Clear all

2021
Brain-inspired spiking neural networks for decoding and understanding muscle activity and kinematics from electroencephalography signals during hand movementsKaushalya Kumarasinghe, Nikola Kasabov, Denise TaylorScientific Reports · University of Moratuwa · Auckland University of Technology · +1
2020
Application of a Brain-Inspired Spiking Neural Network Architecture to Odor Data ClassificationAnup Vanarse, Josafath I. Espinosa‐Ramos, Adam Osseiran … Nikola KasabovSensors · Edith Cowan University · Auckland University of Technology · +2
2018
Evolving Spiking Neural Networks for online learning over drifting data streamsJesús L. Lobo, Ibai Laña, Javier Del Ser … Nikola KasabovNeural Networks · Euskadiko Parke Teknologikoa · University of the Basque Country · +2

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.