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.

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Shulin Liu Shanghai University Clear all

2022
Small-sample continual learning classification method with vaccine to update memory cells based on the artificial immune systemHongli Zhang, Lunchang Jiang, Wenhui Jiao … Haihua XiaoBiosystems · Shanghai University
2022
Self-updating continual learning classification method based on artificial immune systemXin Sun, Haotian Wang, Shulin Liu … Haihua XiaoApplied Intelligence · Shanghai University · Changzhou University
2022
Continual learning classification method with the weighted k-nearest neighbor rule for time-varying data space based on the artificial immune systemDong Li, Ming Gu, Shulin Liu … Kun QianKnowledge-Based Systems · Changzhou University · Shanghai University
2021
Continual learning classification method with single-label memory cells based on the intelligent mechanism of the biological immune systemDong Li, Lanlan Gong, Shulin Liu … Kun QianJournal of Intelligent & Fuzzy Systems · Changzhou University · Shanghai University
2021
Continual learning classification method for time-varying data space based on artificial immune systemDong Li, Shulin Liu, Furong Gao, Xin SunJournal of Intelligent & Fuzzy Systems · Hong Kong University of Science and Technology · Changzhou University · +1
2021
Continual learning classification method with constant-sized memory cells based on the artificial immune systemDong Li, Shulin Liu, Furong Gao, Xin SunKnowledge-Based Systems · Hong Kong University of Science and Technology · Changzhou University · +1
2020
Continual learning classification method with new labeled data based on the artificial immune systemDong Li, Shulin Liu, Furong Gao, Xin SunApplied Soft Computing · Hong Kong University of Science and Technology · Changzhou University · +1

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.