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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2020 University of Science and Technology of China Clear all

2020
Deep Inhomogeneous Regularization For Transfer LearningWen Wang, Wei Zhai, Yang CaoICIP · University of Science and Technology of China
2020
Incremental learning imbalanced data streams with concept drift: The dynamic updated ensemble algorithmLi Zeng, Wenchao Huang, Yan Xiong … Tuanfei ZhuKnowledge-Based Systems · University of Science and Technology of China · Zhejiang Gongshang University · +1
2020
Explicit Filterbank Learning for Neural Image Style Transfer and Image ProcessingDongdong Chen, Lu Yuan, Jing Liao … Gang HuaTPAMI · University of Science and Technology of China · Microsoft (United States) · +1
2020
Memory Protection Generative Adversarial Network (MPGAN): A Framework to Overcome the Forgetting of GANs Using Parameter Regularization MethodsYifan Chang, Wenbo Li, Jian Peng … Yingliang HuangIEEE Access · University of Science and Technology of China · Hefei Institute of Technology Innovation · +3

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.