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 Knowledge-Based Systems Clear all

2020
Incremental learning based multi-domain adaptation for object detectionXing Wei, Shaofan Liu, Yaoci Xiang … Yang LuKnowledge-Based Systems · Hefei University of Technology
2020
Incremental learning model inspired in Rehearsal for deep convolutional networksDavid A. Muñoz, Camilo Narváez, Carlos Cobos … Francisco HerreraKnowledge-Based Systems · University of Cauca · Universidad de Granada · +1
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
Discriminative Streaming Network EmbeddingYiyan Qi, Jiefeng Cheng, Xiaojun Chen … Pinghui WangKnowledge-Based Systems · Xi'an Jiaotong University · Tencent (China) · +5
2020
Granular structure-based incremental updating for multi-label classificationYuanjian Zhang, Duoqian Miao, Witold Pedrycz … Ying YuKnowledge-Based Systems · Tongji University · University of Alberta · +4

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.