unify

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.

6 papers of 11,817Sort Recent · Most cited
Remote Sensing Clear all
  1. 2025
    Transfer Learning Based on Multi-Branch Architecture Feature Extractor for Airborne LiDAR Point Cloud Semantic Segmentation with Few SamplesJialing Yuan, Hong-Chao Ma, Liang Zhang … Zhan CaiRemote Sensing
  2. 2025
    Class-Incremental Semantic Segmentation for Mobile Laser Scanning Point Clouds Using Feature Representation Preservation and Loss Cross-CouplingXu-Cheng Chen, Hai-Feng Luo, Tianqiang Huang … Wenyan HuRemote Sensing
  3. 2022
    Continual Contrastive Learning for Cross-Dataset Scene ClassificationRui Peng, Wenzhi Zhao, Kaiyuan Li … Caixia RongRemote Sensing · Beijing Normal University · State Key Laboratory of Remote Sensing Science
  4. 2022
    A Framework Integrating DeeplabV3+, Transfer Learning, Active Learning, and Incremental Learning for Mapping Building FootprintsZhichao Li, Jinwei DongRemote Sensing · Chinese Academy of Sciences · Institute of Geographic Sciences and Natural Resources Research
  5. 2022
    Electromagnetic Signal Classification Based on Class Exemplar Selection and Multi-Objective Linear ProgrammingHuaji Zhou, Jing Bai, Linchun Niu … Xiaoniu YangRemote Sensing · Xidian University · Hunan University
  6. 2021
    A Higher-Order Graph Convolutional Network for Location Recommendation of an Air-Quality-Monitoring StationYu Kang, Jie Chen, Yang Cao, Zhenyi XuRemote Sensing · University of Science and Technology of China
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.