Spatiotemporal Machine Learning

Spatiotemporal Machine Learning is a machine learning paradigm that integrates spatial and temporal dependencies within data to model dynamic geographical phenomena by jointly accounting for location-based relationships and time-evolving patterns.

531

Publications

34K

Citations

2.1K

Authors

682

Institutions

Publications per year

2017–2026

467

Authors

2.1K

  1. JZ
    Junbo Zhang

    Southwest Jiaotong University, China

    13 publications · 4.5K citations

    13

    h-index

  2. YZ
    Yu Zheng

    Microsoft Research Asia (China), China

    9 publications · 4K citations

    9

    h-index

  3. XS
    Xuan Song

    The University of Tokyo, Japan

    7 publications · 278 citations

    7

    h-index

  4. RJ
    Renhe Jiang

    The University of Tokyo, Japan

    7 publications · 278 citations

    7

    h-index

  5. YL
    Yuxuan Liang

    National University of Singapore, Singapore

    6 publications · 876 citations

    6

    h-index

1–5 of 2.1K

Venues

  1. 19

    h-index

  2. arXiv (Cornell University)

    Repository · 26 publications · 885 citations

    16

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 17 publications · 4.5K citations

    15

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 14 publications · 1.4K citations

    13

    h-index

  5. Remote Sensing

    12 publications · 389 citations

    12

    h-index

1–5