Spatio-temporal Forecasting

Spatio-Temporal Forecasting is a computational prediction task that involves modeling and extrapolating the evolution of spatially distributed phenomena over time, distinguished from purely spatial or purely temporal forecasting by its simultaneous incorporation of both spatial dependencies and temporal dynamics.

549

Publications

38.6K

Citations

2K

Authors

712

Institutions

Publications per year

2017–2026

421

Authors

2K

  1. YL
    Yuxuan Liang

    National University of Singapore, Singapore

    13 publications · 2.2K citations

    13

    h-index

  2. JZ
    Junbo Zhang

    Southwest Jiaotong University, China

    13 publications · 2.2K citations

    13

    h-index

  3. YZ
    Yu Zheng

    Microsoft Research Asia (China), China

    9 publications · 2.1K citations

    9

    h-index

  4. GJ
    Guangyin Jin

    National University of Defense Technology, China

    8 publications · 644 citations

    8

    h-index

  5. LZ
    Liang Zhao

    George Mason University, United States

    7 publications · 322 citations

    7

    h-index

1–5 of 2K

Venues

  1. arXiv (Cornell University)

    Repository · 32 publications · 1K citations

    19

    h-index

  2. 13

    h-index

  3. IEEE Access

    12 publications · 457 citations

    12

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 9 publications · 2.1K citations

    9

    h-index

  5. Scientific Reports

    9 publications · 929 citations

    9

    h-index

1–5