Temporal Graph Learning

Temporal Graph Learning is a subfield of graph-based learning that focuses on modeling and analyzing graph-structured data where the nodes, edges, or attributes evolve over time, incorporating temporal dynamics into the representation and inference processes.

221

Publications

16.2K

Citations

931

Authors

276

Institutions

Publications per year

2017–2026

205

Authors

931

  1. LC
    Lei Chen

    Hong Kong University of Science and Technology, Hong Kong SAR China

    4 publications · 124 citations

    4

    h-index

  2. PS
    Philip S. Yu

    University of Illinois Chicago, United States

    4 publications · 253 citations

    4

    h-index

  3. YS
    Yanyan Shen

    Shanghai Jiao Tong University, China

    4 publications · 124 citations

    4

    h-index

  4. YX
    Yun Xiong

    Fudan University, China

    4 publications · 215 citations

    4

    h-index

  5. GN
    Giang Nguyen

    Intel (United States), United States

    3 publications · 621 citations

    3

    h-index

1–5 of 931

Venues

  1. arXiv (Cornell University)

    Repository · 31 publications · 1K citations

    18

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 10 publications · 505 citations

    10

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 8 publications · 657 citations

    8

    h-index

  4. Knowledge-Based Systems

    4 publications · 277 citations

    4

    h-index

  5. IEEE Access

    4 publications · 154 citations

    4

    h-index

1–5