Dynamic Graph Features

Dynamic Graph Features is a graph feature engineering methodology that captures evolving structural and attribute-based patterns in temporal graphs by differentiating itself from static graph features through the explicit incorporation of time-varying relationships and node dynamics.

37

Publications

1.7K

Citations

162

Authors

73

Institutions

Publications per year

2017–2026

31

Authors

162

  1. PW
    Pengfei Wang

    Chinese Academy of Sciences, China

    2 publications · 103 citations

    2

    h-index

  2. BL
    Baisheng Lai

    Zhejiang University, China

    2 publications · 103 citations

    2

    h-index

  3. FC
    Fei Chen

    Nagoya University, Japan

    2 publications · 103 citations

    2

    h-index

  4. KZ
    Kaibo Zhou

    Huazhong University of Science and Technology, China

    2 publications · 119 citations

    2

    h-index

  5. ZJ
    Zhongming Jin

    Zhejiang University, China

    2 publications · 103 citations

    2

    h-index

1–5 of 162

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 392 citations

    5

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 88 citations

    2

    h-index

  3. IEEE Access

    2 publications · 101 citations

    2

    h-index

  4. Measurement Science and Technology

    1 publications · 21 citations

    1

    h-index

  5. IEEE Transactions on Industrial Electronics

    1 publications · 98 citations

    1

    h-index

1–5