Temporal Convolutional Networks

Temporal Convolutional Network is a type of convolutional neural network architecture that employs dilated causal convolutions to model temporal dependencies in sequential data, distinguishing itself by enabling parallelizable training and long-range context capture without recurrence.

1.2K

Publications

80.8K

Citations

4K

Authors

966

Institutions

Publications per year

2017–2026

1.2K

Authors

4K

  1. LB
    Luca Benini

    University of Bologna, Italy

    13 publications · 841 citations

    12

    h-index

  2. LW
    Limin Wang

    Nanjing University, China

    10 publications · 1.8K citations

    10

    h-index

  3. AB
    Alessio Burrello

    University of Bologna, Italy

    9 publications · 389 citations

    9

    h-index

  4. YQ
    Yu Qiao

    Shenzhen Institutes of Advanced Technology, China

    8 publications · 1.2K citations

    8

    h-index

  5. CG
    Chuang Gan

    IBM (United States), United States

    8 publications · 2.6K citations

    8

    h-index

1–5 of 4K

Venues

  1. arXiv (Cornell University)

    Repository · 89 publications · 10.3K citations

    37

    h-index

  2. IEEE Access

    36 publications · 1.8K citations

    23

    h-index

  3. 20

    h-index

  4. Sensors

    21 publications · 642 citations

    18

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 18 publications · 1.4K citations

    17

    h-index

1–5