Temporal Dependency Modeling
Temporal Dependency Modeling is a computational framework that formalizes the sequencing and timing constraints among interrelated tasks in a workflow orchestration system, distinguishing itself by explicitly representing temporal relationships and their propagation effects to ensure correct execution order and timing guarantees.
267
Publications
20.1K
Citations
1K
Authors
362
Institutions
Publications per year
2017–2026
199
267
Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
Ziyu Liu, Hongwen Zhang, Zhenghao Chen et al. · 2020 · 1.2K citations
Spatial–Temporal Recurrent Neural Network for Emotion Recognition
Tong Zhang, Wenming Zheng, Zhen Cui et al. · IEEE Transactions on Cybernetics · 2018 · 586 citations · Full text
1–5 of 267
1K
6
h-index
4
h-index
4
h-index
4
h-index
4
h-index
1–5 of 1K
362
Tsinghua University
Beijing, China
11 h-index
34 publications
4.1K citations
University of Chinese Academy of Sciences
Beijing, China
10 h-index
21 publications
2.5K citations
University of Science and Technology of China
Hefei, China
7 h-index
23 publications
1K citations

Chinese Academy of Sciences
Beijing, China
7 h-index
20 publications
1.3K citations

University of Electronic Science and Technology of China
Chengdu, China
7 h-index
13 publications
633 citations

Beihang University
Beijing, China
7 h-index
22 publications
4.2K citations
IBM (United States)
Armonk, United States
6 h-index
9 publications
530 citations

Sun Yat-sen University
Guangzhou, China
6 h-index
22 publications
943 citations
1–8 of 362
Repository · 26 publications · 1.8K citations
17
h-index
Conference · 8 publications · 2K citations
8
h-index
6 publications · 277 citations
6
h-index
5 publications · 331 citations
5
h-index
5 publications · 331 citations
5
h-index
1–5