FEDDGCN: A Frequency-Enhanced Decoupling Dynamic Graph Convolutional Network for Traffic Flow Prediction.
Wendong Zhang|Ruobai Xiang|Zhifang Liao|Peng Lan|Qihao Liang
| Anthology ID: | DBLP:conf/cikm/ZhangXLLL25 |
|---|---|
| Volume: | Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025 |
| Year: | 2025 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 4222-4231 |
| URL: | https://doi.org/10.1145/3746252.3761048 |
| DOI: | https://doi.org/10.1145/3746252.3761048 |
| DBLP: | conf/cikm/ZhangXLLL25 |
| BibTeX: |
@inproceedings{zhang-2025-feddgcn,
author = {Wendong Zhang and
Ruobai Xiang and
Zhifang Liao and
Peng Lan and
Qihao Liang},
editor = {Meeyoung Cha and
Carl Yang and
Senjuti Basu Roy and
Chanyoung Park and
Zhenhui Jessie Li and
Noseong Park and
Carl Yang and
Senjuti Basu Roy and
Zhenhui Jessie Li and
Jaap Kamps and
Kijung Shin and
Bryan Hooi and
Lifang He},
title = {{FEDDGCN: A Frequency-Enhanced Decoupling Dynamic Graph Convolutional Network for Traffic Flow Prediction}},
booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}},
pages = {4222--4231},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3746252.3761048},
doi = {https://doi.org/10.1145/3746252.3761048}
}