Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting.
Juyong Jiang|Binqing Wu|Ling Chen|Kai Zhang|Sunghun Kim
| Anthology ID: | DBLP:conf/cikm/JiangWCZK23 |
|---|---|
| Volume: | Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023 |
| Year: | 2023 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 987-996 |
| URL: | https://doi.org/10.1145/3583780.3614868 |
| DOI: | https://doi.org/10.1145/3583780.3614868 |
| DBLP: | conf/cikm/JiangWCZK23 |
| BibTeX: |
@inproceedings{jiang-2023-enhancing,
author = {Juyong Jiang and
Binqing Wu and
Ling Chen and
Kai Zhang and
Sunghun Kim},
editor = {Ingo Frommholz and
Frank Hopfgartner and
Mark Lee and
Michael P. Oakes and
Mounia Lalmas-Roelleke and
Min Zhang and
Rodrygo L. T. Santos},
title = {{Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting}},
booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}},
pages = {987--996},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3583780.3614868},
doi = {https://doi.org/10.1145/3583780.3614868}
}