A Two-Stage Anomaly-Aware Framework for Robust Traffic Forecasting with Memory-Guided GNNs.
Pei-Xuan Li|Cheng-Ru Chou|Jhe-Wei Tsai|Hsun-Ping Hsieh
| Anthology ID: | DBLP:conf/wsdm/LiCTH26 |
|---|---|
| Volume: | Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, WSDM 2026, Boise, ID, USA, February 22-26, 2026 |
| Year: | 2026 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 1180-1184 |
| URL: | https://doi.org/10.1145/3773966.3779379 |
| DOI: | https://doi.org/10.1145/3773966.3779379 |
| DBLP: | conf/wsdm/LiCTH26 |
| BibTeX: |
@inproceedings{li-2026-twostage,
author = {Pei-Xuan Li and
Cheng-Ru Chou and
Jhe-Wei Tsai and
Hsun-Ping Hsieh},
title = {{A Two-Stage Anomaly-Aware Framework for Robust Traffic Forecasting with Memory-Guided GNNs}},
booktitle = {{Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, WSDM 2026, Boise, ID, USA, February 22-26, 2026}},
pages = {1180--1184},
publisher = {ACM},
year = {2026},
url = {https://doi.org/10.1145/3773966.3779379},
doi = {https://doi.org/10.1145/3773966.3779379}
}