Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction.
Xinke Jiang|Dingyi Zhuang|Xianghui Zhang|Hao Chen|Jiayuan Luo|Xiaowei Gao
| Anthology ID: | DBLP:conf/cikm/JiangZZCLG23 |
|---|---|
| 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: | 3983-3987 |
| URL: | https://doi.org/10.1145/3583780.3615215 |
| DOI: | https://doi.org/10.1145/3583780.3615215 |
| DBLP: | conf/cikm/JiangZZCLG23 |
| BibTeX: |
@inproceedings{jiang-2023-uncertainty,
author = {Xinke Jiang and
Dingyi Zhuang and
Xianghui Zhang and
Hao Chen and
Jiayuan Luo and
Xiaowei Gao},
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 = {{Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction}},
booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}},
pages = {3983--3987},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3583780.3615215},
doi = {https://doi.org/10.1145/3583780.3615215}
}