ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis.
Mingyue Cheng|Jiqian Yang|Tingyue Pan|Qi Liu|Zhi Li|Shijin Wang
| Anthology ID: | DBLP:conf/www/ChengYP00W25 |
|---|---|
| Volume: | Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025 |
| Year: | 2025 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 171-180 |
| URL: | https://doi.org/10.1145/3701716.3715214 |
| DOI: | https://doi.org/10.1145/3701716.3715214 |
| DBLP: | conf/www/ChengYP00W25 |
| BibTeX: |
@inproceedings{cheng-2025-convtimenet,
author = {Mingyue Cheng and
Jiqian Yang and
Tingyue Pan and
Qi Liu and
Zhi Li and
Shijin Wang},
editor = {Guodong Long and
Michale Blumestein and
Yi Chang and
Liane Lewin-Eytan and
Zi Huang and
Elad Yom-Tov},
title = {{ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis}},
booktitle = {{Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025}},
pages = {171--180},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3701716.3715214},
doi = {https://doi.org/10.1145/3701716.3715214}
}