Higher-order Spatio-temporal Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation.
Guojun Liang|Prayag Tiwari|Slawomir Nowaczyk|Stefan Byttner
| Anthology ID: | DBLP:conf/cikm/LiangTNB24 |
|---|---|
| Volume: | Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024 |
| Year: | 2024 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 1356-1366 |
| URL: | https://doi.org/10.1145/3627673.3679775 |
| DOI: | https://doi.org/10.1145/3627673.3679775 |
| DBLP: | conf/cikm/LiangTNB24 |
| BibTeX: |
@inproceedings{liang-2024-higherorder,
author = {Guojun Liang and
Prayag Tiwari and
Slawomir Nowaczyk and
Stefan Byttner},
editor = {Edoardo Serra and
Francesca Spezzano},
title = {{Higher-order Spatio-temporal Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation}},
booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}},
pages = {1356--1366},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3627673.3679775},
doi = {https://doi.org/10.1145/3627673.3679775}
}