Spectral Temporal Graph Neural Network for Multivariate Time-Series Forecasting
Abstract
Multivariate time-series forecasting plays a crucial role in many real-world applications. It is a challenging problem as one needs to consider both intra-series temporal correlations and inter-series correlations simultaneously. Recently, there have been multiple works trying to capture both correlations, but most, if not all of them only capture temporal correlations in the time domain and resort to pre-defined priors as inter-series relationships.
Cite
Text
Cao et al. "Spectral Temporal Graph Neural Network for Multivariate Time-Series Forecasting." Neural Information Processing Systems, 2020.Markdown
[Cao et al. "Spectral Temporal Graph Neural Network for Multivariate Time-Series Forecasting." Neural Information Processing Systems, 2020.](https://mlanthology.org/neurips/2020/cao2020neurips-spectral/)BibTeX
@inproceedings{cao2020neurips-spectral,
title = {{Spectral Temporal Graph Neural Network for Multivariate Time-Series Forecasting}},
author = {Cao, Defu and Wang, Yujing and Duan, Juanyong and Zhang, Ce and Zhu, Xia and Huang, Congrui and Tong, Yunhai and Xu, Bixiong and Bai, Jing and Tong, Jie and Zhang, Qi},
booktitle = {Neural Information Processing Systems},
year = {2020},
url = {https://mlanthology.org/neurips/2020/cao2020neurips-spectral/}
}