GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing-Reference-Cited by-同舟云学术

GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing

Published:2024-08-24 Issue: Volume:34 Page:3989-4000
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Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Yu Chengqing¹^ORCID,Wang Fei²^ORCID,Shao Zezhi¹^ORCID,Qian Tangwen³^ORCID,Zhang Zhao³^ORCID,Wei Wei⁴^ORCID,Xu Yongjun³^ORCID

Affiliation:

1. Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China

2. Institute of Computig Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China

3. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

4. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

Funder

National Natural Science Foundation of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3672055

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