Multivariate Time Series Forecasting With Dynamic Graph Neural ODEs

Multivariate time series forecasting has long received significant attention in real-world applications, such as energy consumption and traffic prediction. While recent methods demonstrate good forecasting abilities, they have three fundamental limitations. (i). Discrete neural architectures: Interl...

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Bibliographic Details

Published in:	IEEE transactions on knowledge and data engineering Vol. 35; no. 9; pp. 9168 - 9180
Main Authors:	Jin, Ming, Zheng, Yu, Li, Yuan-Fang, Chen, Siheng, Yang, Bin, Pan, Shirui
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.09.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Computational modeling Electronic mail Energy consumption Forecasting graph neural networks Mathematical models Message passing Multivariate analysis Multivariate time series forecasting neural ordinary differential equations Predictive models Time series Time series analysis Topology Trajectory
ISSN:	1041-4347, 1558-2191
Online Access:	Get full text
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