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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Vydané v:	IEEE transactions on knowledge and data engineering Ročník 35; číslo 9; s. 9168 - 9180
Hlavní autori:	Jin, Ming, Zheng, Yu, Li, Yuan-Fang, Chen, Siheng, Yang, Bin, Pan, Shirui
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.09.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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