Causal-oriented representation learning for time-series forecasting based on the spatiotemporal information transformation

Causal-oriented representation learning for time-series forecasting based on the spatiotemporal information transformation

Abstract In real-world high-dimensional systems, both causal dependencies and temporal information of key variables are essential for dissecting the underlying mechanisms governing system dynamics. However, effective approaches to synthesize these two interconnected aspects for deeper insights remai...

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Bibliographic Details
Main Authors:	Sihua Cai, Hao Peng, Rui Liu, Pei Chen
Format:	Article
Language:	English
Published:	Nature Portfolio 2025-06-01
Series:	Communications Physics
Online Access:	https://doi.org/10.1038/s42005-025-02170-6
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