AI RESEARCH
GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables
arXiv CS.LG
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ArXi:2603.08032v1 Announce Type: new Exogenous variables offer valuable supplementary information for predicting future endogenous variables. Forecasting with exogenous variables needs to consider both past-to-future dependencies (i.e., temporal correlations) and the influence of exogenous variables on endogenous variables (i.e., channel correlations). This is pivotal when future exogenous variables are available, because they may directly affect the future endogenous variables.