Abstract: Multivariate Time-Series (MTS) forecasting is challenging due to the complex spatial-temporal dependencies inherent in MTS data. Recent studies typically adopt spatial-temporal graph models ...

Abstract: We propose a novel method for learning time-varying graphs from time-series data by leveraging techniques from directed acyclic graph (DAG) learning. The unknown graphs are parameterized ...