Multivariate time series (MTS) forecasting penetrates various aspects of our economy and
society, whose roles become increasingly recognized. However, often MTS forecasting is …

Multivariate time-series (MTS) forecasting plays a crucial role in various real-world
applications, but the complex dependencies between time-series variables (ie, inter-series …

Industrial time series prediction (ITSP) is critical to the predictive maintenance system of
modern industry. However, time-varying conditions and complex industrial processes cause …

Multivariate time series (MTS) forecasting has a wide range of applications in both industry
and academia. Recently, spatial–temporal graph neural networks (STGNNs) have gained …

Deep graph clustering is a highly significant tool for community detection, enabling the
identification of strongly connected groups of nodes within a graph. This technology is …

The non-stationary nature of real-world Multivariate Time Series (MTS) data presents
forecasting models with a formidable challenge of the time-variant distribution of time series …

The performance of business processes such as order fulfillment, is measured and
monitored in terms of Key Performance Indicators (KPIs) measured at periodic time intervals …