cross-variable-loss

This paper identifies an objective gap in Direct Forecasting for multivariate time series and proposes CvLoss, a plug-in structural regularizer that constrains forecast residuals on a cross-variable graph to improve consistency across synchronous and asynchronous interactions. Experiments show consistent improvements over competitive forecasting models.