A Self-supervised Approach to Hierarchical Forecasting with Applications to Groupwise Synthetic Controls

no code implementations • 25 Jun 2019 • Konstantin Mishchenko, Mallory Montgomery, Federico Vaggi

When forecasting time series with a hierarchical structure, the existing state of the art is to forecast each time series independently, and, in a post-treatment step, to reconcile the time series in a way that respects the hierarchy (Hyndman et al., 2011; Wickramasuriya et al., 2018).

counterfactual Time Series +1