Lucien D Werner

End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series

This paper presents a novel approach for hierarchical time series forecasting that produces coherent, probabilistic forecasts without requiring any explicit post-processing reconciliation. Unlike the state-of-the-art, the proposed method simultaneously learns from all time series in the hierarchy an…