Abstract: We propose a novel modeling framework that efficiently encodes seasonal climate predictions to provide robust and reliable time-series forecasting for supply chain functions. The encoding ...

Abstract: Existing spatio-temporal prediction networks that rely on recurrent neural networks face significant parallelization challenges, leading to high computational costs and prolonged training ...