S. Pei

Learning shared forecast-error structure to improve ensemble forecasts of seasonal respiratory outbreaks

A deep learning framework is developed that learns structured residual errors from historical forecasts and uses them to correct ensemble predictions, improving influenza hospitalization forecasts across horizons and geographic scales and providing a generalizable approach for improving real-time epidemic forecasts.