Interpretable Sequence Learning for COVID-19 Forecasting

Sercan O. Arik, Chun-Liang Li, Jinsung Yoon +12

We propose a novel approach that integrates machine learning into compartmental disease modeling to predict the progression of COVID-19. Our model is explainable by design as it ex…