HEI: hybrid explicit-implicit learning for multiscale problems

Understand

Splitting is a method to handle application problems by splitting physics, scales, domain, and so on.

• Many splitting algorithms have been designed for efficient temporal discretization.
• In this paper, our goal is to use temporal splitting concepts in designing machine learning algorithms and, at the same time, help splitting algorithms by incorporating data and speeding them up.
• Since the spitting solution usually has an explicit and implicit part, we will call our method hybrid explicit-implict (HEI) learning.