Mini-batch optimization enables training of ODE models on large-scale datasets

Abstract

Ordinary differential equation (ODE) models are widely used to understand multiple processes. Here the authors show how the concept of mini-batch optimization can be transferred from the field of Deep Learning to ODE modelling.