Physics-informed machine learning with neural network, or PINNs, is a recent and active field of research aiming to use mechanistic modeling (ODE/PDE) together with machine learning and statistics. In this talk, we will introduce and explain the PINNs methodology, and discuss various interesting research directions from a statistical and numerical point-of-view. We will also present our contribution with the jinns python package for efficiently training PINNs with JAX. This work is still in progress and we are open to suggestion and collaborations.
Package & documentation can be found here : https://gitlab.com/mia_jinns/jinns