2024
An operator preconditioning perspective on training in physics-informed machine learning
ICLR 2024poster
In this paper, we investigate the behavior of gradient descent algorithms in physics-informed machine learning methods like PINNs, which minimize residuals connected to partial differential equations (PDEs). Our key result is that the difficulty in training these models is closely related to the con…