2 papers
cs.LG2024
Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks
Felix Dangel, Johannes Müller, Marius Zeinhofer
Physics-informed neural networks (PINNs) are infamous for being hard to train. Recently, second-order methods based on natural gradient and Gauss-Newton methods have shown promisin…
math.OC2024
Position: Optimization in SciML Should Employ the Function Space Geometry
Johannes Müller, Marius Zeinhofer
Scientific machine learning (SciML) is a relatively new field that aims to solve problems from different fields of natural sciences using machine learning tools. It is well-documen…