Zhang-Yong Liang

Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers

Energy natural gradient descent (ENGD) aligns parameter updates with the curvature of an underlying function-space energy, but existing formulations assume an unconstrained Euclidean parameter domain. We introduce \EMNGDfull{}, a manifold optimization framework for physics-informed and variational neural PDE solvers wh...