LA-FEM

Solver-in-the-Loop joint operator learning: fractional Laplace-Beltrami features for interface reconstruction

arXiv:2411.05341v2 Announce Type: replace Abstract: In this work, we propose a joint operator learning method for reconstructing images of conductivity coefficients from boundary data. Inspired by the idea of employing partial differential equation (PDE) solvers as preconditioners for this inverse problem, we investigate a ``solver-in-the-loop'' training mechanism. It allows the interaction of learnable parameters integrated in a PDE solver module and those in neural networks for...