Author:
Pang Subeen,Barbastathis George
Abstract
We propose a neural network regularizer that mitigates the ill-conditionedness of the Lippmann-Schwinger equation. By learning the physics, it can significantly reduce the computational time and can be generalizable to objects unseen during the training.