Dirichlet-to-Neumann and Calderon operator via deep learning techniques.

Abstract: In this talk we consider the Dirichlet-to-Neumann operator and the Calderón mapping appearing in Calderon’s inverse problem. Using deep learning techniques, we prove that these maps are rigorously approximated by infinite-dimensional neural networks.