Learned iterative solvers for the Helmholtz equation

We propose a ‘learned’ iterative solver for the Helmholtz equation, by combining traditional Krylov-based solvers with machine learning. The method is, in principle, able to circumvent the shortcomings of classical iterative solvers, and has clear advantages over purely data-driven ap- proaches. We demonstrate the effectiveness of this approach under a 1.5-D assumption, when ade- quate a priori information about the velocity distribution is known.

https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2019/rizzut...