Neural Network Preconditioning: A Case Study for the Solution of the Parametric Helmholtz Equation
A U-Net based convolutional neural network is trained self-supervised to approximate the inverse of a discretized Helmholtz operator. This trained network is then used as a nonlinear preconditioner within the flexible GMRES algorithm to solve linear systems from parametric Helmholtz equations, significantly improving convergence speed.