Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers

Finding accurate solutions to partial differential equations (PDEs) is a crucial task in all scientific and engineering disciplines. It has recently been shown that machine learning methods can improve the solution accuracy by correcting for effects not captured by the discretized PDE.