3 code implementations • 15 Sep 2021 • Nils Wandel, Michael Weinmann, Michael Neidlin, Reinhard Klein
Second, convolutional neural networks provide fast inference and generalize but either require large amounts of training data or a physics-constrained loss based on finite differences that can lead to inaccuracies and discretization artifacts.
