IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients

We introduce a novel neural operator architecture designed to approximate solutions of linear elliptic partial differential equations with high-contrast, spatially varying coefficients. The network, termed the Iterated V-shaped Net (IV-Net), realizes a mapping from the input coefficients and righthand side to the corresponding solution field. The IV-Net model is parameterized via convolutional layers de