Deep-Learning Solvers and Surrogates for Infinity and p-Laplace Problems

The paper investigates neural network solvers for infinity and p-Laplace problems, which arise in nonlinear analysis and have practical applications. It combines Physics-Informed Neural Networks and Deep Operator Networks to address computational challenges for large p values from 2 to 1000 on 2D and 3D domains.