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

License: See LICENSE file · Updated 2026-09-25
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This research focuses on neural network solvers for infinity and p-Laplace problems, which arise in nonlinear analysis. The study applies Physics-Informed Neural Networks and Deep Operator Networks to 2D and 3D domains, addressing computational challenges across p values from 2 to 1000. The method is presented as an alternative to traditional physics-based solvers.

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