Deep-Learning Solvers and Surrogates for Infinity and p-Laplace Problems
This work employs Physics-Informed Neural Networks and Deep Operator Networks to address computational challenges associated with large $p$ values, ranging from $2 to $1000$, on various 2D and 3D domains and establishes conditional convergence results for PINN approximations of both problems.
T.-Y. Yeung, Ka-Chun Cheung, Hannah Potgieter et al.
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