Neural networks trained on scalar diffusion data predict adaptive coarse basis functions for Schwarz methods, transferring without retraining to linear elasticity and nonlinear p-Laplace problems.
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Learning Adaptive Coarse Spaces Using Transferable Neural Network Models for Linear and Nonlinear Overlapping Domain Decomposition Methods
Neural networks trained on scalar diffusion data predict adaptive coarse basis functions for Schwarz methods, transferring without retraining to linear elasticity and nonlinear p-Laplace problems.