A finite-element-inspired neural network with locally focused basis blocks and an adaptive refinement loop solves PDEs with sharp features more accurately than standard PINNs in the reported experiments.
Modeling subgrid-scale forces by spatial artificial neural networks in large eddy simulation of turbulence
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Adaptive Basis-inspired Deep Neural Network for Solving Partial Differential Equations with Localized Features
A finite-element-inspired neural network with locally focused basis blocks and an adaptive refinement loop solves PDEs with sharp features more accurately than standard PINNs in the reported experiments.