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Found 3 papers, 1 papers with code
Moving Sampling Physics-informed Neural Networks induced by Moving Mesh PDE
In this work, we propose an end-to-end adaptive sampling neural network (MMPDE-Net) based on the moving mesh method, which can adaptively generate new sampling points by solving the moving mesh PDE.
On the uncertainty analysis of the data-enabled physics-informed neural network for solving neutron diffusion eigenvalue problem
In practical engineering experiments, the data obtained through detectors are inevitably noisy.
Neural Networks Based on Power Method and Inverse Power Method for Solving Linear Eigenvalue Problems
In this article, we propose two kinds of neural networks inspired by power method and inverse power method to solve linear eigenvalue problems.
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