Deep-Picard iteration uses supervised neural networks trained on Monte Carlo labels from beta-stable subordinators and alpha-stable Levy walks to approximate solutions of high-dimensional fractional PDEs up to dimension 100.
Numerical methods for time-fractional evolution equations with nonsmooth data: A concise overview
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Deep-Picard Iteration for Space-time Fractional Diffusion PDEs
Deep-Picard iteration uses supervised neural networks trained on Monte Carlo labels from beta-stable subordinators and alpha-stable Levy walks to approximate solutions of high-dimensional fractional PDEs up to dimension 100.