arXiv:1904.07200

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• Link
• Title: A Discussion on Solving Partial Differential Equations using Neural Networks
• Keywords (optional):
• Authors (optional):
• Reason (optional):
• Summary (optional): Discretization, plug boundary condition into loss function. Possion solution reproduced
• Ideas (optional): I will maintain a list of work at the interplay between PDE and DL with particular focus on use NN ansatz to solve PDEs.

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Relevant work

• DGM: A deep learning algorithm for solving partial differential equations Just every person chooses to do: meshfree, MC sample batch, add boundary condition to the loss, nothing new
• Artiial Neural Networks for Solving Ordinary and Partial Differential Equations
• Accelerating Eulerian Fluid Simulation With Convolutional Networks
• Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
• Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations