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20162026
most citedDeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

3.4k citations · 4.7k across the 10 of their papers we have counts for

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physics.comp-ph2018★ 1.1k cited

fPINNs: Fractional Physics-Informed Neural Networks

Guofei Pang, Lu Lu, George Em Karniadakis

Physics-informed neural networks (PINNs) are effective in solving integer-order partial differential equations (PDEs) based on scattered and noisy data. PINNs employ standard feedf…

physics.comp-ph2018

A new radial basis function collocation method based on the quasi-uniform nodes for 2D fractional wave equation

Yiran Xu, Jingye Li, Guofei Pang +3

We mainly concerned with a decoupled fractional Laplacian wave equation in this paper. A new time-space domain radial basis function (RBF) collocation method is introduced to solve…