Three ways to solve partial differential equations with neural networks—A review
J Blechschmidt, OG Ernst - GAMM‐Mitteilungen, 2021 - Wiley Online Library
Neural networks are increasingly used to construct numerical solution methods for partial
differential equations. In this expository review, we introduce and contrast three important …
differential equations. In this expository review, we introduce and contrast three important …
Overview frequency principle/spectral bias in deep learning
Understanding deep learning is increasingly emergent as it penetrates more and more into
industry and science. In recent years, a research line from Fourier analysis sheds light on …
industry and science. In recent years, a research line from Fourier analysis sheds light on …
Deep nitsche method: Deep ritz method with essential boundary conditions
Y Liao, P Ming - ar** between infinite-
dimensional parameter and solution spaces of partial differential equations (PDEs). In this …
dimensional parameter and solution spaces of partial differential equations (PDEs). In this …
A deep domain decomposition method based on Fourier features
S Li, Y ** by Fourier neural network with transfer learning
The particle damper (PD) filled with granular material exhibits hysteretic behavior under
dynamic excitation, meaning that its response depends not only on the current excitation but …
dynamic excitation, meaning that its response depends not only on the current excitation but …