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arXiv Machine Learning By Ilkhom Mukhammadiev, Diyora Salimova

Residual neural networks overcome the curse of dimensionality for semilinear heat equations

Read the original on arXiv Machine Learning →

arXiv:2609. 03626v1 Announce Type: cross Abstract: Rigorous results show that feedforward neural networks can overcome the curse of dimensionality in the numerical approximation of high-dimensional partial differential equations (PDEs), but comparatively little is known about residual neural networks (ResNets) in the nonlinear PDE setting.

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