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Approximation properties of residual neural networks for Kolmogorov PDEs - MaRDI portal

Approximation properties of residual neural networks for Kolmogorov PDEs (Q2697245)

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scientific article; zbMATH DE number 7675805

Language	Label	Description	Also known as
English	Approximation properties of residual neural networks for Kolmogorov PDEs	scientific article; zbMATH DE number 7675805

Statements

scholarly article

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Approximation properties of residual neural networks for Kolmogorov PDEs (English)

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Jonas Baggenstos

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Diyora Salimova

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Discrete and Continuous Dynamical Systems. Series B

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publication date

18 April 2023

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full work available at URL

https://arxiv.org/abs/2111.00215

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zbMATH Keywords

residual neural networks

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Kolmogorov PDEs

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resnets

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Euler-Maruyama approximations

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Feynman-Kac formula

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MaRDI profile type

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Neural ODEs as the deep limit of ResNets with constant weights

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Solving the Kolmogorov PDE by means of deep learning

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Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations

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The Deep Ritz Method: a deep learning-based numerical algorithm for solving variational problems

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DNN expression rate analysis of high-dimensional PDEs: application to option pricing

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Approximation spaces of deep neural networks

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Deep neural network approximation for high-dimensional elliptic PDEs with boundary conditions

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Deep neural network approximations for solutions of PDEs based on Monte Carlo algorithms

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Loss of regularity for Kolmogorov equations

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Solving high-dimensional partial differential equations using deep learning

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Proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients

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Über die analytischen Methoden in der Wahrscheinlichkeitsrechnung

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Stochastic PDE's and Kolmogorov equations in infinite dimensions. Lectures given at the 2nd session of the Centro Internazionale Matematico Estivo (CIME) held in Cetraro, Italy, August 24 - September 1, 1998

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A theoretical analysis of deep neural networks and parametric PDEs

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Navigation of autonomous mobile robot using different activation functions of wavelet neural network

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Optimal approximation of piecewise smooth functions using deep ReLU neural networks

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Data driven governing equations approximation using deep neural networks

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Identifiers

Mathematics Subject Classification ID

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zbMATH DE Number

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10.3934/DCDSB.2022210

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Sitelinks

Mathematics(1 entry)

mardi Publication:2697245

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