PINNs error estimates for nonlinear equations in $\mathbb{R}$-smooth Banach spaces

Fuente: arXiv
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Autores principales: Gao, Jiexing, Zakharian, Yurii
Formato: Preprint
Publicado: 2023
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author Gao, Jiexing
Zakharian, Yurii
author_facet Gao, Jiexing
Zakharian, Yurii
contents In the paper, we describe in operator form classes of PDEs that admit PINN's error estimation. Also, for $L^p$ spaces, we obtain a Bramble-Hilbert type lemma that is a tool for PINN's residuals bounding.
format Preprint
id arxiv_https___arxiv_org_abs_2305_11915
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle PINNs error estimates for nonlinear equations in $\mathbb{R}$-smooth Banach spaces
Gao, Jiexing
Zakharian, Yurii
Functional Analysis
Machine Learning
Numerical Analysis
In the paper, we describe in operator form classes of PDEs that admit PINN's error estimation. Also, for $L^p$ spaces, we obtain a Bramble-Hilbert type lemma that is a tool for PINN's residuals bounding.
title PINNs error estimates for nonlinear equations in $\mathbb{R}$-smooth Banach spaces
topic Functional Analysis
Machine Learning
Numerical Analysis
url https://arxiv.org/abs/2305.11915