Deep Ritz method for elliptical multiple eigenvalue problems (Q6182319)

scientific article; zbMATH DE number 7794703

Language	Label	Description	Also known as
English	Deep Ritz method for elliptical multiple eigenvalue problems	scientific article; zbMATH DE number 7794703

Statements

instance of

scholarly article

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title

Deep Ritz method for elliptical multiple eigenvalue problems (English)

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Journal of Scientific Computing

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publication date

25 January 2024

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zbMATH Keywords

elliptical multiple eigenvalue

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DRM

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FNN

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convergence rate

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MaRDI profile type

MaRDI publication profile

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full work available at URL

https://doi.org/10.1007/s10915-023-02443-8

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cites work

Q5381117

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Q4907706

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Friedrichs Learning: Weak Solutions of Partial Differential Equations via Deep Learning

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Bounds on the Poincaré constant for convolution measures

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Convergence Rate Analysis for Deep Ritz Method

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The sizes of compact subsets of Hilbert space and continuity of Gaussian processes

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Q5189317

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A sharp form of Whitney's extension theorem

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An eigenvalue problem for the Schrödinger-Maxwell equations

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SelectNet: self-paced learning for high-dimensional partial differential equations

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Solving high-dimensional partial differential equations using deep learning

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Solving many-electron Schrödinger equation using deep neural networks

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Solving high-dimensional eigenvalue problems using deep neural networks: a diffusion Monte Carlo like approach

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Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations

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Convergence of the Poincaré Constant

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On the Schrödinger equation and the eigenvalue problem

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A semigroup method for high dimensional elliptic PDEs and eigenvalue problems based on neural networks

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A priori generalization error analysis of two-layer neural networks for solving high dimensional Schrödinger eigenvalue problems

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DeepXDE: A Deep Learning Library for Solving Differential Equations

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Numerical Analysis of a Finite Element/Volume Penalty Method

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Estimates on the generalization error of physics-informed neural networks for approximating a class of inverse problems for PDEs

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Inferring solutions of differential equations using noisy multi-fidelity data

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Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

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DGM: a deep learning algorithm for solving partial differential equations

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

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Weak adversarial networks for high-dimensional partial differential equations

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Identifiers

DOI

10.1007/s10915-023-02443-8

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:6182319