Solving PDEs on spheres with physics-informed convolutional neural networks (Q6652574)

scientific article; zbMATH DE number 7957712

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English	Solving PDEs on spheres with physics-informed convolutional neural networks	scientific article; zbMATH DE number 7957712

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instance of

scholarly article

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title

Solving PDEs on spheres with physics-informed convolutional neural networks (English)

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Applied and Computational Harmonic Analysis

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publication date

12 December 2024

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zbMATH Keywords

physics-informed neural network

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convolutional neural network

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solving PDEs on spheres

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convergence analysis

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curse of dimensionality

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Publication

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cites work

Estimates near the boundary for solutions of elliptic partial differential equations satisfying general boundary conditions. I

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Point sets on the sphere \(\mathbb{S}^{2}\) with small spherical cap discrepancy

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Physics-informed neural networks for shell structures

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Nonparametric regression on low-dimensional manifolds using deep ReLU networks: function approximation and statistical recovery

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Approximation Theory and Harmonic Analysis on Spheres and Balls

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A Rate of Convergence of Physics Informed Neural Networks for the Linear Second Order Elliptic PDEs

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Deep ReLU Networks Overcome the Curse of Dimensionality for Generalized Bandlimited Functions

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New Error Bounds for Deep ReLU Networks Using Sparse Grids

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DGM: a deep learning algorithm for solving partial differential equations

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Bayesian manifold regression

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Learning and approximation by Gaussians on Riemannian manifolds

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Identifiers

DOI

10.1016/j.acha.2024.101714

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Mathematics Subject Classification ID

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Mathematics(1 entry)

mardi Publication:6652574