Barron Space Representations for Elliptic PDEs with Homogeneous Boundary Conditions
Numerical Analysis
2025-10-21 v2 Machine Learning
Numerical Analysis
Analysis of PDEs
Abstract
We study the approximation complexity of high-dimensional second-order elliptic PDEs with homogeneous boundary conditions on the unit hypercube, within the framework of Barron spaces. Under the assumption that the coefficients belong to suitably defined Barron spaces, we prove that the solution can be efficiently approximated by two-layer neural networks, circumventing the curse of dimensionality. Our results demonstrate the expressive power of shallow networks in capturing high-dimensional PDE solutions under appropriate structural assumptions.
Keywords
Cite
@article{arxiv.2508.07559,
title = {Barron Space Representations for Elliptic PDEs with Homogeneous Boundary Conditions},
author = {Ziang Chen and Liqiang Huang},
journal= {arXiv preprint arXiv:2508.07559},
year = {2025}
}