3 papers
math.OC2026
Grassmannian Geometry and Global Convergence of Variable Projection for Neural Networks
Mathias Dus
Training deep neural networks and Physics-Informed Neural Networks (PINNs) often leads to ill-conditioned and stiff optimization problems. A key structural feature of these models…
math.OC2024
Comparison between tensor methods and neural networks in electronic structure calculations
Mathias Dus, Geneviève Dusson, Virginie Ehrlacher +2
This article compares the tensor method density matrix renormalization group (DMRG) with two neural network based methods -namely FermiNet and PauliNet) for determining the ground…
math.AP2024
Two-layers neural networks for Schr{ö}dinger eigenvalue problems
Mathias Dus, Ehrlacher Virginie
The aim of this article is to analyze numerical schemes using two-layer neural networks withinfinite width for the resolution of high-dimensional Schr{ö}dinger eigenvalue problems…