1 citations · 1 across the 4 of their papers we have counts for
4 papers
Bases of Lebesgue spaces formed by neural networks
Vladimir Kulbatov, Jan Lang, Cornelia Schneider +1
The seminal work of Daubechies, DeVore, Foucart, Hanin, and Petrova introduced in 2022 a sequence of univariate piece-wise linear functions, which resemble the classical Fourier ba…
Nonlocal techniques for the analysis of deep ReLU neural network approximations
Cornelia Schneider, Mario Ullrich, Jan Vybiral
Recently, Daubechies, DeVore, Foucart, Hanin, and Petrova introduced a system of piece-wise linear functions, which can be easily reproduced by artificial neural networks with the…
Improved universal approximation with neural networks studied via affine-invariant subspaces of
Cornelia Schneider, Samuel Probst
We show that there are no non-trivial closed subspaces of that are invariant under invertible affine transformations. We apply this result to neural networks sh…
Sobolev spaces with mixed weights and the Poisson equation on angular domains
Petru A. Cioica-Licht, Cornelia Schneider, Markus Weimar
We introduce and analyse a class of weighted Sobolev spaces with mixed weights on angular domains. The weights are based on both the distance to the boundary and the distance to th…