6 citations · 8 across the 7 of their papers we have counts for
13 papers
Classification of anisotropic Triebel-Lizorkin spaces
Sarah Koppensteiner, Jordy Timo van Velthoven, Felix Voigtlaender
This paper provides a classification theorem for expansive matrices generating the same anisotropic homogeneous Triebel-Lizorkin space $\dot{\mat…
Sobolev-type embeddings for neural network approximation spaces
Philipp Grohs, Felix Voigtlaender
We consider neural network approximation spaces that classify functions according to the rate at which they can be approximated (with error measured in ) by ReLU neural networ…
A note on the invertibility of the Gabor frame operator on certain modulation spaces
Dae Gwan Lee, Friedrich Philipp, Felix Voigtlaender
We consider Gabor frames generated by a general lattice and a window function that belongs to one of the following spaces: the Sobolev space , the weighted…
Proof of the Theory-to-Practice Gap in Deep Learning via Sampling Complexity bounds for Neural Network Approximation Spaces
Philipp Grohs, Felix Voigtlaender
We study the computational complexity of (deterministic or randomized) algorithms based on point samples for approximating or integrating functions that can be well approximated by…
Phase Transitions in Rate Distortion Theory and Deep Learning
Philipp Grohs, Andreas Klotz, Felix Voigtlaender
Rate distortion theory is concerned with optimally encoding a given signal class using a budget of bits, as . We say that can be compres…
Schur-type Banach modules of integral kernels acting on mixed-norm Lebesgue spaces
Nicki Holighaus, Felix Voigtlaender
Schur's test states that if satisfies and , then the associated integral operator acts boundedly…