Approximation with Neural Networks in Variable Lebesgue Spaces

8 July 2020

Papers citing "Approximation with Neural Networks in Variable Lebesgue Spaces"

10 / 10 papers shown

Title
Smooth function approximation by deep neural networks with general activation functions Ilsang Ohn Yongdai Kim 52 80 0 17 Jun 2019
Universal Approximation with Deep Narrow Networks Patrick Kidger Terry Lyons 134 335 0 21 May 2019
Negative results for approximation using single layer and multilayer feedforward neural networks J. M. Almira P. E. López-de-Teruel D. J. Romero-Lopez F. Voigtlaender MLT 42 2 0 23 Oct 2018
Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality Taiji Suzuki 188 246 0 18 Oct 2018
Generalization and Expressivity for Deep Nets Shao-Bo Lin 59 45 0 10 Mar 2018
Optimal approximation of piecewise smooth functions using deep ReLU neural networks P. Petersen Felix Voigtländer 225 475 0 15 Sep 2017
Nonparametric regression using deep neural networks with ReLU activation function Johannes Schmidt-Hieber 240 816 0 22 Aug 2017
Optimal Approximation with Sparsely Connected Deep Neural Networks Helmut Bölcskei Philipp Grohs Gitta Kutyniok P. Petersen 199 256 0 04 May 2017
Error bounds for approximations with deep ReLU networks Dmitry Yarotsky 202 1,236 0 03 Oct 2016
Provable approximation properties for deep neural networks Uri Shaham A. Cloninger Ronald R. Coifman 185 231 0 24 Sep 2015