Approximation spaces of deep neural networks

3 May 2019

Rémi Gribonval

Papers citing "Approximation spaces of deep neural networks"

21 / 21 papers shown

Title
Theoretical Insights into CycleGAN: Analyzing Approximation and Estimation Errors in Unpaired Data Generation Luwei Sun Dongrui Shen Han Feng 40 2 0 16 Jul 2024
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations Akshay Kumar Jarvis D. Haupt ODL 44 3 0 12 Mar 2024
Mathematical Algorithm Design for Deep Learning under Societal and Judicial Constraints: The Algorithmic Transparency Requirement Holger Boche Adalbert Fono Gitta Kutyniok FaML 31 4 0 18 Jan 2024
Operator theory, kernels, and Feedforward Neural Networks P. Jorgensen Myung-Sin Song James Tian 35 0 0 03 Jan 2023
Approximation results for Gradient Descent trained Shallow Neural Networks in $1d$ R. Gentile G. Welper ODL 52 6 0 17 Sep 2022
Qualitative neural network approximation over R and C: Elementary proofs for analytic and polynomial activation Josiah Park Stephan Wojtowytsch 20 1 0 25 Mar 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 44 20 0 31 Jan 2022
Training Thinner and Deeper Neural Networks: Jumpstart Regularization Carles Roger Riera Molina Camilo Rey Thiago Serra Eloi Puertas O. Pujol 27 4 0 30 Jan 2022
Approximation of functions with one-bit neural networks C. S. Güntürk Weilin Li 17 8 0 16 Dec 2021
Sobolev-type embeddings for neural network approximation spaces Philipp Grohs F. Voigtlaender 14 1 0 28 Oct 2021
Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods Tobias Alt Karl Schrader Joachim Weickert Pascal Peter M. Augustin 22 4 0 31 Aug 2021
Proof of the Theory-to-Practice Gap in Deep Learning via Sampling Complexity bounds for Neural Network Approximation Spaces Philipp Grohs F. Voigtlaender 8 34 0 06 Apr 2021
The universal approximation theorem for complex-valued neural networks F. Voigtlaender 19 62 0 06 Dec 2020
Approximation of Smoothness Classes by Deep Rectifier Networks Mazen Ali A. Nouy 9 9 0 30 Jul 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 50 0 09 Jul 2020
Deep Network Approximation for Smooth Functions Jianfeng Lu Zuowei Shen Haizhao Yang Shijun Zhang 64 247 0 09 Jan 2020
Stochastic Feedforward Neural Networks: Universal Approximation Thomas Merkh Guido Montúfar 17 8 0 22 Oct 2019
NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation Anastasis Kratsios Cody B. Hyndman OOD 22 17 0 31 Aug 2018
On the stable recovery of deep structured linear networks under sparsity constraints F. Malgouyres 22 7 0 31 May 2017
Wider or Deeper: Revisiting the ResNet Model for Visual Recognition Zifeng Wu Chunhua Shen A. Hengel SSeg 260 1,491 0 30 Nov 2016
Benefits of depth in neural networks Matus Telgarsky 142 602 0 14 Feb 2016