Why Deep Neural Networks for Function Approximation?

13 October 2016

Papers citing "Why Deep Neural Networks for Function Approximation?"

10 / 60 papers shown

Title
Dialectical GAN for SAR Image Translation: From Sentinel-1 to TerraSAR-X Dongyang Ao C. Dumitru G. Schwarz Mihai Datcu GAN 17 42 0 20 Jul 2018
ResNet with one-neuron hidden layers is a Universal Approximator Hongzhou Lin Stefanie Jegelka 36 227 0 28 Jun 2018
The universal approximation power of finite-width deep ReLU networks Dmytro Perekrestenko Philipp Grohs Dennis Elbrächter Helmut Bölcskei 13 36 0 05 Jun 2018
Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks Yingzhou Li Xiuyuan Cheng Jianfeng Lu 21 23 0 18 May 2018
Analysis on the Nonlinear Dynamics of Deep Neural Networks: Topological Entropy and Chaos Husheng Li 17 11 0 03 Apr 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 13 293 0 10 Feb 2018
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank Liang Zhao Siyu Liao Yanzhi Wang Zhe Li Jian Tang Victor Pan Bo Yuan 31 61 0 01 Mar 2017
Understanding Deep Neural Networks with Rectified Linear Units R. Arora A. Basu Poorya Mianjy Anirbit Mukherjee PINN 30 633 0 04 Nov 2016
Error bounds for approximations with deep ReLU networks Dmitry Yarotsky 30 1,223 0 03 Oct 2016
Benefits of depth in neural networks Matus Telgarsky 148 602 0 14 Feb 2016