Learning Functions: When Is Deep Better Than Shallow

3 March 2016

Papers citing "Learning Functions: When Is Deep Better Than Shallow"

22 / 22 papers shown

Title
Deep neural network approximation of composite functions without the curse of dimensionality Adrian Riekert 26 0 0 12 Apr 2023
Universal Approximation Property of Hamiltonian Deep Neural Networks M. Zakwan M. d’Angelo Giancarlo Ferrari-Trecate 36 5 0 21 Mar 2023
Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning Chi-Ken Lu Patrick Shafto BDL 27 4 0 01 Oct 2021
Tensor Methods in Computer Vision and Deep Learning Yannis Panagakis Jean Kossaifi Grigorios G. Chrysos James Oldfield M. Nicolaou Anima Anandkumar S. Zafeiriou 27 119 0 07 Jul 2021
Wide-band butterfly network: stable and efficient inversion via multi-frequency neural networks Matthew T.C. Li L. Demanet Leonardo Zepeda-Núnez 35 8 0 24 Nov 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 51 0 09 Jul 2020
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 35 122 0 23 Jun 2019
A Selective Overview of Deep Learning Jianqing Fan Cong Ma Yiqiao Zhong BDL VLM 36 136 0 10 Apr 2019
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs Gitta Kutyniok P. Petersen Mones Raslan R. Schneider 20 197 0 31 Mar 2019
BCR-Net: a neural network based on the nonstandard wavelet form Yuwei Fan Cindy Orozco Bohorquez Lexing Ying 15 47 0 20 Oct 2018
Training Deeper Neural Machine Translation Models with Transparent Attention Ankur Bapna Mengzhao Chen Orhan Firat Yuan Cao Yonghui Wu 29 138 0 22 Aug 2018
Deep Multiscale Model Learning Yating Wang Siu Wun Cheung Eric T. Chung Y. Efendiev Min Wang AI4CE 19 79 0 13 Jun 2018
Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks Yingzhou Li Xiuyuan Cheng Jianfeng Lu 21 23 0 18 May 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 27 294 0 10 Feb 2018
On the Compressive Power of Deep Rectifier Networks for High Resolution Representation of Class Boundaries Senjian An Bennamoun F. Boussaïd 18 2 0 24 Aug 2017
The power of deeper networks for expressing natural functions David Rolnick Max Tegmark 36 174 0 16 May 2017
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions Nadav Cohen Or Sharir Yoav Levine Ronen Tamari David Yakira Amnon Shashua 20 38 0 05 May 2017
Why does deep and cheap learning work so well? Henry W. Lin Max Tegmark David Rolnick 19 602 0 29 Aug 2016
On the Expressive Power of Deep Neural Networks M. Raghu Ben Poole Jon M. Kleinberg Surya Ganguli Jascha Narain Sohl-Dickstein 27 777 0 16 Jun 2016
Inductive Bias of Deep Convolutional Networks through Pooling Geometry Nadav Cohen Amnon Shashua 22 132 0 22 May 2016
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex Q. Liao T. Poggio 213 255 0 13 Apr 2016
MatConvNet - Convolutional Neural Networks for MATLAB Andrea Vedaldi Karel Lenc 183 2,946 0 15 Dec 2014