The Expressive Power of Neural Networks: A View from the Width

8 September 2017

Papers citing "The Expressive Power of Neural Networks: A View from the Width"

38 / 138 papers shown

Title
Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations Christopher J. Arthurs A. King PINN 43 51 0 02 May 2020
On Deep Instrumental Variables Estimate Ruiqi Liu Zuofeng Shang Guang Cheng 26 26 0 30 Apr 2020
It's Not What Machines Can Learn, It's What We Cannot Teach Gal Yehuda Moshe Gabel Assaf Schuster FaML 14 37 0 21 Feb 2020
A closer look at the approximation capabilities of neural networks Kai Fong Ernest Chong 21 16 0 16 Feb 2020
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets Gauthier Gidel David Balduzzi Wojciech M. Czarnecki M. Garnelo Yoram Bachrach 15 7 0 14 Feb 2020
Invariant Risk Minimization Games Kartik Ahuja Karthikeyan Shanmugam Kush R. Varshney Amit Dhurandhar OOD 33 244 0 11 Feb 2020
Deep Network Approximation for Smooth Functions Jianfeng Lu Zuowei Shen Haizhao Yang Shijun Zhang 67 247 0 09 Jan 2020
Sparse Weight Activation Training Md Aamir Raihan Tor M. Aamodt 34 73 0 07 Jan 2020
Deep Learning via Dynamical Systems: An Approximation Perspective Qianxiao Li Ting Lin Zuowei Shen AI4TS AI4CE 25 107 0 22 Dec 2019
Are Transformers universal approximators of sequence-to-sequence functions? Chulhee Yun Srinadh Bhojanapalli A. S. Rawat Sashank J. Reddi Sanjiv Kumar 14 335 0 20 Dec 2019
Deep Learning-based Limited Feedback Designs for MIMO Systems Jeonghyeon Jang Hoon Lee S. Hwang Haibao Ren Inkyu Lee AI4CE 30 32 0 19 Dec 2019
Analysis of Deep Neural Networks with Quasi-optimal polynomial approximation rates Joseph Daws Clayton Webster 30 8 0 04 Dec 2019
Neural Contextual Bandits with UCB-based Exploration Dongruo Zhou Lihong Li Quanquan Gu 36 15 0 11 Nov 2019
Stochastic Feedforward Neural Networks: Universal Approximation Thomas Merkh Guido Montúfar 17 8 0 22 Oct 2019
DirectPET: Full Size Neural Network PET Reconstruction from Sinogram Data W. Whiteley W. K. Luk J. Gregor 3DV AI4TS 29 54 0 19 Aug 2019
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks Alejandro Molina P. Schramowski Kristian Kersting ODL 23 78 0 15 Jul 2019
Densely Connected Search Space for More Flexible Neural Architecture Search Jiemin Fang Yuzhu Sun Qian Zhang Yuan Li Wenyu Liu Xinggang Wang 21 122 0 23 Jun 2019
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 35 122 0 23 Jun 2019
The phase diagram of approximation rates for deep neural networks Dmitry Yarotsky Anton Zhevnerchuk 30 121 0 22 Jun 2019
Deep Network Approximation Characterized by Number of Neurons Zuowei Shen Haizhao Yang Shijun Zhang 23 182 0 13 Jun 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 11 17,761 0 28 May 2019
Universal Approximation with Deep Narrow Networks Patrick Kidger Terry Lyons 40 328 0 21 May 2019
Nonlinear Approximation via Compositions Zuowei Shen Haizhao Yang Shijun Zhang 26 92 0 26 Feb 2019
A Survey of the Recent Architectures of Deep Convolutional Neural Networks Asifullah Khan A. Sohail Umme Zahoora Aqsa Saeed Qureshi OOD 65 2,271 0 17 Jan 2019
Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections Jian-Feng Cai Dong Li Jiaze Sun Ke Wang 30 5 0 22 Nov 2018
On a Sparse Shortcut Topology of Artificial Neural Networks Fenglei Fan Dayang Wang Hengtao Guo Qikui Zhu Pingkun Yan Ge Wang Hengyong Yu 38 22 0 22 Nov 2018
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 33 446 0 21 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du J. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 44 1,125 0 09 Nov 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 28 117 0 17 Oct 2018
Universal Approximation with Quadratic Deep Networks Fenglei Fan Jinjun Xiong Ge Wang PINN 36 78 0 31 Jul 2018
ResNet with one-neuron hidden layers is a Universal Approximator Hongzhou Lin Stefanie Jegelka 43 227 0 28 Jun 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 57 1,395 0 22 Jun 2018
Learning One-hidden-layer ReLU Networks via Gradient Descent Xiao Zhang Yaodong Yu Lingxiao Wang Quanquan Gu MLT 30 134 0 20 Jun 2018
The Effect of Network Width on the Performance of Large-batch Training Lingjiao Chen Hongyi Wang Jinman Zhao Dimitris Papailiopoulos Paraschos Koutris 21 22 0 11 Jun 2018
Understanding Generalization and Optimization Performance of Deep CNNs Pan Zhou Jiashi Feng MLT 30 48 0 28 May 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 27 294 0 10 Feb 2018
The power of deeper networks for expressing natural functions David Rolnick Max Tegmark 36 174 0 16 May 2017
Benefits of depth in neural networks Matus Telgarsky 153 603 0 14 Feb 2016