The Power of Depth for Feedforward Neural Networks

12 December 2015

Papers citing "The Power of Depth for Feedforward Neural Networks"

50 / 367 papers shown

Title
When Can Neural Networks Learn Connected Decision Regions? Trung Le Dinh Q. Phung MLT 23 1 0 25 Jan 2019
On Connected Sublevel Sets in Deep Learning Quynh N. Nguyen 19 102 0 22 Jan 2019
Deep Neural Network Approximation Theory Dennis Elbrächter Dmytro Perekrestenko Philipp Grohs Helmut Bölcskei 16 207 0 08 Jan 2019
The capacity of feedforward neural networks Pierre Baldi Roman Vershynin 17 67 0 02 Jan 2019
Fast convergence rates of deep neural networks for classification Yongdai Kim Ilsang Ohn Dongha Kim 3DH 3DV 11 79 0 10 Dec 2018
On variation of gradients of deep neural networks Yongdai Kim Dongha Kim ODL FAtt MLT 17 0 0 02 Dec 2018
Sequentially Aggregated Convolutional Networks Yiwen Huang Rihui Wu Pinglai Ou Ziyong Feng 21 1 0 27 Nov 2018
A Differential Topological View of Challenges in Learning with Feedforward Neural Networks Hao Shen AAML AI4CE 23 6 0 26 Nov 2018
Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections Jian-Feng Cai Dong Li Jiaze Sun Ke Wang 22 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
Data Driven Governing Equations Approximation Using Deep Neural Networks Tong Qin Kailiang Wu D. Xiu PINN 34 270 0 13 Nov 2018
Statistical Characteristics of Deep Representations: An Empirical Investigation Daeyoung Choi Kyungeun Lee Changho Shin Stephen J. Roberts AI4TS 18 2 0 08 Nov 2018
Convergence of the Deep BSDE Method for Coupled FBSDEs Jiequn Han Jihao Long 13 156 0 03 Nov 2018
Size-Noise Tradeoffs in Generative Networks Bolton Bailey Matus Telgarsky 21 20 0 26 Oct 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 26 117 0 17 Oct 2018
On the Approximation Properties of Random ReLU Features Yitong Sun A. Gilbert Ambuj Tewari 10 3 0 10 Oct 2018
Deep Neural Network Compression for Aircraft Collision Avoidance Systems Kyle D. Julian Mykel J. Kochenderfer Michael P. Owen 20 169 0 09 Oct 2018
Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units Yixi Xu Tianlin Li MQ 31 12 0 03 Oct 2018
Image as Data: Automated Visual Content Analysis for Political Science Jungseock Joo Zachary C. Steinert-Threlkeld 24 40 0 03 Oct 2018
Deep, Skinny Neural Networks are not Universal Approximators Jesse Johnson 11 65 0 30 Sep 2018
The jamming transition as a paradigm to understand the loss landscape of deep neural networks Mario Geiger S. Spigler Stéphane dÁscoli Levent Sagun Marco Baity-Jesi Giulio Biroli M. Wyart 24 141 0 25 Sep 2018
A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients Arnulf Jentzen Diyora Salimova Timo Welti AI4CE 16 116 0 19 Sep 2018
Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black-Scholes Partial Differential Equations Julius Berner Philipp Grohs Arnulf Jentzen 14 181 0 09 Sep 2018
A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations Philipp Grohs F. Hornung Arnulf Jentzen Philippe von Wurstemberger 16 167 0 07 Sep 2018
Wide Activation for Efficient and Accurate Image Super-Resolution Jiahui Yu Yuchen Fan Jianchao Yang N. Xu Zhaowen Wang Xinchao Wang Thomas Huang SupR 19 355 0 27 Aug 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 Learning for Energy Markets Michael Polson Vadim Sokolov AI4TS 9 26 0 16 Aug 2018
Genre-Agnostic Key Classification With Convolutional Neural Networks Filip Korzeniowski Gerhard Widmer 11 31 0 16 Aug 2018
Collapse of Deep and Narrow Neural Nets Lu Lu Yanhui Su George Karniadakis ODL 19 153 0 15 Aug 2018
Universal Approximation with Quadratic Deep Networks Fenglei Fan Jinjun Xiong Ge Wang PINN 36 78 0 31 Jul 2018
Are Efficient Deep Representations Learnable? Maxwell Nye Andrew M. Saxe 14 24 0 17 Jul 2018
Semi-supervised Feature Learning For Improving Writer Identification Shiming Chen Yisong Wang Chin-Teng Lin Weiping Ding Zehong Cao 11 53 0 15 Jul 2018
Training Neural Networks Using Features Replay Zhouyuan Huo Bin Gu Heng-Chiao Huang 22 69 0 12 Jul 2018
ResNet with one-neuron hidden layers is a Universal Approximator Hongzhou Lin Stefanie Jegelka 41 227 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 1,394 0 22 Jun 2018
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond Xingguo Li Junwei Lu Zhaoran Wang Jarvis Haupt T. Zhao 27 78 0 13 Jun 2018
The Nonlinearity Coefficient - Predicting Generalization in Deep Neural Networks George Philipp J. Carbonell 23 14 0 01 Jun 2018
Interpreting Deep Learning: The Machine Learning Rorschach Test? Adam S. Charles AAML HAI AI4CE 24 9 0 01 Jun 2018
Representational Power of ReLU Networks and Polynomial Kernels: Beyond Worst-Case Analysis Frederic Koehler Andrej Risteski 13 12 0 29 May 2018
Universality of Deep Convolutional Neural Networks Ding-Xuan Zhou HAI PINN 10 509 0 28 May 2018
Understanding Generalization and Optimization Performance of Deep CNNs Pan Zhou Jiashi Feng MLT 17 48 0 28 May 2018
Learning Restricted Boltzmann Machines via Influence Maximization Guy Bresler Frederic Koehler Ankur Moitra Elchanan Mossel AI4CE 20 29 0 25 May 2018
Adversarially Robust Training through Structured Gradient Regularization Kevin Roth Aurelien Lucchi Sebastian Nowozin Thomas Hofmann 27 23 0 22 May 2018
Reducing Parameter Space for Neural Network Training Tong Qin Ling Zhou D. Xiu 14 6 0 22 May 2018
Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks Yingzhou Li Xiuyuan Cheng Jianfeng Lu 21 23 0 18 May 2018
Tropical Geometry of Deep Neural Networks Liwen Zhang Gregory Naitzat Lek-Heng Lim 37 137 0 18 May 2018
Doing the impossible: Why neural networks can be trained at all Nathan Oken Hodas P. Stinis AI4CE 23 19 0 13 May 2018
Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds Santosh Vempala John Wilmes MLT 8 50 0 07 May 2018
Decoupled Parallel Backpropagation with Convergence Guarantee Zhouyuan Huo Bin Gu Qian Yang Heng-Chiao Huang 23 97 0 27 Apr 2018
A comparison of deep networks with ReLU activation function and linear spline-type methods Konstantin Eckle Johannes Schmidt-Hieber 17 322 0 06 Apr 2018