The Singular Values of Convolutional Layers

26 May 2018

Papers citing "The Singular Values of Convolutional Layers"

28 / 128 papers shown

Title
The intriguing role of module criticality in the generalization of deep networks Niladri S. Chatterji Behnam Neyshabur Hanie Sedghi 28 51 0 02 Dec 2019
Orthogonal Convolutional Neural Networks Jiayun Wang Yubei Chen Rudrasis Chakraborty Stella X. Yu 27 186 0 27 Nov 2019
Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov Theory Arash Rahnama A. Nguyen Edward Raff AAML 21 20 0 12 Nov 2019
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks Qiyang Li Saminul Haque Cem Anil James Lucas Roger C. Grosse Joern-Henrik Jacobsen 25 114 0 03 Nov 2019
Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory Micah Goldblum Jonas Geiping Avi Schwarzschild Michael Moeller Tom Goldstein 21 32 0 01 Oct 2019
Infusing Learned Priors into Model-Based Multispectral Imaging Jiaming Liu Yu Sun Ulugbek S. Kamilov 17 0 0 20 Sep 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks Sekitoshi Kanai Yasutoshi Ida Yasuhiro Fujiwara Masanori Yamada S. Adachi AAML 23 1 0 19 Sep 2019
Refining the Structure of Neural Networks Using Matrix Conditioning Roozbeh Yousefzadeh D. O’Leary 21 4 0 06 Aug 2019
A Frobenius norm regularization method for convolutional kernels to avoid unstable gradient problem Pei-Chang Guo 34 5 0 25 Jul 2019
On regularization for a convolutional kernel in neural networks Pei-Chang Guo Qiang Ye 28 1 0 12 Jun 2019
Generalization bounds for deep convolutional neural networks Philip M. Long Hanie Sedghi MLT 42 90 0 29 May 2019
Norm-based generalisation bounds for multi-class convolutional neural networks Antoine Ledent Waleed Mustafa Yunwen Lei Marius Kloft 18 5 0 29 May 2019
Orthogonal Deep Neural Networks Kui Jia Shuai Li Yuxin Wen Tongliang Liu Dacheng Tao 39 132 0 15 May 2019
Block Coordinate Regularization by Denoising Yu Sun Jiaming Liu Ulugbek S. Kamilov 32 82 0 13 May 2019
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent Karthik A. Sankararaman Soham De Zheng Xu Yifan Jiang Tom Goldstein ODL 27 103 0 15 Apr 2019
Deep Learning for Inverse Problems: Bounds and Regularizers Jaweria Amjad Zhaoyang Lyu M. Rodrigues 13 4 0 31 Jan 2019
Understanding and Training Deep Diagonal Circulant Neural Networks Alexandre Araujo Benjamin Négrevergne Y. Chevaleyre Jamal Atif 27 4 0 29 Jan 2019
Improving MMD-GAN Training with Repulsive Loss Function Wei Wang Yuan Sun Saman K. Halgamuge GAN 17 79 0 24 Dec 2018
Singular Values for ReLU Layers Sören Dittmer E. King Peter Maass 16 40 0 06 Dec 2018
Effects of Loss Functions And Target Representations on Adversarial Robustness Sean Saito S. Roy AAML 16 7 0 01 Dec 2018
Generalizable Adversarial Training via Spectral Normalization Farzan Farnia Jesse M. Zhang David Tse OOD AAML 45 138 0 19 Nov 2018
Sorting out Lipschitz function approximation Cem Anil James Lucas Roger C. Grosse 30 318 0 13 Nov 2018
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 37 618 0 02 Nov 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 16 15 0 30 Sep 2018
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions Yusuke Tsuzuku Issei Sato AAML 24 62 0 11 Sep 2018
A Peek Into the Hidden Layers of a Convolutional Neural Network Through a Factorization Lens Uday Singh Saini Evangelos E. Papalexakis FAtt 6 2 0 06 Jun 2018
Norm-Preservation: Why Residual Networks Can Become Extremely Deep? Alireza Zaeemzadeh Nazanin Rahnavard M. Shah 18 69 0 18 May 2018
Regularisation of Neural Networks by Enforcing Lipschitz Continuity Henry Gouk E. Frank Bernhard Pfahringer M. Cree 21 468 0 12 Apr 2018