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Parseval Networks: Improving Robustness to Adversarial Examples

28 April 2017

Papers citing "Parseval Networks: Improving Robustness to Adversarial Examples"

50 / 489 papers shown

Title
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 108 36 0 26 Dec 2019
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing Jinyuan Jia Xiaoyu Cao Binghui Wang Neil Zhenqiang Gong AAML 67 96 0 20 Dec 2019
Asynchronous Federated Learning with Differential Privacy for Edge Intelligence Yanan Li Shusen Yang Xuebin Ren Cong Zhao FedML 78 35 0 17 Dec 2019
What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network Performance Mahmoud Afifi M. Brown AAML 86 115 0 15 Dec 2019
Two Way Adversarial Unsupervised Word Translation Blaine Cole GAN 21 0 0 12 Dec 2019
Gabor Layers Enhance Network Robustness Juan C. Pérez Motasem Alfarra Guillaume Jeanneret Adel Bibi Ali K. Thabet Guohao Li Pablo Arbelaez AAML 67 18 0 11 Dec 2019
An Empirical Study on the Relation between Network Interpretability and Adversarial Robustness Adam Noack Isaac Ahern Dejing Dou Boyang Albert Li OOD AAML 158 10 0 07 Dec 2019
Adversarial Risk via Optimal Transport and Optimal Couplings Muni Sreenivas Pydi Varun Jog 92 60 0 05 Dec 2019
Continuous Graph Neural Networks Louis-Pascal Xhonneux Meng Qu Jian Tang GNN 117 156 0 02 Dec 2019
Attributional Robustness Training using Input-Gradient Spatial Alignment M. Singh Nupur Kumari Puneet Mangla Abhishek Sinha V. Balasubramanian Balaji Krishnamurthy OOD 109 10 0 29 Nov 2019
Fantastic Four: Differentiable Bounds on Singular Values of Convolution Layers Sahil Singla Soheil Feizi AAML 70 8 0 22 Nov 2019
Analysis of Deep Networks for Monocular Depth Estimation Through Adversarial Attacks with Proposal of a Defense Method Junjie Hu Takayuki Okatani AAML MDE 67 17 0 20 Nov 2019
On Model Robustness Against Adversarial Examples Shufei Zhang Kaizhu Huang Zenglin Xu AAML 44 0 0 15 Nov 2019
Adversarial Margin Maximization Networks Ziang Yan Yiwen Guo Changshui Zhang AAML 40 12 0 14 Nov 2019
There is Limited Correlation between Coverage and Robustness for Deep Neural Networks Yizhen Dong Peixin Zhang Jingyi Wang Shuang Liu Jun Sun Jianye Hao Xinyu Wang Li Wang J. Dong Ting Dai OOD AAML 78 32 0 14 Nov 2019
Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov Theory Arash Rahnama A. Nguyen Edward Raff AAML 51 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 143 116 0 03 Nov 2019
Adversarial Music: Real World Audio Adversary Against Wake-word Detection System Juncheng Billy Li Shuhui Qu Xinjian Li Joseph Szurley J. Zico Kolter Florian Metze AAML 73 67 0 31 Oct 2019
Structure Matters: Towards Generating Transferable Adversarial Images Dan Peng Zizhan Zheng Linhao Luo Xiaofeng Zhang AAML 70 2 0 22 Oct 2019
Enforcing Linearity in DNN succours Robustness and Adversarial Image Generation A. Sarkar Nikhil Kumar Gupta Raghu Sesha Iyengar AAML 48 11 0 17 Oct 2019
Notes on Margin Training and Margin p-Values for Deep Neural Network Classifiers G. Kesidis David J. Miller Zhen Xiang 28 0 0 15 Oct 2019
Testing and verification of neural-network-based safety-critical control software: A systematic literature review Jin Zhang Jingyue Li 93 48 0 05 Oct 2019
Training Robust Deep Neural Networks via Adversarial Noise Propagation Aishan Liu Xianglong Liu Chongzhi Zhang Hang Yu Qiang Liu Dacheng Tao AAML 86 116 0 19 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 51 1 0 19 Sep 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 90 680 0 17 Sep 2019
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors Gilad Cohen Guillermo Sapiro Raja Giryes TDI 73 128 0 15 Sep 2019
Wasserstein Diffusion Tikhonov Regularization A. Lin Yonatan Dukler Wuchen Li Guido Montúfar 45 2 0 15 Sep 2019
Feedback Learning for Improving the Robustness of Neural Networks Chang Song Zuoguan Wang H. Li AAML 65 7 0 12 Sep 2019
Structural Robustness for Deep Learning Architectures Carlos Lassance Vincent Gripon Jian Tang Antonio Ortega OOD 75 2 0 11 Sep 2019
Towards Learning a Self-inverse Network for Bidirectional Image-to-image Translation ZENGMING SHEN Yifan Chen S. Kevin Zhou Bogdan Georgescu Xuqi Liu Thomas S. Huang SSL MedIm 51 1 0 09 Sep 2019
Metric Learning for Adversarial Robustness Chengzhi Mao Ziyuan Zhong Junfeng Yang Carl Vondrick Baishakhi Ray OOD 101 188 0 03 Sep 2019
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Zhijun Mai Guosheng Hu Dexiong Chen Fumin Shen Heng Tao Shen 60 43 0 27 Aug 2019
DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation Seungju Cho Tae Joon Jun Byungsoo Oh Daeyoung Kim 113 31 0 14 Aug 2019
Benchmarking the Robustness of Semantic Segmentation Models Christoph Kamann Carsten Rother VLM UQCV 86 164 0 14 Aug 2019
Likelihood Contribution based Multi-scale Architecture for Generative Flows Hari Prasanna Das Pieter Abbeel C. Spanos DRL AI4CE 61 5 0 05 Aug 2019
Understanding Adversarial Robustness: The Trade-off between Minimum and Average Margin Kaiwen Wu Yaoliang Yu AAML 47 8 0 26 Jul 2019
A Frobenius norm regularization method for convolutional kernels to avoid unstable gradient problem Pei-Chang Guo 52 5 0 25 Jul 2019
Recovery Guarantees for Compressible Signals with Adversarial Noise J. Dhaliwal Kyle Hambrook AAML 57 2 0 15 Jul 2019
Unsupervised Adversarial Graph Alignment with Graph Embedding Chaoqi Chen Weiping Xie Tingyang Xu Yu Rong Wenbing Huang Xinghao Ding Yue Huang Junzhou Huang 42 15 0 01 Jul 2019
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks Ahmed T. Elthakeb Prannoy Pilligundla Alex Cloninger H. Esmaeilzadeh MQ 55 8 0 14 Jun 2019
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks Kaifeng Lyu Jian Li 128 336 0 13 Jun 2019
On regularization for a convolutional kernel in neural networks Pei-Chang Guo Qiang Ye 47 1 0 12 Jun 2019
Stable Rank Normalization for Improved Generalization in Neural Networks and GANs Amartya Sanyal Philip Torr P. Dokania 110 49 0 11 Jun 2019
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness Walt Woods Jack H Chen C. Teuscher AAML 75 46 0 07 Jun 2019
FSPool: Learning Set Representations with Featurewise Sort Pooling Yan Zhang Jonathon S. Hare Adam Prugel-Bennett 148 80 0 06 Jun 2019
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 66 15 0 05 Jun 2019
Adversarial Training is a Form of Data-dependent Operator Norm Regularization Kevin Roth Yannic Kilcher Thomas Hofmann 58 13 0 04 Jun 2019
Body Shape Privacy in Images: Understanding Privacy and Preventing Automatic Shape Extraction Hosnieh Sattar Katharina Krombholz Gerard Pons-Moll Mario Fritz 3DH 69 3 0 27 May 2019
Inverse Reinforcement Learning in Contextual MDPs Stav Belogolovsky Philip Korsunsky Shie Mannor Chen Tessler Tom Zahavy OffRL BDL 115 18 0 23 May 2019
What Do Adversarially Robust Models Look At? Takahiro Itazuri Yoshihiro Fukuhara Hirokatsu Kataoka Shigeo Morishima 32 5 0 19 May 2019