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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
Robust and Information-theoretically Safe Bias Classifier against Adversarial Attacks Lijia Yu Xiao-Shan Gao AAML 114 5 0 08 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang Huan Zhang Yuanyuan Shi J Zico Kolter Anima Anandkumar 105 78 0 02 Nov 2021
Improving Local Effectiveness for Global robust training Jingyue Lu M. P. Kumar AAML 49 0 0 26 Oct 2021
A Dynamical System Perspective for Lipschitz Neural Networks Laurent Meunier Blaise Delattre Alexandre Araujo A. Allauzen 128 56 0 25 Oct 2021
A Layer-wise Adversarial-aware Quantization Optimization for Improving Robustness Chang Song Riya Ranjan H. Li MQ 67 4 0 23 Oct 2021
Boosting the Certified Robustness of L-infinity Distance Nets Bohang Zhang Du Jiang Di He Liwei Wang OOD 93 30 0 13 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 139 102 0 07 Oct 2021
Trustworthy AI: From Principles to Practices Yue Liu Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 213 383 0 04 Oct 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 71 4 0 16 Sep 2021
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques Shiyu Tang Ruihao Gong Yan Wang Aishan Liu Jiakai Wang ... Xianglong Liu Basel Alomair Alan Yuille Philip Torr Dacheng Tao VLM AAML 99 108 0 11 Sep 2021
Impact of Attention on Adversarial Robustness of Image Classification Models Prachi Agrawal Narinder Singh Punn S. K. Sonbhadra Sonali Agarwal AAML 45 6 0 02 Sep 2021
Benchmarking the Robustness of Instance Segmentation Models Said Fahri Altindis Yusuf Dalva Hamza Pehlivan Aysegül Dündar VLM OOD 225 12 0 02 Sep 2021
CDCGen: Cross-Domain Conditional Generation via Normalizing Flows and Adversarial Training Hari Prasanna Das Ryan Tran Japjot Singh Yu-Wen Lin C. Spanos OOD 66 11 0 25 Aug 2021
Bridged Adversarial Training Hoki Kim Woojin Lee Sungyoon Lee Jaewook Lee AAML GAN 67 9 0 25 Aug 2021
Neural Architecture Dilation for Adversarial Robustness Yanxi Li Zhaohui Yang Yunhe Wang Chang Xu AAML 69 24 0 16 Aug 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks El Mehdi Achour Franccois Malgouyres Franck Mamalet 62 21 0 12 Aug 2021
Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100 Sahil Singla Surbhi Singla Soheil Feizi AAML 90 58 0 05 Aug 2021
Certified Defense via Latent Space Randomized Smoothing with Orthogonal Encoders Huimin Zeng Jiahao Su Furong Huang AAML 49 4 0 01 Aug 2021
NeuralDP Differentially private neural networks by design Moritz Knolle Dmitrii Usynin Alexander Ziller Marcus R. Makowski Daniel Rueckert Georgios Kaissis 37 1 0 30 Jul 2021
Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering Nairouz Mrabah Mohamed Bouguessa M. Touati Riadh Ksantini 99 65 0 19 Jul 2021
Geometry and Generalization: Eigenvalues as predictors of where a network will fail to generalize S. Agarwala Ben Dees A. Gearhart Corey Lowman 50 2 0 13 Jul 2021
A Robust Classification-autoencoder to Defend Outliers and Adversaries Lijia Yu Xiao-Shan Gao AAML 77 2 0 30 Jun 2021
Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting Zheng Fang Qingqing Long Guojie Song Kunqing Xie AI4TS 73 485 0 24 Jun 2021
Scaling-up Diverse Orthogonal Convolutional Networks with a Paraunitary Framework Jiahao Su Wonmin Byeon Furong Huang 36 9 0 16 Jun 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 51 12 0 14 Jun 2021
Adversarial Robustness via Fisher-Rao Regularization Marine Picot Francisco Messina Malik Boudiaf Fabrice Labeau Ismail Ben Ayed Pablo Piantanida AAML 79 25 0 12 Jun 2021
CARTL: Cooperative Adversarially-Robust Transfer Learning Dian Chen Hongxin Hu Qian Wang Yinli Li Cong Wang Chao Shen Qi Li 48 14 0 12 Jun 2021
Attacking Adversarial Attacks as A Defense Boxi Wu Heng Pan Li Shen Jindong Gu Shuai Zhao Zhifeng Li Deng Cai Xiaofei He Wei Liu AAML 93 32 0 09 Jun 2021
A Deep Value-network Based Approach for Multi-Driver Order Dispatching Xiaocheng Tang Zhiwei Qin Fan Zhang Zhaodong Wang Zhe Xu Yintai Ma Hongtu Zhu Jieping Ye OffRL 70 183 0 08 Jun 2021
Adversarial Attack and Defense in Deep Ranking Mo Zhou Le Wang Zhenxing Niu Qilin Zhang N. Zheng G. Hua OOD 83 15 0 07 Jun 2021
Human-Adversarial Visual Question Answering Sasha Sheng Amanpreet Singh Vedanuj Goswami Jose Alberto Lopez Magana Wojciech Galuba Devi Parikh Douwe Kiela OOD EgoV AAML 58 63 0 04 Jun 2021
Exploring Memorization in Adversarial Training Yinpeng Dong Ke Xu Xiao Yang Tianyu Pang Zhijie Deng Hang Su Jun Zhu TDI 58 74 0 03 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 87 9 0 31 May 2021
Quantifying and Localizing Usable Information Leakage from Neural Network Gradients Fan Mo Anastasia Borovykh Mohammad Malekzadeh Soteris Demetriou Deniz Gündüz Hamed Haddadi FedML 31 3 0 28 May 2021
A Universal Law of Robustness via Isoperimetry Sébastien Bubeck Mark Sellke 55 218 0 26 May 2021
Skew Orthogonal Convolutions Sahil Singla Soheil Feizi 79 69 0 24 May 2021
Sparta: Spatially Attentive and Adversarially Robust Activation Qing Guo Felix Juefei Xu Changqing Zhou Wei Feng Yang Liu Song Wang AAML 70 4 0 18 May 2021
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective Florin Gogianu Tudor Berariu Mihaela Rosca Claudia Clopath L. Buşoniu Razvan Pascanu 86 56 0 11 May 2021
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety Sebastian Houben Stephanie Abrecht Maram Akila Andreas Bär Felix Brockherde ... Serin Varghese Michael Weber Sebastian J. Wirkert Tim Wirtz Matthias Woehrle AAML 126 58 0 29 Apr 2021
Orthogonalizing Convolutional Layers with the Cayley Transform Asher Trockman J. Zico Kolter 95 115 0 14 Apr 2021
Sparse Coding Frontend for Robust Neural Networks Can Bakiskan Metehan Cekic Ahmet Dundar Sezer Upamanyu Madhow AAML 21 0 0 12 Apr 2021
Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networks Louis Bethune Thibaut Boissin M. Serrurier Franck Mamalet Corentin Friedrich Alberto González Sanz 111 23 0 11 Apr 2021
Combating Adversaries with Anti-Adversaries Motasem Alfarra Juan C. Pérez Ali K. Thabet Adel Bibi Philip Torr Guohao Li AAML 103 27 0 26 Mar 2021
JFB: Jacobian-Free Backpropagation for Implicit Networks Samy Wu Fung Howard Heaton Qiuwei Li Daniel McKenzie Stanley Osher W. Yin FedML 138 85 0 23 Mar 2021
Constant Random Perturbations Provide Adversarial Robustness with Minimal Effect on Accuracy Bronya R. Chernyak Bhiksha Raj Tamir Hazan Joseph Keshet AAML 65 1 0 15 Mar 2021
Reframing Neural Networks: Deep Structure in Overcomplete Representations Calvin Murdock George Cazenavette Simon Lucey BDL 64 5 0 10 Mar 2021
Insta-RS: Instance-wise Randomized Smoothing for Improved Robustness and Accuracy Chong Chen Kezhi Kong Peihong Yu J. Luque Tom Goldstein Furong Huang AAML 64 8 0 07 Mar 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack Mengting Xu Tao Zhang Zhongnian Li Mingxia Liu Daoqiang Zhang AAML OOD MedIm 105 45 0 05 Mar 2021
Smoothness Analysis of Adversarial Training Sekitoshi Kanai Masanori Yamada Hiroshi Takahashi Yuki Yamanaka Yasutoshi Ida AAML 95 6 0 02 Mar 2021
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training Sheng Liu Xiao Li Yuexiang Zhai Chong You Zhihui Zhu C. Fernandez‐Granda Qing Qu 52 26 0 01 Mar 2021