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Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

50 / 4,017 papers shown

Title
Adversarial Purification with the Manifold Hypothesis Zhaoyuan Yang Zhiwei Xu Jing Zhang Leonid Sigal Peter Tu AAML 99 5 0 26 Oct 2022
Causal Information Bottleneck Boosts Adversarial Robustness of Deep Neural Network Hua Hua Jun Yan Xi Fang Weiquan Huang Huilin Yin Wancheng Ge AAML 68 1 0 25 Oct 2022
Tighter Abstract Queries in Neural Network Verification Elazar Cohen Y. Elboher Clark W. Barrett Guy Katz 118 7 0 23 Oct 2022
Adversarial Pretraining of Self-Supervised Deep Networks: Past, Present and Future Guo-Jun Qi M. Shah SSL 78 8 0 23 Oct 2022
Exploring The Landscape of Distributional Robustness for Question Answering Models Anas Awadalla Mitchell Wortsman Gabriel Ilharco Sewon Min Ian H. Magnusson Hannaneh Hajishirzi Ludwig Schmidt ELM OOD KELM 121 21 0 22 Oct 2022
Abstract Interpretation-Based Feature Importance for SVMs Abhinanda Pal Francesco Ranzato Caterina Urban Marco Zanella FAtt 69 0 0 22 Oct 2022
Hindering Adversarial Attacks with Implicit Neural Representations Andrei A. Rusu D. A. Calian Sven Gowal R. Hadsell AAML 174 4 0 22 Oct 2022
Precisely the Point: Adversarial Augmentations for Faithful and Informative Text Generation Wenhao Wu Wei Li Jiachen Liu Xinyan Xiao Sujian Li Yajuan Lyu 124 4 0 22 Oct 2022
Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifier Sumedha Singla Nihal Murali Forough Arabshahi Sofia Triantafyllou Kayhan Batmanghelich CML 124 5 0 21 Oct 2022
Window-Based Distribution Shift Detection for Deep Neural Networks Guy Bar-Shalom Yonatan Geifman Ran El-Yaniv 64 4 0 19 Oct 2022
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries Yuxin Wen Arpit Bansal Hamid Kazemi Eitan Borgnia Micah Goldblum Jonas Geiping Tom Goldstein MIACV 122 32 0 19 Oct 2022
Learning Transferable Adversarial Robust Representations via Multi-view Consistency Minseon Kim Hyeonjeong Ha Dong Bok Lee Sung Ju Hwang 69 0 0 19 Oct 2022
Effective Targeted Attacks for Adversarial Self-Supervised Learning Minseon Kim Hyeonjeong Ha Sooel Son Sung Ju Hwang AAML 84 3 0 19 Oct 2022
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey Huiyun Cao Wenlong Zou Yinkun Wang Ting Song Mengjun Liu AAML 103 6 0 19 Oct 2022
A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities Andrea Tocchetti Lorenzo Corti Agathe Balayn Mireia Yurrita Philip Lippmann Marco Brambilla Jie Yang 87 14 0 17 Oct 2022
Differential Evolution based Dual Adversarial Camouflage: Fooling Human Eyes and Object Detectors Jialiang Sun Tingsong Jiang Wen Yao Donghua Wang Xiaoqian Chen AAML 98 17 0 17 Oct 2022
Nowhere to Hide: A Lightweight Unsupervised Detector against Adversarial Examples Hui Liu Bo Zhao Kehuan Zhang Peng Liu AAML 69 4 0 16 Oct 2022
Object-Attentional Untargeted Adversarial Attack Chao Zhou Yuan-Gen Wang Guopu Zhu AAML 74 2 0 16 Oct 2022
Dynamics-aware Adversarial Attack of Adaptive Neural Networks An Tao Yueqi Duan Yingqi Wang Jiwen Lu Jie Zhou AAML 85 6 0 15 Oct 2022
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture Yi Mo Dongxian Wu Yifei Wang Yiwen Guo Yisen Wang ViT 101 58 0 14 Oct 2022
GA-SAM: Gradient-Strength based Adaptive Sharpness-Aware Minimization for Improved Generalization Zhiyuan Zhang Ruixuan Luo Qi Su Xueting Sun 112 13 0 13 Oct 2022
Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition Shuai Jia Bangjie Yin Taiping Yao Shouhong Ding Chunhua Shen Xiaokang Yang Chao Ma AAML CVBM 91 50 0 13 Oct 2022
Visual Prompting for Adversarial Robustness Aochuan Chen P. Lorenz Yuguang Yao Pin-Yu Chen Sijia Liu VLM VPVLM 123 36 0 12 Oct 2022
Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity Andrew C. Cullen Paul Montague Shijie Liu S. Erfani Benjamin I. P. Rubinstein AAML 79 15 0 12 Oct 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper Margret Keuper AAML 80 25 0 12 Oct 2022
Human Body Measurement Estimation with Adversarial Augmentation Nataniel Ruiz Míriam Bellver Timo Bolkart Ambuj Arora Ming-Chia Lin Javier Romero Raj Bala 3DH 106 5 0 11 Oct 2022
Adversarial Attack Against Image-Based Localization Neural Networks Meir Brand I. Naeh Daniel Teitelman AAML 75 0 0 11 Oct 2022
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis Julia Kempe AAML 102 20 0 11 Oct 2022
Stable and Efficient Adversarial Training through Local Linearization Zhuorong Li Daiwei Yu AAML 34 0 0 11 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 60 5 0 11 Oct 2022
Certified Training: Small Boxes are All You Need Mark Niklas Muller Franziska Eckert Marc Fischer Martin Vechev AAML 99 48 0 10 Oct 2022
DeepPerform: An Efficient Approach for Performance Testing of Resource-Constrained Neural Networks Simin Chen Mirazul Haque Cong Liu Wei Yang 110 22 0 10 Oct 2022
Pruning Adversarially Robust Neural Networks without Adversarial Examples T. Jian Zifeng Wang Yanzhi Wang Jennifer Dy Stratis Ioannidis AAML VLM 71 13 0 09 Oct 2022
Towards Understanding and Boosting Adversarial Transferability from a Distribution Perspective Yao Zhu YueFeng Chen Xiaodan Li Kejiang Chen Yuan He Xiang Tian Bo Zheng Yao-wu Chen Qingming Huang AAML 64 59 0 09 Oct 2022
Symmetry Defense Against CNN Adversarial Perturbation Attacks Blerta Lindqvist AAML 94 2 0 08 Oct 2022
FedDef: Defense Against Gradient Leakage in Federated Learning-based Network Intrusion Detection Systems Jiahui Chen Yi Zhao Qi Li Xuewei Feng Ke Xu AAML FedML 112 15 0 08 Oct 2022
LLMEffiChecker: Understanding and Testing Efficiency Degradation of Large Language Models Simin Chen Cong Liu Mirazul Haque Wei Yang 92 24 0 07 Oct 2022
A2: Efficient Automated Attacker for Boosting Adversarial Training Zhuoer Xu Guanghui Zhu Changhua Meng Shiwen Cui ZhenZhe Ying Weiqiang Wang GU Ming Yihua Huang AAML 101 14 0 07 Oct 2022
Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems Chawin Sitawarin Florian Tramèr Nicholas Carlini AAML 126 8 0 07 Oct 2022
Bad Citrus: Reducing Adversarial Costs with Model Distances Giorgio Severi Will Pearce Alina Oprea AAML 74 1 0 06 Oct 2022
Towards Out-of-Distribution Adversarial Robustness Adam Ibrahim Charles Guille-Escuret Ioannis Mitliagkas Irina Rish David M. Krueger P. Bashivan OOD 64 6 0 06 Oct 2022
Dynamic Stochastic Ensemble with Adversarial Robust Lottery Ticket Subnetworks Qi Peng Wen-ling Liu Ruoxi Qin Libin Hou Bin Yan Linyuan Wang AAML 79 3 0 06 Oct 2022
Active Image Indexing Pierre Fernandez Matthijs Douze Hervé Jégou Teddy Furon VLM 67 10 0 05 Oct 2022
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 131 11 0 05 Oct 2022
Natural Color Fool: Towards Boosting Black-box Unrestricted Attacks Shengming Yuan Qilong Zhang Lianli Gao Yaya Cheng Jingkuan Song AAML 108 47 0 05 Oct 2022
Robustness Certification of Visual Perception Models via Camera Motion Smoothing Hanjiang Hu Zuxin Liu Linyi Li Jiacheng Zhu Ding Zhao AAML 66 6 0 04 Oct 2022
NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learning Buyun Liang Tim Mitchell Ju Sun OOD 118 7 0 03 Oct 2022
Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao Yanbo Fan Ruoyu Sun Jue Wang Zhimin Luo AAML 85 31 0 03 Oct 2022
Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop Weixia Zhang Dingquan Li Xiongkuo Min Guangtao Zhai Guodong Guo Xiaokang Yang Kede Ma OOD 81 35 0 03 Oct 2022
Robust Empirical Risk Minimization with Tolerance Robi Bhattacharjee Max Hopkins Akash Kumar Hantao Yu Kamalika Chaudhuri OOD 89 8 0 02 Oct 2022