Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

30 / 1,630 papers shown

Title
DeepFense: Online Accelerated Defense Against Adversarial Deep Learning B. Rouhani Mohammad Samragh Mojan Javaheripi T. Javidi F. Koushanfar AAML 12 15 0 08 Sep 2017
A Formal Framework to Characterize Interpretability of Procedures Amit Dhurandhar Vijay Iyengar Ronny Luss Karthikeyan Shanmugam 15 19 0 12 Jul 2017
Efficient Data Representation by Selecting Prototypes with Importance Weights Karthik S. Gurumoorthy Amit Dhurandhar Guillermo Cecchi Charu Aggarwal 26 22 0 05 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks A. Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 86 11,872 0 19 Jun 2017
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong Warren He James Wei Xinyun Chen Nicholas Carlini D. Song AAML 43 242 0 15 Jun 2017
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples Yizhen Wang S. Jha Kamalika Chaudhuri AAML 16 154 0 13 Jun 2017
Towards Robust Detection of Adversarial Examples Tianyu Pang Chao Du Yinpeng Dong Jun Zhu AAML 39 18 0 02 Jun 2017
MagNet: a Two-Pronged Defense against Adversarial Examples Dongyu Meng Hao Chen AAML 13 1,198 0 25 May 2017
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction Bin Liang Hongcheng Li Miaoqiang Su Xirong Li Wenchang Shi Xiaofeng Wang AAML 14 215 0 23 May 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 61 1,842 0 20 May 2017
MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial Attacks with Moving Target Defense Sailik Sengupta Tathagata Chakraborti S. Kambhampati AAML 26 63 0 19 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 70 2,701 0 19 May 2017
DeepXplore: Automated Whitebox Testing of Deep Learning Systems Kexin Pei Yinzhi Cao Junfeng Yang Suman Jana AAML 48 1,353 0 18 May 2017
Extending Defensive Distillation Nicolas Papernot Patrick McDaniel AAML 32 118 0 15 May 2017
DeepCorrect: Correcting DNN models against Image Distortions Tejas S. Borkar Lina Karam 27 93 0 05 May 2017
Universal Adversarial Perturbations Against Semantic Image Segmentation J. H. Metzen Mummadi Chaithanya Kumar Thomas Brox Volker Fischer AAML 30 287 0 19 Apr 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 25 1,233 0 04 Apr 2017
Blocking Transferability of Adversarial Examples in Black-Box Learning Systems Hossein Hosseini Yize Chen Sreeram Kannan Baosen Zhang Radha Poovendran AAML 30 106 0 13 Mar 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences Yingzhen Li Y. Gal UQCV BDL 49 196 0 08 Mar 2017
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents Yen-Chen Lin Zhang-Wei Hong Yuan-Hong Liao Meng-Li Shih Ming Liu Min Sun AAML 17 411 0 08 Mar 2017
Compositional Falsification of Cyber-Physical Systems with Machine Learning Components T. Dreossi Alexandre Donzé S. Seshia AAML 32 230 0 02 Mar 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 36 886 0 01 Mar 2017
On the (Statistical) Detection of Adversarial Examples Kathrin Grosse Praveen Manoharan Nicolas Papernot Michael Backes Patrick McDaniel AAML 39 709 0 21 Feb 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 104 1,503 0 25 Jan 2017
Vulnerability of Deep Reinforcement Learning to Policy Induction Attacks Vahid Behzadan Arslan Munir AAML SILM 21 274 0 16 Jan 2017
Learning Adversary-Resistant Deep Neural Networks Qinglong Wang Wenbo Guo Kaixuan Zhang Alexander Ororbia Masashi Sugiyama Xue Liu C. Lee Giles AAML 23 43 0 05 Dec 2016
Delving into Transferable Adversarial Examples and Black-box Attacks Yanpei Liu Xinyun Chen Chang-rui Liu D. Song AAML 25 1,722 0 08 Nov 2016
Towards Lifelong Self-Supervision: A Deep Learning Direction for Robotics J. M. Wong 27 11 0 01 Nov 2016
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 933 0 21 Oct 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 326 5,847 0 08 Jul 2016