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Safety Verification of Deep Neural Networks

21 October 2016

Min Wu

Papers citing "Safety Verification of Deep Neural Networks"

50 / 448 papers shown

Title
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features Nicolas Berthier Amany Alshareef James Sharp S. Schewe Xiaowei Huang 74 10 0 05 Mar 2021
PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations Mark Niklas Muller Gleb Makarchuk Gagandeep Singh Markus Püschel Martin Vechev 95 92 0 05 Mar 2021
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers Colin Paterson Haoze Wu John M. Grese R. Calinescu C. Păsăreanu Clark W. Barrett AAML 77 23 0 02 Mar 2021
NEUROSPF: A tool for the Symbolic Analysis of Neural Networks Muhammad Usman Yannic Noller C. Păsăreanu Youcheng Sun D. Gopinath 67 8 0 27 Feb 2021
A PAC-Bayes Analysis of Adversarial Robustness Paul Viallard Guillaume Vidot Amaury Habrard Emilie Morvant AAML 75 15 0 19 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs Soheil Feizi AAML 102 47 0 15 Feb 2021
A Computability Perspective on (Verified) Machine Learning T. Crook J. Morgan A. Pauly M. Roggenbach FaML 23 3 0 12 Feb 2021
Benford's law: what does it say on adversarial images? João G. Zago Fabio L. Baldissera Eric A. Antonelo Rodrigo T. Saad AAML 24 3 0 09 Feb 2021
Efficient Certified Defenses Against Patch Attacks on Image Classifiers J. H. Metzen Maksym Yatsura AAML 61 41 0 08 Feb 2021
Neural Termination Analysis Mirco Giacobbe Daniel Kroening Julian Parsert 72 17 0 07 Feb 2021
Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS) Richard Hawkins Colin Paterson Chiara Picardi Yan Jia R. Calinescu Ibrahim Habli 88 84 0 02 Feb 2021
Challenges for Using Impact Regularizers to Avoid Negative Side Effects David Lindner Kyle Matoba Alexander Meulemans 25 3 0 29 Jan 2021
Towards Practical Robustness Analysis for DNNs based on PAC-Model Learning Renjue Li Pengfei Yang Cheng-Chao Huang Youcheng Sun Bai Xue Lijun Zhang AAML 154 18 0 25 Jan 2021
Adaptive Neighbourhoods for the Discovery of Adversarial Examples Jay Morgan A. Paiement A. Pauly Monika Seisenberger AAML 28 1 0 22 Jan 2021
Shielding Atari Games with Bounded Prescience Mirco Giacobbe Mohammadhosein Hasanbeig Daniel Kroening H. Wijk 68 23 0 20 Jan 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 186 177 0 13 Jan 2021
SyReNN: A Tool for Analyzing Deep Neural Networks Matthew Sotoudeh Aditya V. Thakur AAML GNN 63 16 0 09 Jan 2021
The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks Arno Blaas Stephen J. Roberts BDL AAML 83 2 0 07 Jan 2021
Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers Michael Everett Golnaz Habibi Jonathan P. How 64 15 0 05 Jan 2021
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Mohamed Bennai Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 139 101 0 04 Jan 2021
Identification of Unexpected Decisions in Partially Observable Monte-Carlo Planning: a Rule-Based Approach Giulio Mazzi A. Castellini Alessandro Farinelli 42 9 0 23 Dec 2020
Incremental Verification of Fixed-Point Implementations of Neural Networks Luiz Sena E. Alves I. Bessa Eddie Batista de Lima Filho Lucas C. Cordeiro 31 0 0 21 Dec 2020
ROBY: Evaluating the Robustness of a Deep Model by its Decision Boundaries Jinyin Chen Zhen Wang Haibin Zheng Jun Xiao Zhaoyan Ming AAML 82 5 0 18 Dec 2020
Scalable Verification of Quantized Neural Networks (Technical Report) T. Henzinger Mathias Lechner Dorde Zikelic MQ 54 34 0 15 Dec 2020
Data-Dependent Randomized Smoothing Motasem Alfarra Adel Bibi Philip Torr Guohao Li UQCV 108 35 0 08 Dec 2020
Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection Byunggill Joe Jihun Hamm Sung Ju Hwang Sooel Son I. Shin AAML OOD 57 0 0 07 Dec 2020
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers Kaidi Xu Huan Zhang Shiqi Wang Yihan Wang Suman Jana Xue Lin Cho-Jui Hsieh 118 188 0 27 Nov 2020
Adversarial Examples for $k$ -Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams Chawin Sitawarin Evgenios M. Kornaropoulos Basel Alomair David Wagner AAML 35 8 0 19 Nov 2020
An SMT-Based Approach for Verifying Binarized Neural Networks Guy Amir Haoze Wu Clark W. Barrett Guy Katz 65 59 0 05 Nov 2020
All-Weather Object Recognition Using Radar and Infrared Sensing Marcel Sheeny 40 1 0 30 Oct 2020
Safety Verification of Model Based Reinforcement Learning Controllers Akshita Gupta Inseok Hwang 79 4 0 21 Oct 2020
Tight Second-Order Certificates for Randomized Smoothing Alexander Levine Aounon Kumar Thomas A. Goldstein Soheil Feizi AAML 55 16 0 20 Oct 2020
Formal Verification of Robustness and Resilience of Learning-Enabled State Estimation Systems Wei Huang Yifan Zhou Alec Banks Youcheng Sun Jie Meng James Sharp Xiaowei Huang 46 3 0 16 Oct 2020
Improving Neural Network Verification through Spurious Region Guided Refinement Pengfei Yang Renjue Li Jianlin Li Cheng-Chao Huang Jingyi Wang Jun Sun Bai Xue Lijun Zhang AAML 61 39 0 15 Oct 2020
How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks Gao Jin Xinping Yi Liang Zhang Lijun Zhang S. Schewe Xiaowei Huang 80 42 0 12 Oct 2020
Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers Christoph Kamann Burkhard Güssefeld Robin Hutmacher J. H. Metzen Carsten Rother 60 18 0 12 Oct 2020
Understanding Local Robustness of Deep Neural Networks under Natural Variations Ziyuan Zhong Yuchi Tian Baishakhi Ray AAML 61 1 0 09 Oct 2020
Global Optimization of Objective Functions Represented by ReLU Networks Christopher A. Strong Haoze Wu Aleksandar Zeljić Kyle D. Julian Guy Katz Clark W. Barrett Mykel J. Kochenderfer AAML 57 33 0 07 Oct 2020
Robustness Analysis of Neural Networks via Efficient Partitioning with Applications in Control Systems Michael Everett Golnaz Habibi Jonathan P. How AAML 30 3 0 01 Oct 2020
Assessing Robustness of Text Classification through Maximal Safe Radius Computation Emanuele La Malfa Min Wu Luca Laurenti Benjie Wang Anthony Hartshorn Marta Z. Kwiatkowska AAML 70 18 0 01 Oct 2020
NeuroDiff: Scalable Differential Verification of Neural Networks using Fine-Grained Approximation Brandon Paulsen Jingbo Wang Jiawei Wang Chao Wang 86 36 0 21 Sep 2020
Deep Learning & Software Engineering: State of Research and Future Directions P. Devanbu Matthew B. Dwyer Sebastian G. Elbaum M. Lowry Kevin Moran Denys Poshyvanyk Baishakhi Ray Rishabh Singh Xiangyu Zhang 62 22 0 17 Sep 2020
A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses Ambar Pal René Vidal AAML 96 27 0 14 Sep 2020
Towards the Quantification of Safety Risks in Deep Neural Networks Peipei Xu Wenjie Ruan Xiaowei Huang 39 7 0 13 Sep 2020
How Much Can We Really Trust You? Towards Simple, Interpretable Trust Quantification Metrics for Deep Neural Networks A. Wong Xiao Yu Wang Andrew Hryniowski 62 23 0 12 Sep 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Yue Liu AAML 123 131 0 09 Sep 2020
Linear Temporal Public Announcement Logic: a new perspective for reasoning about the knowledge of multi-classifiers Amirhoshang Hoseinpour Dehkordi Majid Alizadeh A. Movaghar 19 0 0 08 Sep 2020
Assessing Safety-Critical Systems from Operational Testing: A Study on Autonomous Vehicles Xingyu Zhao K. Salako L. Strigini Valentin Robu David Flynn 67 40 0 19 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 116 73 0 07 Aug 2020
Incorrect by Construction: Fine Tuning Neural Networks for Guaranteed Performance on Finite Sets of Examples I. Papusha Rosa Wu Joshua Brulé Yanni Kouskoulas D. Genin Aurora C. Schmidt 26 5 0 03 Aug 2020