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引用“”的文章Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks.

标题/作者	年份
Threat of adversarial attacks on deep learning in computer vision: A survey N Akhtar, A Mian Ieee Access 6, 14410-14430	2018
Adversarial examples: Attacks and defenses for deep learning X Yuan, P He, Q Zhu, X Li IEEE transactions on neural networks and learning systems 30 (9), 2805-2824	2019
Provable defenses against adversarial examples via the convex outer adversarial polytope E Wong, Z Kolter International Conference on Machine Learning, 5286-5295	2018
Deeptest: Automated testing of deep-neural-network-driven autonomous cars Y Tian, K Pei, S Jana, B Ray Proceedings of the 40th international conference on software engineering …	2018
Deepxplore: Automated whitebox testing of deep learning systems K Pei, Y Cao, J Yang, S Jana proceedings of the 26th Symposium on Operating Systems Principles, 1-18	2017
Certified adversarial robustness via randomized smoothing J Cohen, E Rosenfeld, Z Kolter International Conference on Machine Learning, 1310-1320	2019
Decision-based adversarial attacks: Reliable attacks against black-box machine learning models W Brendel, J Rauber, M Bethge arXiv preprint arXiv:1712.04248	2017
Safety verification of deep neural networks X Huang, M Kwiatkowska, S Wang, M Wu International conference on computer aided verification, 3-29	2017
Certified defenses against adversarial examples A Raghunathan, J Steinhardt, P Liang arXiv preprint arXiv:1801.09344	2018
Certifying some distributional robustness with principled adversarial training A Sinha, H Namkoong, R Volpi, J Duchi arXiv preprint arXiv:1710.10571	2017
Ai2: Safety and robustness certification of neural networks with abstract interpretation T Gehr, M Mirman, D Drachsler-Cohen, P Tsankov, S Chaudhuri, ... 2018 IEEE symposium on security and privacy (SP), 3-18	2018
Certified robustness to adversarial examples with differential privacy M Lecuyer, V Atlidakis, R Geambasu, D Hsu, S Jana 2019 IEEE Symposium on Security and Privacy (SP), 656-672	2019
A survey of deep learning techniques for autonomous driving S Grigorescu, B Trasnea, T Cocias, G Macesanu Journal of Field Robotics 37 (3), 362-386	2020
Planning and decision-making for autonomous vehicles W Schwarting, J Alonso-Mora, D Rus Annual Review of Control, Robotics, and Autonomous Systems 1 (1), 187-210	2018
Evaluating robustness of neural networks with mixed integer programming V Tjeng, K Xiao, R Tedrake arXiv preprint arXiv:1711.07356	2017
Formal verification of piece-wise linear feed-forward neural networks R Ehlers International Symposium on Automated Technology for Verification and …	2017
Towards fast computation of certified robustness for relu networks L Weng, H Zhang, H Chen, Z Song, CJ Hsieh, L Daniel, D Boning, ... International Conference on Machine Learning, 5276-5285	2018
Speech emotion recognition using deep 1D & 2D CNN LSTM networks J Zhao, X Mao, L Chen Biomedical signal processing and control 47, 312-323	2019
Deepgauge: Multi-granularity testing criteria for deep learning systems L Ma, F Juefei-Xu, F Zhang, J Sun, M Xue, B Li, C Chen, T Su, L Li, Y Liu, ... Proceedings of the 33rd ACM/IEEE International Conference on Automated …	2018
Efficient neural network robustness certification with general activation functions H Zhang, TW Weng, PY Chen, CJ Hsieh, L Daniel Advances in neural information processing systems 31	2018

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