Safety verification of deep neural networks X Huang, M Kwiatkowska, S Wang, M Wu Computer Aided Verification: 29th International Conference, CAV 2017 …, 2017 | 1157 | 2017 |
A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability X Huang, D Kroening, W Ruan, J Sharp, Y Sun, E Thamo, M Wu, X Yi Computer Science Review 37, 100270, 2020 | 557 | 2020 |
Concolic testing for deep neural networks Y Sun, M Wu, W Ruan, X Huang, M Kwiatkowska, D Kroening Proceedings of the 33rd ACM/IEEE International Conference on Automated …, 2018 | 364 | 2018 |
A game-based approximate verification of deep neural networks with provable guarantees M Wu, M Wicker, W Ruan, X Huang, M Kwiatkowska Theoretical Computer Science 807, 298-329, 2020 | 138 | 2020 |
Global robustness evaluation of deep neural networks with provable guarantees for the Hamming distance W Ruan, M Wu, Y Sun, X Huang, D Kroening, M Kwiatkowska International Joint Conference on Artificial Intelligence, 2019 | 109 | 2019 |
Safety and trustworthiness of deep neural networks: A survey X Huang, D Kroening, M Kwiatkowska, W Ruan, Y Sun, E Thamo, M Wu, ... arXiv preprint arXiv:1812.08342, 151, 2018 | 49 | 2018 |
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Norm W Ruan, M Wu, Y Sun, X Huang, D Kroening, M Kwiatkowska arXiv preprint arXiv:1804.05805, 2018 | 37 | 2018 |
Gaze-based Intention Anticipation over Driving Manoeuvres in Semi-Autonomous Vehicles M Wu, T Louw, M Lahijanian, W Ruan, X Huang, N Merat, M Kwiatkowska 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 34 | 2019 |
Robustness Guarantees for Deep Neural Networks on Videos M Wu, M Kwiatkowska 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 33 | 2020 |
A survey of safety and trustworthiness of deep neural networks X Huang, D Kroening, W Ruan, J Sharp, Y Sun, E Thamo, M Wu, X Yi arXiv preprint arXiv:1812.08342, 2018 | 23 | 2018 |
Assessing Robustness of Text Classification through Maximal Safe Radius Computation E La Malfa, M Wu, L Laurenti, B Wang, A Hartshorn, M Kwiatkowska Findings of the Association for Computational Linguistics: EMNLP 2020, 2949-2968, 2020 | 21 | 2020 |
Marabou 2.0: a versatile formal analyzer of neural networks H Wu, O Isac, A Zeljić, T Tagomori, M Daggitt, W Kokke, I Refaeli, G Amir, ... International Conference on Computer Aided Verification, 249-264, 2024 | 19 | 2024 |
Verix: Towards verified explainability of deep neural networks M Wu, H Wu, C Barrett Advances in Neural Information Processing Systems 36, 22247-22268, 2023 | 15 | 2023 |
Full Poincaré polarimetry enabled through physical inference C He, J Lin, J Chang, J Antonello, B Dai, J Wang, J Cui, J Qi, M Wu, ... Optica 9 (10), 1109-1114, 2022 | 14* | 2022 |
Towards Efficient Verification of Quantized Neural Networks P Huang, H Wu, Y Yang, I Daukantas, M Wu, Y Zhang, C Barrett Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21152 …, 2024 | 9 | 2024 |
Convex bounds on the softmax function with applications to robustness verification D Wei, H Wu, M Wu, PY Chen, C Barrett, E Farchi International Conference on Artificial Intelligence and Statistics, 6853-6878, 2023 | 8 | 2023 |
Robustness Evaluation of Deep Neural Networks with Provable Guarantees M Wu University of Oxford, 2020 | 2 | 2020 |
Policy-specific abstraction predicate selection in neural policy safety verification M Vinzent, M Wu, H Wu, J Hoffmann Proc. 2nd Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS …, 2023 | 1 | 2023 |
Better Verified Explanations with Applications to Incorrectness and Out-of-Distribution Detection M Wu, X Li, H Wu, C Barrett arXiv preprint arXiv:2409.03060, 2024 | | 2024 |
Parallel Verification for -Equivalence of Neural Network Quantization P Huang, Y Yang, H Wu, I Daukantas, M Wu, F Jia, C Barrett International Symposium on AI Verification, 78-99, 2024 | | 2024 |