| Safety verification of deep neural networks X Huang, M Kwiatkowska, S Wang, M Wu Computer Aided Verification: 29th International Conference, CAV 2017 …, 2017 | 997 | 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 | 439 | 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 | 310 | 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 | 119 | 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 | 90 | 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 | 30 | 2020 |
| 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 | 29 | 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 | 23 | 2019 |
| 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 | 22 | 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 | 19 | 2020 |
| 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 | 12* | 2022 |
| VeriX: Towards Verified Explainability of Deep Neural Networks M Wu, H Wu, C Barrett arXiv preprint arXiv:2212.01051, 2022 | 4 | 2022 |
| 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 | 2 | 2023 |
| 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 |
| Robustness Evaluation of Deep Neural Networks with Provable Guarantees M Wu University of Oxford, 2020 | 1 | 2020 |
| Soy: An Efficient MILP Solver for Piecewise-Affine Systems H Wu, M Wu, D Sadigh, C Barrett arXiv preprint arXiv:2303.13697, 2023 | | 2023 |
| Full Poincaré polarimetry enabled through physical inference: supplemental document C HE, J LIN, J CHANG, J ANTONELLO, BEN DAI, J WANG, J CUI, JI QI, ... | | 2022 |
| 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 | | 2018 |
| Full Poincaré polarimetry enabled through physical inference: supplement C HE, J LIN, J CHANG, J ANTONELLO, BEN DAI, J WANG, J CUI, JI QI, ... | | |
Marta KwiatkowskaProfessor of Computing Systems, University of OxfordVerified email at comlab.ox.ac.uk
