| Safety verification of deep neural networks X Huang, M Kwiatkowska, S Wang, M Wu International Conference on Computer Aided Verification, 3-29, 2017 | 758 | 2017 |
| Concolic Testing for Deep Neural Networks Y Sun, M Wu, W Ruan, X Huang, M Kwiatkowska, D Kroening ASE2018, 2018 | 216 | 2018 |
| Reachability Analysis of Deep Neural Networks with Provable Guarantees W Ruan, X Huang, M Kwiatkowska IJCAI2018, 2018 | 196 | 2018 |
| Feature-guided black-box safety testing of deep neural networks M Wicker, X Huang, M Kwiatkowska International Conference on Tools and Algorithms for the Construction and …, 2018 | 186 | 2018 |
| Testing deep neural networks Y Sun, X Huang, D Kroening, J Sharp, M Hill, R Ashmore arXiv preprint arXiv:1803.04792, 2018 | 180 | 2018 |
| 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 | 148 | 2020 |
| 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 | 80 | 2020 |
| Structural test coverage criteria for deep neural networks Y Sun, X Huang, D Kroening, J Sharp, M Hill, R Ashmore Proceedings of the 41st International Conference on Software Engineering …, 2019 | 62 | 2019 |
| An epistemic strategy logic X Huang, RVD Meyden ACM Transactions on Computational Logic (TOCL) 19 (4), 26, 2018 | 61* | 2018 |
| Symbolic model checking epistemic strategy logic X Huang, R van der Meyden Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence …, 2014 | 47 | 2014 |
| 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 | 46 | 2019 |
| 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, 2018 | 44 | 2018 |
| Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification J Li, J Liu, P Yang, L Chen, X Huang, L Zhang International Static Analysis Symposium, 296-319, 2019 | 39 | 2019 |
| DeepConcolic: testing and debugging deep neural networks Y Sun, X Huang, D Kroening, J Sharp, M Hill, R Ashmore 2019 IEEE/ACM 41st International Conference on Software Engineering …, 2019 | 39 | 2019 |
| Reasoning about cognitive trust in stochastic multiagent systems X Huang, M Kwiatkowska, M Olejnik ACM Transactions on Computational Logic (TOCL) 20 (4), 1-64, 2019 | 33 | 2019 |
| A safety framework for critical systems utilising deep neural networks X Zhao, A Banks, J Sharp, V Robu, D Flynn, M Fisher, X Huang International Conference on Computer Safety, Reliability, and Security, 244-259, 2020 | 31 | 2020 |
| Symbolic model checking of probabilistic knowledge X Huang, C Luo, R Van Der Meyden Proceedings of the 13th Conference on Theoretical Aspects of Rationality and …, 2011 | 29 | 2011 |
| Probabilistic alternating-time temporal logic of incomplete information and synchronous perfect recall X Huang, K Su, C Zhang Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 765-771, 2012 | 28 | 2012 |
| 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 |
| 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 | 22 | 2018 |
Marta KwiatkowskaProfessor of Computing Systems, University of Oxford在 comlab.ox.ac.uk 的电子邮件经过验证
