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Xiaowei Huang
Xiaowei Huang
Professor of Computer Science, University of Liverpool
Verified email at liverpool.ac.uk - Homepage
Title
Cited by
Cited by
Year
Safety verification of deep neural networks
X Huang, M Kwiatkowska, S Wang, M Wu
International Conference on Computer Aided Verification, 3-29, 2017
10452017
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
4762020
Concolic Testing for Deep Neural Networks
Y Sun, M Wu, W Ruan, X Huang, M Kwiatkowska, D Kroening
ASE2018, 2018
3292018
Reachability Analysis of Deep Neural Networks with Provable Guarantees
W Ruan, X Huang, M Kwiatkowska
IJCAI2018, 2018
3012018
Feature-guided black-box safety testing of deep neural networks
M Wicker, X Huang, M Kwiatkowska
Tools and Algorithms for the Construction and Analysis of Systems: 24th …, 2018
2572018
Testing deep neural networks
Y Sun, X Huang, D Kroening, J Sharp, M Hill, R Ashmore
arXiv preprint arXiv:1803.04792, 2018
2482018
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
1252020
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
1132019
Machine Learning Safety
X Huang, G Jin, W Ruan
Springer, 2023
102*2023
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
972019
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
Static Analysis: 26th International Symposium, SAS 2019, Porto, Portugal …, 2019
882019
Spatial Uncertainty-Aware Semi-Supervised Crowd Counting
Y Meng, H Zhang, Y Zhao, X Yang, X Qian, X Huang, Y Zheng
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
782021
Baylime: Bayesian local interpretable model-agnostic explanations
X Zhao, W Huang, X Huang, V Robu, D Flynn
Uncertainty in Artificial Intelligence, 887-896, 2021
752021
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
652019
An epistemic strategy logic
X Huang, RVD Meyden
ACM Transactions on Computational Logic (TOCL) 19 (4), 26, 2018
65*2018
Symbolic model checking epistemic strategy logic
X Huang, R van der Meyden
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence …, 2014
552014
CNN-GCN aggregation enabled boundary regression for biomedical image segmentation
Y Meng, M Wei, D Gao, Y Zhao, X Yang, X Huang, Y Zheng
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
522020
A safety framework for critical systems utilising deep neural networks
X Zhao, A Banks, J Sharp, V Robu, D Flynn, M Fisher, X Huang
Computer Safety, Reliability, and Security: 39th International Conference …, 2020
502020
Graph-based region and boundary aggregation for biomedical image segmentation
Y Meng, H Zhang, Y Zhao, X Yang, Y Qiao, IJC MacCormick, X Huang, ...
IEEE transactions on medical imaging 41 (3), 690-701, 2021
472021
Enhancing Adversarial Training with Second-Order Statistics of Weights
G Jin, X Yi, W Huang, S Schewe, X Huang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
452022
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