
Min Wu
Postdoctoral Scholar, Computer Science
Professional Education
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Doctor of Philosophy, University of Oxford, Computer Science (2020)
Current Research and Scholarly Interests
Safe and trustworthy AI: robustness, explainability, and fairness
All Publications
- Convex Bounds on the Softmax Function with Applications to Robustness Verification Proceedings of The 26th International Conference on Artificial Intelligence and Statistics 2023: 6853-6878
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Full Poincare polarimetry enabled through physical inference
OPTICA
2022; 9 (10): 1109-1114
View details for DOI 10.1364/OPTICA.452646
View details for Web of Science ID 000880667200002
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A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability?
COMPUTER SCIENCE REVIEW
2020; 37
View details for DOI 10.1016/j.cosrev.2020.100270
View details for Web of Science ID 000559782300009
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A game-based approximate verification of deep neural networks with provable guarantees
THEORETICAL COMPUTER SCIENCE
2020; 807: 298-329
View details for DOI 10.1016/j.tcs.2019.05.046
View details for Web of Science ID 000512219400020
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Robustness Guarantees for Deep Neural Networks on Videos
IEEE. 2020: 308-317
View details for DOI 10.1109/CVPR42600.2020.00039
View details for Web of Science ID 000620679500032
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Assessing Robustness of Text Classification through Maximal Safe Radius Computation
Findings of the Association for Computational Linguistics: EMNLP 2020
2020: 2949-2968
View details for DOI 10.18653/v1/2020.findings-emnlp.266
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Gaze-based Intention Anticipation over Driving Manoeuvres in Semi-Autonomous Vehicles
IEEE. 2019: 6210-6216
View details for Web of Science ID 000544658404127
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Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
2019: 5944-5952
View details for DOI 10.24963/ijcai.2019/824
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Concolic Testing for Deep Neural Networks
IEEE. 2018: 109-119
View details for DOI 10.1145/3238147.3238172
View details for Web of Science ID 000553784500014
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Safety Verification of Deep Neural Networks
SPRINGER INTERNATIONAL PUBLISHING AG. 2017: 3-29
View details for DOI 10.1007/978-3-319-63387-9_1
View details for Web of Science ID 000432196400001