Xingyu Zhao
Xingyu Zhao
Assistant Professor, University of Warwick
Подтвержден адрес электронной почты в домене warwick.ac.uk - Главная страница
Machine learning methods for wind turbine condition monitoring: A review
A Stetco, F Dinmohammadi, X Zhao, V Robu, D Flynn, M Barnes, J Keane, ...
Renewable energy 133, 620-635, 2019
BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations
X Zhao, W Huang, X Huang, V Robu, D Flynn
UAI'21: 37th Conf. on Uncertainty in Artificial Intelligence, 887-896, 2021
Assessing the Safety and Reliability of Autonomous Vehicles from Road Testing
X Zhao, V Robu, D Flynn, K Salako, L Strigini
ISSRE'19: IEEE 30th Int. Symp. on Software Reliability Engineering, 13-23, 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
Computer Safety, Reliability, and Security 12234, 244-259, 2020
Coverage Guided Testing for Recurrent Neural Networks
W Huang, Y Sun, X Zhao, J Sharp, W Ruan, J Meng, X Huang
IEEE Transactions on Reliability 71 (3), 1191-1206, 2021
Probabilistic Model Checking of Robots Deployed in Extreme Environments
X Zhao, V Robu, D Flynn, F Dinmohammadi, M Fisher, M Webster
AAAI'19: Proc. of the AAAI Conference on Artificial Intelligence 33, 8066-8074, 2019
A New Approach to Assessment of Confidence in Assurance Cases
X Zhao, D Zhang, M Lu, F Zeng
Computer Safety, Reliability, and Security 7613, 79-91, 2012
Verifiable self-certifying autonomous systems
M Fisher, E Collins, L Dennis, M Luckcuck, M Webster, M Jump, V Page, ...
ISSRE'18: IEEE 29th Int. Symp. on Software Reliability Engineering Workshops …, 2018
Assessing safety-critical systems from operational testing: A study on autonomous vehicles
X Zhao, K Salako, L Strigini, V Robu, D Flynn
Information and Software Technology 128, 106393, 2020
Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles
X Zhao, W Huang, A Banks, V Cox, D Flynn, S Schewe, X Huang
AISafety'21: Workshop on AI Safety at IJCAI-21, 2021
Modeling the probability of failure on demand (pfd) of a 1-out-of-2 system in which one channel is “quasi-perfect”
X Zhao, B Littlewood, A Povyakalo, L Strigini, D Wright
Reliability Engineering & System Safety 158, 230-245, 2017
Interval change-point detection for runtime probabilistic model checking
X Zhao, R Calinescu, S Gerasimou, V Robu, D Flynn
ASE'20: 35th IEEE/ACM Int. Conf. on Automated Software Engineering, 2020
On Reliability Assessment When a Software-based System Is Replaced by a Thought-to-be-Better One
B Littlewood, K Salako, L Strigini, X Zhao
Reliability Engineering & System Safety 197, 106752, 2020
Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance
Y Dong, W Huang, V Bharti, V Cox, A Banks, S Wang, X Zhao, S Schewe, ...
ACM Transactions on Embedded Computing Systems, 2022
Towards integrating formal verification of autonomous robots with battery prognostics and health management
X Zhao, M Osborne, J Lantair, V Robu, D Flynn, X Huang, M Fisher, ...
SEFM'19: Int. Conf. on Software Engineering and Formal Methods, 105-124, 2019
UAS Operators Safety and Reliability Survey: Emerging Technologies towards the Certification of Autonomous UAS
M Osborne, J Lantair, Z Shafiq, X Zhao, V Robu, D Flynn, J Perry
ICSRS'19: IEEE Int. Conf. on System Reliability and Safety, 203-212, 2019
Conservative claims for the probability of perfection of a software-based system using operational experience of previous similar systems
X Zhao, B Littlewood, A Povyakalo, L Strigini, D Wright
Reliability Engineering & System Safety 175, 265-282, 2018
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation
X Huang, W Ruan, W Huang, G Jin, Y Dong, C Wu, S Bensalem, R Mu, ...
arXiv preprint arXiv:2305.11391, 2023
Conservative Claims about the Probability of Perfection of Software-based Systems
X Zhao, B Littlewood, A Povyakalo, D Wright
ISSRE'15: IEEE 26th Int. Symp. on Software Reliability Engineering, 130-140, 2015
Detecting Operational Adversarial Examples for Reliable Deep Learning
X Zhao, W Huang, S Schewe, Y Dong, X Huang
DSN'21: 51st IEEE/IFIP Int. Conf. on Dependable Systems and Networks, 2021
В данный момент система не может выполнить эту операцию. Повторите попытку позднее.
Статьи 1–20