Wei Huang

According to our database, Wei Huang authored at least 24 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A survey of safety and trustworthiness of large language models through the lens of verification and validation.

Xiaowei Huang, Wenjie Ruan, Wei Huang, Gaojie Jin, Yi Dong, Changshun Wu, Saddek Bensalem, Ronghui Mu, Yi Qi, Xingyu Zhao, Kaiwen Cai, Yanghao Zhang, Sihao Wu, Peipei Xu, Dengyu Wu, André Freitas, Mustafa A. Mustafa

Artif. Intell. Rev., July, 2024

Hierarchical Distribution-aware Testing of Deep Learning.

Wei Huang, Xingyu Zhao, Alec Banks, Victoria Cox, Xiaowei Huang

ACM Trans. Softw. Eng. Methodol., February, 2024

A simple framework to enhance the adversarial robustness of deep learning-based intrusion detection system.

Xinwei Yuan, Shu Han, Wei Huang, Hongliang Ye, Xianglong Kong, Fan Zhang

Comput. Secur., February, 2024

Formal verification of robustness and resilience of learning-enabled state estimation systems.

Wei Huang, Yifan Zhou, Gaojie Jin, Youcheng Sun, Jie Meng, Fan Zhang, Xiaowei Huang

Neurocomputing, 2024

Diversity supporting robustness: Enhancing adversarial robustness via differentiated ensemble predictions.

Xi Chen, Wei Huang, Ziwen Peng, Wei Guo, Fan Zhang

Comput. Secur., 2024

Eidos: Efficient, Imperceptible Adversarial 3D Point Clouds.

Hanwei Zhang, Luo Cheng, Qisong He, Wei Huang, Renjue Li, Ronan Sicre, Xiaowei Huang, Holger Hermanns, Lijun Zhang

Proceedings of the Dependable Software Engineering. Theories, Tools, and Applications, 2024

Ensemble Adversarial Defense via Integration of Multiple Dispersed Low Curvature Models.

Kaikang Zhao, Xi Chen, Wei Huang, Liuxin Ding, Xianglong Kong, Fan Zhang

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance.

Yi Dong, Wei Huang, Vibhav Bharti, Victoria Cox, Alec Banks, Sen Wang, Xingyu Zhao, Sven Schewe, Xiaowei Huang

ACM Trans. Embed. Comput. Syst., 2023

What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety-Critical Systems.

Saddek Bensalem, Chih-Hong Cheng, Wei Huang, Xiaowei Huang, Changshun Wu, Xingyu Zhao

Proceedings of the Bridging the Gap Between AI and Reality, 2023

SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability.

Wei Huang, Xingyu Zhao, Gaojie Jin, Xiaowei Huang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Coverage-Guided Testing for Recurrent Neural Networks.

Wei Huang, Youcheng Sun, Xingyu Zhao, James Sharp, Wenjie Ruan, Jie Meng, Xiaowei Huang

IEEE Trans. Reliab., 2022

Embedding and extraction of knowledge in tree ensemble classifiers.

Wei Huang, Xingyu Zhao, Xiaowei Huang

Mach. Learn., 2022

A Hierarchical HAZOP-Like Safety Analysis for Learning-Enabled Systems.

Yi Qi, Philippa Ryan Conmy, Wei Huang, Xingyu Zhao, Xiaowei Huang

Proceedings of the Workshop on Artificial Intelligence Safety 2022 (AISafety 2022) co-located with the Thirty-First International Joint Conference on Artificial Intelligence and the Twenty-Fifth European Conference on Artificial Intelligence (IJCAI-ECAI-2022), 2022

Enhancing Adversarial Training with Second-Order Statistics of Weights.

Gaojie Jin, Xinping Yi, Wei Huang, Sven Schewe, Xiaowei Huang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Reliability Assessment and Safety Arguments for Machine Learning Components in Assuring Learning-Enabled Autonomous Systems.

Xingyu Zhao, Wei Huang, Vibhav Bharti, Yi Dong, Victoria Cox, Alec Banks, Sen Wang, Sven Schewe, Xiaowei Huang

CoRR, 2021

Tutorials on Testing Neural Networks.

Nicolas Berthier, Youcheng Sun, Wei Huang, Yanghao Zhang, Wenjie Ruan, Xiaowei Huang

CoRR, 2021

BayLIME: Bayesian local interpretable model-agnostic explanations.

Xingyu Zhao, Wei Huang, Xiaowei Huang, Valentin Robu, David Flynn

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles.

Xingyu Zhao, Wei Huang, Alec Banks, Victoria Cox, David Flynn, Sven Schewe, Xiaowei Huang

Proceedings of the Workshop on Artificial Intelligence Safety 2021 co-located with the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI 2021), 2021

Detecting Operational Adversarial Examples for Reliable Deep Learning.

Xingyu Zhao, Wei Huang, Sven Schewe, Yi Dong, Xiaowei Huang

Proceedings of the 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2021

2020

Formal Verification of Robustness and Resilience of Learning-Enabled State Estimation Systems for Robotics.

Wei Huang, Yifan Zhou, Youcheng Sun, Alec Banks, Jie Meng, James Sharp, Simon Maskell, Xiaowei Huang

CoRR, 2020

Embedding and Synthesis of Knowledge in Tree Ensemble Classifiers.

Wei Huang, Xingyu Zhao, Xiaowei Huang

CoRR, 2020

Practical Verification of Neural Network Enabled State Estimation System for Robotics.

Wei Huang, Yifan Zhou, Youcheng Sun, James Sharp, Simon Maskell, Xiaowei Huang

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

2019

Test Metrics for Recurrent Neural Networks.

Wei Huang, Youcheng Sun, James Sharp, Xiaowei Huang

CoRR, 2019

testRNN: Coverage-guided Testing on Recurrent Neural Networks.

Wei Huang, Youcheng Sun, Xiaowei Huang, James Sharp

CoRR, 2019