55 citations · 59 across the 2 of their papers we have counts for
8 papers
Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles
Xingyu Zhao, Wei Huang, Alec Banks +4
The utilisation of Deep Learning (DL) is advancing into increasingly more sophisticated applications. While it shows great potential to provide transformational capabilities, DL al…
BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations
Xingyu Zhao, Wei Huang, Xiaowei Huang +2
Given the pressing need for assuring algorithmic transparency, Explainable AI (XAI) has emerged as one of the key areas of AI research. In this paper, we develop a novel Bayesian e…
Embedding and Extraction of Knowledge in Tree Ensemble Classifiers
Wei Huang, Xingyu Zhao, Xiaowei Huang
The embedding and extraction of useful knowledge is a recent trend in machine learning applications, e.g., to supplement existing datasets that are small. Whilst, as the increasing…
Assessing Safety-Critical Systems from Operational Testing: A Study on Autonomous Vehicles
Xingyu Zhao, Kizito Salako, Lorenzo Strigini +2
Context: Demonstrating high reliability and safety for safety-critical systems (SCSs) remains a hard problem. Diverse evidence needs to be combined in a rigorous way: in particular…
A Safety Framework for Critical Systems Utilising Deep Neural Networks
Xingyu Zhao, Alec Banks, James Sharp +4
Increasingly sophisticated mathematical modelling processes from Machine Learning are being used to analyse complex data. However, the performance and explainability of these model…
Towards Integrating Formal Verification of Autonomous Robots with Battery Prognostics and Health Management
Xingyu Zhao, Matt Osborne, Jenny Lantair +6
The battery is a key component of autonomous robots. Its performance limits the robot's safety and reliability. Unlike liquid-fuel, a battery, as a chemical device, exhibits compli…