55 citations · 78 across the 4 of their papers we have counts for
12 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…
Machine learning pipeline for battery state of health estimation
Darius Roman, Saurabh Saxena, Valentin Robu +2
Lithium-ion batteries are ubiquitous in modern day applications ranging from portable electronics to electric vehicles. Irrespective of the application, reliable real-time estimati…
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…
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…
Consider ethical and social challenges in smart grid research
Valentin Robu, David Flynn, Merlinda Andoni +1
Artificial Intelligence and Machine Learning are increasingly seen as key technologies for building more decentralised and resilient energy grids, but researchers must consider the…