47 citations · 59 across the 5 of their papers we have counts for
5 papers
Learning Run-time Safety Monitors for Machine Learning Components
Ozan Vardal, Richard Hawkins, Colin Paterson +4
For machine learning components used as part of autonomous systems (AS) in carrying out critical tasks it is crucial that assurance of the models can be maintained in the face of p…
Creating a Safety Assurance Case for an ML Satellite-Based Wildfire Detection and Alert System
Richard Hawkins, Chiara Picardi, Lucy Donnell +1
Wildfires are a common problem in many areas of the world with often catastrophic consequences. A number of systems have been created to provide early warnings of wildfires, includ…
Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS)
Richard Hawkins, Colin Paterson, Chiara Picardi +3
Machine Learning (ML) is now used in a range of systems with results that are reported to exceed, under certain conditions, human performance. Many of these systems, in domains suc…
Enhancing Covid-19 Decision-Making by Creating an Assurance Case for Simulation Models
Ibrahim Habli, Rob Alexander, Richard Hawkins +4
Simulation models have been informing the COVID-19 policy-making process. These models, therefore, have significant influence on risk of societal harms. But how clearly are the und…
Detection and Mitigation of Rare Subclasses in Deep Neural Network Classifiers
Colin Paterson, Radu Calinescu, Chiara Picardi
Regions of high-dimensional input spaces that are underrepresented in training datasets reduce machine-learnt classifier performance, and may lead to corner cases and unwanted bias…