61 citations · 62 across the 6 of their papers we have counts for
6 papers
Probabilistic Numeric SMC Sampling for Bayesian Nonlinear System Identification in Continuous Time
Joe D. Longbottom, Max D. Champneys, Timothy J. Rogers
In engineering, accurately modeling nonlinear dynamic systems from data contaminated by noise is both essential and complex. Established Sequential Monte Carlo (SMC) methods, used…
Sharing Information Between Machine Tools to Improve Surface Finish Forecasting
Daniel R. Clarkson, Lawrence A. Bull, Tina A. Dardeno +6
At present, most surface-quality prediction methods can only perform single-task prediction which results in under-utilised datasets, repetitive work and increased experimental cos…
A spectrum of physics-informed Gaussian processes for regression in engineering
Elizabeth J Cross, Timothy J Rogers, Daniel J Pitchforth +2
Despite the growing availability of sensing and data in general, we remain unable to fully characterise many in-service engineering systems and structures from a purely data-driven…
PAO: A general particle swarm algorithm with exact dynamics and closed-form transition densities
Max D. Champneys, Timothy J. Rogers
A great deal of research has been conducted in the consideration of meta-heuristic optimisation methods that are able to find global optima in settings that gradient based optimise…
A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves
Marcus Haywood-Alexander, Nikolaos Dervilis, Keith Worden +3
Ultrasonic guided waves offer a convenient and practical approach to structural health monitoring and non-destructive evaluation. A key property of guided waves is the fully-define…
Physics-informed machine learning for Structural Health Monitoring
Elizabeth J Cross, Samuel J Gibson, Matthew R Jones +3
The use of machine learning in Structural Health Monitoring is becoming more common, as many of the inherent tasks (such as regression and classification) in developing condition-b…