56 citations · 61 across the 3 of their papers we have counts for
3 papers
On the development of a practical Bayesian optimisation algorithm for expensive experiments and simulations with changing environmental conditions
Mike Diessner, Kevin J. Wilson, Richard D. Whalley
Experiments in engineering are typically conducted in controlled environments where parameters can be set to any desired value. This assumes that the same applies in a real-world s…
NUBO: A Transparent Python Package for Bayesian Optimization
Mike Diessner, Kevin J. Wilson, Richard D. Whalley
NUBO, short for Newcastle University Bayesian Optimisation, is a Bayesian optimization framework for the optimization of expensive-to-evaluate black-box functions, such as physical…
Investigating Bayesian optimization for expensive-to-evaluate black box functions: Application in fluid dynamics
Mike Diessner, Joseph O'Connor, Andrew Wynn +4
Bayesian optimization provides an effective method to optimize expensive-to-evaluate black box functions. It has been widely applied to problems in many fields, including notably i…