research
∙
07/18/2023
Cross-Validation Based Adaptive Sampling for Multi-Level Gaussian Process Models
Complex computer codes or models can often be run in a hierarchy of diff...
share
research
∙
12/07/2022
Modelling Correlated Bernoulli Data Part II: Inference
Binary data are highly common in many applications, however it is usuall...
research
∙
11/30/2022
Modelling Correlated Bernoulli Data Part I: Theory and Run Lengths
Binary data are very common in many applications, and are typically simu...
research
∙
06/24/2022
Sequential adaptive design for emulating costly computer codes
Gaussian processes (GPs) are generally regarded as the gold standard sur...
research
∙
06/22/2022
Variance-based global sensitivity analysis of numerical models using R
Sensitivity analysis plays an important role in the development of compu...
research
∙
04/11/2022
A Bayesian Decision Support System in Energy Systems Planning
Gaussian Process (GP) emulators are widely used to approximate complex c...
research
∙
05/17/2021
Stochastic Downscaling to Chaotic Weather Regimes using Spatially Conditioned Gaussian Random Fields with Adaptive Covariance
Downscaling aims to link the behaviour of the atmosphere at fine scales ...
research
∙
04/15/2021
Emulating computationally expensive dynamical simulators using Gaussian processes
A Gaussian process (GP)-based methodology is proposed to emulate computa...
research
∙
05/04/2020
Cross-validation based adaptive sampling for Gaussian process models
In many real-world applications, we are interested in approximating blac...
research
∙
01/31/2020
Classification of Computer Models with Labelled Outputs
Classification is a vital tool that is important for modelling many comp...
research
∙
01/07/2020
Future Proofing a Building Design Using History Matching Inspired Level Set Techniques
History Matching is a technique used to calibrate complex computer model...
research
∙
03/05/2019
Emulating computer models with step-discontinuous outputs using Gaussian processes
In many real-world applications, we are interested in approximating func...
research
∙
02/04/2019
Predicting the Output From a Stochastic Computer Model When a Deterministic Approximation is Available
The analysis of computer models can be aided by the construction of surr...
research
∙
02/04/2019
Diagnostics for Stochastic Emulators
Computer models, also known as simulators, can be computationally expens...
research
∙
01/22/2019
Modelling Numerical Systems with Two Distinct Labelled Output Classes
We present a new method of modelling numerical systems where there are t...
research
∙
02/21/2018