activity
20192026
most citedBinary De Bruijn Processes

1 citations · 1 across the 7 of their papers we have counts for

collaborators

8 papers

stat.AP2026

Bayesian Emulation of Multi-fidelity Earth System Modelling Using Hierarchical Gaussian Processes

Xiaoyu Xiong, Louise Kimpton, Huiyi Yang +3

Multi-fidelity Earth system models provide simulations at different levels of complexity and computational cost, but exhaustive exploration of the parameter space at the highest fi…

stat.ME2025

Bayesian Hierarchical Emulators for Multi-Level Models: BayHEm

Louise Kimpton, James Salter, Xiaoyu Xiong +1

Decision making often uses complex computer codes run at the exa-scale (10e18 flops). Such computer codes or models are often run in a hierarchy of different levels of fidelity ran…

stat.OT2024

Uncertainty Quantification for Agent Based Models: A Tutorial

Louise Kimpton, Peter Challenor, James Salter

We explore the application of uncertainty quantification methods to agent-based models (ABMs) using a simple sheep and wolf predator-prey model. This work serves as a tutorial on h…

stat.ME2023

Cross-Validation Based Adaptive Sampling for Multi-Level Gaussian Process Models

Louise Kimpton, James Salter, Tim Dodwell +2

Complex computer codes or models can often be run in a hierarchy of different levels of complexity ranging from the very basic to the sophisticated. The top levels in this hierarch…

stat.ME2022

Modelling Correlated Bernoulli Data Part II: Inference

Louise Kimpton, Peter Challenor, Henry Wynn

Binary data are highly common in many applications, however it is usually modelled with the assumption that the data are independently and identically distributed. This is typicall…

stat.ME2022★ 1 cited

Binary De Bruijn Processes

Louise Kimpton, Peter Challenor, Henry Wynn

Binary time series data are very common in many applications, and are typically modelled independently via a Bernoulli process with a single probability of success. However, the pr…

stat.ME2020

Classification of Computer Models with Labelled Outputs

Louise Kimpton, Peter Challenor, Daniel Williamson

Classification is a vital tool that is important for modelling many complex numerical models. A model or system may be such that, for certain areas of input space, the output eithe…

stat.ME2019

Modelling Numerical Systems with Two Distinct Labelled Output Classes

Louise Kimpton, Peter Challenor, Daniel Williamson

We present a new method of modelling numerical systems where there are two distinct output solution classes, for example tipping points or bifurcations. Gaussian process emulation…