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