138 citations · 138 across the 5 of their papers we have counts for
9 papers
A Bayesian Decision Support System in Energy Systems Planning
Victoria Volodina, Nikki Sonenberg, Peter Challenor +1
Gaussian Process (GP) emulators are widely used to approximate complex computer model behaviour across the input space. Motivated by the problem of coupling computer models, recent…
A microsimulation of spatial inequality in energy access: A Bayesian multi-level modelling approach for urban India
A. P. Neto-Bradley, R. Choudhary, P. Challenor
Access to sustained clean cooking in India is essential to addressing the health burden of indoor air pollution from biomass fuels, but spatial inequality in cities can adversely a…
Stochastic Downscaling to Chaotic Weather Regimes using Spatially Conditioned Gaussian Random Fields with Adaptive Covariance
Rachel Prudden, Niall Robinson, Peter Challenor +1
Downscaling aims to link the behaviour of the atmosphere at fine scales to properties measurable at coarser scales, and has the potential to provide high resolution information at…
Key Questions for Modelling COVID-19 Exit Strategies
Robin N Thompson, T Deirdre Hollingsworth, Valerie Isham +40
Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to impl…
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…
Future Proofing a Building Design Using History Matching Inspired Level-Set Techniques
Evan Baker, Peter Challenor, Matt Eames
History Matching is a technique used to calibrate complex computer models, that is, finding the input settings which lead to the simulated output matching up with real world observ…