36 citations · 95 across the 12 of their papers we have counts for
14 papers
Empirical quantification of predictive uncertainty due to model discrepancy by training with an ensemble of experimental designs: an application to ion channel kinetics
Joseph G. Shuttleworth, Chon Lok Lei, Dominic G. Whittaker +4
When mathematical biology models are used to make quantitative predictions for clinical or industrial use, it is important that these predictions come with a reliable estimate of t…
The Bayesian Spatial Bradley--Terry Model: Urban Deprivation Modeling in Tanzania
R. G. Seymour, D. Sirl, S. Preston +4
Identifying the most deprived regions of any country or city is key if policy makers are to design successful interventions. However, locating areas with the greatest need is often…
Non-parametric regression for networks
Katie E. Severn, Ian L. Dryden, Simon P. Preston
Network data are becoming increasingly available, and so there is a need to develop suitable methodology for statistical analysis. Networks can be represented as graph Laplacian ma…
Invariance and identifiability issues for word embeddings
Rachel Carrington, Karthik Bharath, Simon Preston
Word embeddings are commonly obtained as optimizers of a criterion function of a text corpus, but assessed on word-task performance using a different evaluation function of…
Manifold valued data analysis of samples of networks, with applications in corpus linguistics
Katie E. Severn, Ian L. Dryden, Simon P. Preston
Networks arise in many applications, such as in the analysis of text documents, social interactions and brain activity. We develop a general framework for extrinsic statistical ana…
Quantifying Age and Model Uncertainties in Paleoclimate Data and Dynamical Climate Models with a Joint Inferential Analysis
Jake Carson, Michel Crucifix, Simon P. Preston +1
A major goal in paleoclimate science is to reconstruct historical climates using proxies for climate variables such as those observed in sediment cores, and in the process learn ab…