2 citations · 3 across the 4 of their papers we have counts for
4 papers
Diffusion Generative Modelling for Divide-and-Conquer MCMC
C. Trojan, P. Fearnhead, C. Nemeth
Divide-and-conquer MCMC is a strategy for parallelising Markov Chain Monte Carlo sampling by running independent samplers on disjoint subsets of a dataset and merging their output.…
Inference on Extended-Spectrum Beta-Lactamase Escherichia coli and Klebsiella pneumoniae data through SMC
Lorenzo Rimella, Simon Alderton, Melodie Sammarro +5
We propose a novel stochastic model for the spread of antimicrobial-resistant bacteria in a population, together with an efficient algorithm for fitting such a model to sample data…
A computationally efficient, high-dimensional multiple changepoint procedure with application to global terrorism incidence
S. O. Tickle, I. A. Eckley, P. Fearnhead
Detecting changepoints in datasets with many variates is a data science challenge of increasing importance. Motivated by the problem of detecting changes in the incidence of terror…
On Estimating the Ability of NBA Players
Paul Fearnhead, Benjamin M. Taylor
This paper introduces a new model and methodology for estimating the ability of NBA players. The main idea is to directly measure how good a player is by comparing how their team p…