62 citations · 177 across the 23 of their papers we have counts for
24 papers
Sequential Bayesian inference for stochastic epidemic models of cumulative incidence
Sam A. Whitaker, Andrew Golightly, Colin S. Gillespie +1
Epidemics are inherently stochastic, and stochastic models provide an appropriate way to describe and analyse such phenomena. Given temporal incidence data consisting of, for examp…
Accelerating Bayesian inference for stochastic epidemic models using incidence data
Andrew Golightly, Laura E. Wadkin, Sam A. Whitaker +3
We consider the case of performing Bayesian inference for stochastic epidemic compartment models, using incomplete time course data consisting of incidence counts that are either t…
A Bayesian Nonparametric Analysis of the 2003 Outbreak of Highly Pathogenic Avian Influenza in the Netherlands
R. G. Seymour, T. Kypraios, P. D. O'Neill +1
Infectious diseases on farms pose both public and animal health risks, so understanding how they spread between farms is crucial for developing disease control strategies to preven…
Scalable Bayesian Inference for Population Markov Jump Processes
Iker Perez, Theodore Kypraios
Bayesian inference for Markov jump processes (MJPs) where available observations relate to either system states or jumps typically relies on data-augmentation Markov Chain Monte Ca…
A comparative study of estimation methods in quantum tomography
Anirudh Acharya, Theodore Kypraios, Madalin Guta
As quantum tomography is becoming a key component of the quantum engineering toolbox, there is a need for a deeper understanding of the multitude of estimation methods available. H…
On Bayesian inferential tasks with infinite-state jump processes: efficient data augmentation
Iker Perez, Lax Chan, Mercedes Torres Torres +2
Advances in sampling schemes for Markov jump processes have recently enabled multiple inferential tasks. However, in statistical and machine learning applications, we often require…