3 citations · 3 across the 4 of their papers we have counts for
4 papers
Bayesian Inference for partially observed SDEs Driven by Fractional Brownian Motion
Alexandros Beskos, Joseph Dureau, Konstantinos Kalogeropoulos
We consider continuous-time diffusion models driven by fractional Brownian motion. Observations are assumed to possess a non-trivial likelihood given the latent path. Due to the no…
A Bayesian approach to estimate changes in condom use from limited HIV prevalence data
Joseph Dureau, Konstantinos Kalogeropoulos, Peter Vickerman +2
Evaluation of HIV large scale interventions programme is becoming increasingly important, but impact estimates frequently hinge on knowledge of changes in behaviour such as the fre…
Advanced MCMC Methods for Sampling on Diffusion Pathspace
Alexandros Beskos, Konstantinos Kalogeropoulos, Erik Pazos
The need to calibrate increasingly complex statistical models requires a persistent effort for further advances on available, computationally intensive Monte Carlo methods. We stud…
Capturing the time-varying drivers of an epidemic using stochastic dynamical systems
Joseph Dureau, Konstantinos Kalogeropoulos, Marc Baguelin
Epidemics are often modelled using non-linear dynamical systems observed through partial and noisy data. In this paper, we consider stochastic extensions in order to capture unknow…