3 papers
stat.ME2025
Exchangeable Gaussian Processes with application to epidemics
Lampros Bouranis, Petros Barmpounakis, Nikolaos Demiris +1
We develop a Bayesian non-parametric framework based on multi-task Gaussian processes, appropriate for temporal shrinkage. We focus on a particular class of dynamic hierarchical mo…
stat.ME2025
On a Reinforcement Learning Methodology for Epidemic Control, with application to COVID-19
Giacomo Iannucci, Petros Barmpounakis, Alexandros Beskos +1
This paper presents a real time, data driven decision support framework for epidemic control. We combine a compartmental epidemic model with sequential Bayesian inference and reinf…
stat.AP2023
Multiphasic stochastic epidemic models
Petros Barmpounakis, Nikolaos Demiris
At the onset of the Covid-19 pandemic, a number of non-pharmaceutical interventions have been implemented in order to reduce transmission, thus leading to multiple phases of transm…