39 citations · 140 across the 29 of their papers we have counts for
5 papers · 1 filter
Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market
Beatrice Franzolini, Alexandros Beskos, Maria De Iorio +2
Reliable estimates of volatility and correlation are fundamental in economics and finance for understanding the impact of macroeconomics events on the market and guiding future inv…
Bayesian Dynamic Network Modelling: an application to metabolic associations in cardiovascular diseases
Marco Molinari, Andrea Cremaschi, Maria De Iorio +3
We propose a novel approach to the estimation of multiple Graphical Models to analyse temporal patterns of association among a set of metabolites over different groups of patients.…
Bayesian clustering of multiple zero-inflated outcomes
Beatrice Franzolini, Andrea Cremaschi, Willem van den Boom +1
Several applications involving counts present a large proportion of zeros (excess-of-zeros data). A popular model for such data is the Hurdle model, which explicitly models the pro…
On a wider class of prior distributions for graphical models
Abhinav Natarajan, Willem van den Boom, Kristoforus Bryant Odang +1
Gaussian graphical models are useful tools for conditional independence structure inference of multivariate random variables. Unfortunately, Bayesian inference of latent graph stru…
Bayesian Learning of Graph Substructures
Willem van den Boom, Maria De Iorio, Alexandros Beskos
Graphical models provide a powerful methodology for learning the conditional independence structure in multivariate data. Inference is often focused on estimating individual edges…