Despite major methodological developments, Bayesian inference in Gaussian graphical models remains challenging in high dimension due to the tremendous size of the model space. This article proposes a ...

Graphical models form a cornerstone of modern data analysis by providing a visually intuitive framework to represent and reason about the complex interdependencies among variables. In particular, ...

Gaussian graphical models have received considerable attention during the past four decades from the statistical and machine learning communities. In Bayesian treatments of this model, the G-Wishart ...