Graphical models provide a robust framework for representing the conditional independence structure between variables through networks, enabling nuanced insight into complex high-dimensional data.

Gaussian graphical models are recently used in economics to obtain networks of dependence among agents. A widely used estimator is the graphical least absolute shrinkage and selection operator (GLASSO ...

In this paper we propose a method to calculate the posterior probability of a nondecomposable graphical Gaussian model. Our proposal is based on a new device to sample from Wishart distributions, ...

Topics include directed and undirected graphical models, exact and approximate inference methods, and supervised and unsupervised parameter and structure learning. Grades: Homework will involve both ...

We have previously assumed that we already possess the information necessary to fill in the CPTs (or potentials) and our focus was on how to combine them to obtain a JPD. Things in real life are not ...