Source Themes

Bayesian inference of multiple Ising models for heterogeneous data
Bayesian inference of multiple Ising models for heterogeneous data
On the application of Gaussian graphical models to paired data problems
Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure
Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure
Bayesian Inference of Multiple Ising Models for Heterogeneous Data
Bayesian Inference of Multiple Ising Models for Heterogeneous Data
Exploration of the search space of Gaussian graphical models for paired data
Bayesian nonparametric mixtures of directed acyclic graphs for heterogeneous causal inference
Bayesian sample size determination for causal discovery
Causal glms within a graphical modelling framework
Learning Gaussian graphical models for paired data with the pdglasso
MCMC sampling for Bayesian Gaussian structural learning