Search Results for author:
Found 3 papers, 3 papers with code
Bayesian Joint Spike-and-Slab Graphical Lasso
In this article, we propose a new class of priors for Bayesian inference with multiple Gaussian graphical models.
Using Bayesian latent Gaussian graphical models to infer symptom associations in verbal autopsies
Learning dependence relationships among variables of mixed types provides insights in a variety of scientific settings and is a well-studied problem in statistics.
Applications
An Expectation Conditional Maximization approach for Gaussian graphical models
Bayesian graphical models are a useful tool for understanding dependence relationships among many variables, particularly in situations with external prior information.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
