123 citations · 174 across the 4 of their papers we have counts for
4 papers
Scalable Bayesian Structure Learning for Gaussian Graphical Models Using Marginal Pseudo-likelihood
Reza Mohammadi, Marit Schoonhoven, Lucas Vogels +1
Bayesian methods for learning Gaussian graphical models offer a principled framework for quantifying model uncertainty and incorporating prior knowledge. However, their scalability…
Continuous-Time Birth-Death MCMC for Bayesian Regression Tree Models
Reza Mohammadi, Matthew Pratola, Maurits Kaptein
Decision trees are flexible models that are well suited for many statistical regression problems. In a Bayesian framework for regression trees, Markov Chain Monte Carlo (MCMC) sear…
Gaussian graphical models reveal inter-modal and inter-regional conditional dependencies of brain alterations in Alzheimer's disease
Martin Dyrba, Reza Mohammadi, Michel J. Grothe +2
Alzheimer's disease (AD) is characterized by a sequence of pathological changes, which are commonly assessed in vivo using MRI and PET. Currently, the most approaches to analyze st…
BDgraph: An R Package for Bayesian Structure Learning in Graphical Models
Reza Mohammadi, Ernst C. Wit
Graphical models provide powerful tools to uncover complicated patterns in multivariate data and are commonly used in Bayesian statistics and machine learning. In this paper, we in…