3 papers
stat.ME2023
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…
stat.ML2019
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…
q-bio.NC2018
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…