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20232026
most citedScalable Bayesian Structure Learning for Gaussian Graphical Models Using Marginal Pseudo-likelihood

2 citations · 2 across the 5 of their papers we have counts for

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stat.ME2023

Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison

Lucas Vogels, Reza Mohammadi, Marit Schoonhoven +1

Gaussian graphical models provide a powerful framework to reveal the conditional dependency structure between multivariate variables. The process of uncovering the conditional depe…

stat.ME2023★ 2 cited

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…