16 citations · 58 across the 21 of their papers we have counts for
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stat.AP2017
Using Bayesian latent Gaussian graphical models to infer symptom associations in verbal autopsies
Zehang Richard Li, Tyler H. McCormick, Samuel J. Clark
Learning dependence relationships among variables of mixed types provides insights in a variety of scientific settings and is a well-studied problem in statistics. Existing methods…
stat.ML2017★ 2 cited
An Expectation Conditional Maximization approach for Gaussian graphical models
Zehang Richard Li, Tyler H. McCormick
Bayesian graphical models are a useful tool for understanding dependence relationships among many variables, particularly in situations with external prior information. In high-dim…