1 citations · 1 across the 3 of their papers we have counts for
3 papers
The Traceplot Thickens: Developing All-Purpose Convergence Diagnostics for any Markov Chain Monte Carlo Algorithm
Luke Duttweiler, Jonathan Klus, Brent A. Coull +3
Markov Chain Monte Carlo (MCMC) algorithms are frequently used to perform inference under a Bayesian modeling framework. Convergence diagnostics, such as traceplots, the Gelman-Rub…
Testing Sparsity Assumptions in Bayesian Networks
Luke Duttweiler, Sally W. Thurston, Anthony Almudevar
Bayesian network (BN) structure discovery algorithms typically either make assumptions about the sparsity of the true underlying network, or are limited by computational constraint…
Spectral Bayesian Network Theory
Luke Duttweiler, Sally W. Thurston, Anthony Almudevar
A Bayesian Network (BN) is a probabilistic model that represents a set of variables using a directed acyclic graph (DAG). Current algorithms for learning BN structures from data fo…