89 citations · 109 across the 8 of their papers we have counts for
11 papers
Consistency of mixture models with a prior on the number of components
Jeffrey W. Miller
This article establishes general conditions for posterior consistency of Bayesian finite mixture models with a prior on the number of components. That is, we provide sufficient con…
Bayesian data selection
Eli N. Weinstein, Jeffrey W. Miller
Insights into complex, high-dimensional data can be obtained by discovering features of the data that match or do not match a model of interest. To formalize this task, we introduc…
Bayesian Optimal Experimental Design for Inferring Causal Structure
Michele Zemplenyi, Jeffrey W. Miller
Inferring the causal structure of a system typically requires interventional data, rather than just observational data. Since interventional experiments can be costly, it is prefer…
Inference in generalized bilinear models
Jeffrey W. Miller, Scott L. Carter
Latent factor models are widely used to discover and adjust for hidden variation in modern applications. However, most methods do not fully account for uncertainty in the latent fa…
Robust Inference and Model Criticism Using Bagged Posteriors
Jonathan H. Huggins, Jeffrey W. Miller
Standard Bayesian inference is known to be sensitive to model misspecification, leading to unreliable uncertainty quantification and poor predictive performance. However, finding g…
Fast and accurate approximation of the full conditional for gamma shape parameters
Jeffrey W. Miller
The gamma distribution arises frequently in Bayesian models, but there is not an easy-to-use conjugate prior for the shape parameter of a gamma. This inconvenience is usually dealt…