327 citations · 2.5k across the 191 of their papers we have counts for
210 papers
Low-rank longitudinal factor regression with application to chemical mixtures
Glenn Palmer, Amy H. Herring, David B. Dunson
Developmental epidemiology commonly focuses on assessing the association between multiple early life exposures and childhood health. Statistical analyses of data from such studies…
Identifiable and interpretable nonparametric factor analysis
Maoran Xu, Steven Winter, Amy H. Herring +1
Factor models are widely used to reduce dimensionality in modeling high-dimensional data. However, there remains a need for models that can be reliably fit in modest sample sizes a…
Nonparametric Bayes multiresolution testing for high-dimensional rare events
Jyotishka Datta, Sayantan Banerjee, David B. Dunson
In a variety of application areas, there is interest in assessing evidence of differences in the intensity of event realizations between groups. For example, in cancer genomic stud…
Bayesian nonparametric modeling of latent partitions via Stirling-gamma priors
Alessandro Zito, Tommaso Rigon, David B. Dunson
Dirichlet process mixtures are particularly sensitive to the value of the precision parameter controlling the behavior of the latent partition. Randomization of the precision throu…
Inferring Covariance Structure from Multiple Data Sources via Subspace Factor Analysis
Noirrit Kiran Chandra, David B. Dunson, Jason Xu
Factor analysis provides a canonical framework for imposing lower-dimensional structure such as sparse covariance in high-dimensional data. High-dimensional data on the same set of…
Machine Learning and the Future of Bayesian Computation
Steven Winter, Trevor Campbell, Lizhen Lin +2
Bayesian models are a powerful tool for studying complex data, allowing the analyst to encode rich hierarchical dependencies and leverage prior information. Most importantly, they…