336 citations · 1k across the 37 of their papers we have counts for
5 papers · 2 filters
Differential gene co-expression networks via Bayesian biclustering models
Chuan Gao, Shiwen Zhao, Ian C. McDowell +2
Identifying latent structure in large data matrices is essential for exploring biological processes. Here, we consider recovering gene co-expression networks from gene expression d…
Bayesian group latent factor analysis with structured sparsity
Shiwen Zhao, Chuan Gao, Sayan Mukherjee +1
Latent factor models are the canonical statistical tool for exploratory analyses of low-dimensional linear structure for an observation matrix with p features across n samples. We…
Bayesian Structured Sparsity from Gaussian Fields
Barbara E. Engelhardt, Ryan P. Adams
Substantial research on structured sparsity has contributed to analysis of many different applications. However, there have been few Bayesian procedures among this work. Here, we d…
Expandable Factor Analysis
Sanvesh Srivastava, Barbara E. Engelhardt, David B. Dunson
Bayesian sparse factor models have proven useful for characterizing dependence in multivariate data, but scaling computation to large numbers of samples and dimensions is problemat…
Posterior predictive checks to quantify lack-of-fit in admixture models of latent population structure
David Mimno, David M Blei, Barbara E Engelhardt
Admixture models are a ubiquitous approach to capture latent population structure in genetic samples. Despite the widespread application of admixture models, little thought has bee…