207 citations · 570 across the 16 of their papers we have counts for
9 papers · 1 filter
On the Stability of General Bayesian Inference
Jack Jewson, Jim Q. Smith, Chris Holmes
We study the stability of posterior predictive inferences to the specification of the likelihood model and perturbations of the data generating process. In modern big data analyses…
Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior
Anna Menacher, Thomas E. Nichols, Chris Holmes +1
Neural demyelination and brain damage accumulated in white matter appear as hyperintense areas on T2-weighted MRI scans in the form of lesions. Modeling binary images at the popula…
Conformal Bayesian Computation
Edwin Fong, Chris Holmes
We develop scalable methods for producing conformal Bayesian predictive intervals with finite sample calibration guarantees. Bayesian posterior predictive distributions, $p(y \mid…
Martingale posterior distributions
Edwin Fong, Chris Holmes, Stephen G. Walker
The prior distribution on parameters of a sampling distribution is the usual starting point for Bayesian uncertainty quantification. In this paper, we present a different perspecti…
Better together? Statistical learning in models made of modules
Pierre E. Jacob, Lawrence M. Murray, Chris C. Holmes +1
In modern applications, statisticians are faced with integrating heterogeneous data modalities relevant for an inference, prediction, or decision problem. In such circumstances, it…
Scalable Bayesian nonparametric measures for exploring pairwise dependence via Dirichlet Process Mixtures
Sarah Filippi, Chris C. Holmes, Luis E. Nieto-Barajas
In this article we propose novel Bayesian nonparametric methods using Dirichlet Process Mixture (DPM) models for detecting pairwise dependence between random variables while accoun…