4 papers
Bayesian Multiple Multivariate Density-Density Regression
Khai Nguyen, Yang Ni, Peter Mueller
We propose the first approach for multiple multivariate density-density regression (MDDR), making it possible to consider the regression of a multivariate density-valued response o…
Bayesian Multivariate Density-Density Regression
Khai Nguyen, Yang Ni, Peter Mueller
We introduce a novel and scalable Bayesian framework for multivariate-density-density regression (DDR), designed to model relationships between multivariate distributions. Our appr…
Summarizing Bayesian Nonparametric Mixture Posterior -- Sliced Optimal Transport Metrics for Gaussian Mixtures
Khai Nguyen, Peter Mueller
Existing methods to summarize posterior inference for mixture models focus on identifying a point estimate of the implied random partition for clustering, with density estimation a…
DPGLM: A Semiparametric Bayesian GLM with Inhomogeneous Normalized Random Measures
Entejar Alam, Paul J. Rathouz, Peter Mueller
We introduce a novel varying-weight dependent Dirichlet process (DDP) model that extends a recently developed semi-parametric generalized linear model (SPGLM) by adding a nonparame…