collaborators

9 papers

math.ST2026

Closed-form solutions to some generalized variational inference problems

Hien Duy Nguyen, Jacob Westerhout

The Donsker--Varadhan formula characterizes the ordinary Bayesian posterior as the solution of an unrestricted -regularized variational problem. Generalized variationa…

math.ST2026

Bounds on the Number of Modes of a Gaussian Mixture Density

Hien Duy Nguyen

We derive explicit upper bounds for the number of nondegenerate critical points of a -component Gaussian mixture density in , and the number of modes when the moda…

stat.ME2026

Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation

Rafael Mouallem Rosa, Julyan Arbel, Hien Duy Nguyen

We introduce a general framework that extends Bayesian inference by allowing the researcher to explicitly encode confidence in each source of uncertainty within the model. This mec…

stat.ME2026

Shifted asymmetric Laplace mixtures of experts

Sphiwe B. Skhosana, Hien Duy Nguyen

Mixtures of experts (MoE) models provide a flexible framework for modelling heterogeneity in data for regression and model-based clustering and classification. MoE models for regre…

math.ST2026

Characterisations of Kullback--Leibler approximation by finite Gaussian mixtures

Hien Duy Nguyen

We study the Kullback--Leibler (KL) divergence approximation theory of Gaussian mixture models (GMMs) by isolating an abstract mechanism behind several necessary-and-sufficient sta…

math.ST2026

Consistency of the Bayesian Information Criterion for Model Selection in Exploratory Factor Analysis

Hien Duy Nguyen, Kei Hirose

We study model selection by the Bayesian information criterion (BIC) in fixed-dimensional exploratory factor analysis over a fixed finite family of compact covariance classes. Our…