10 citations · 21 across the 8 of their papers we have counts for
5 papers · 1 filter
Bayesian Mixture Models for Histograms: with Applications to Large Datasets
Richard L. Warr, Fernando A. Quintana, Alessandra Guglielmi +1
In many real-world scenarios, especially those involving privacy constraints or data summarization, data are available only in aggregated forms, such as histograms or frequency tab…
Clustering blood donors via mixtures of product partition models with covariates
Raffaele Argiento, Riccardo Corradin, Alessandra Guglielmi +1
Motivated by the problem of accurately predicting gap times between successive blood donations, we present here a general class of Bayesian nonparametric models for clustering. The…
MCMC computations for Bayesian mixture models using repulsive point processes
Mario Beraha, Raffaele Argiento, Jesper Møller +1
Repulsive mixture models have recently gained popularity for Bayesian cluster detection. Compared to more traditional mixture models, repulsive mixture models produce a smaller num…
Bayesian nonparametric temporal dynamic clustering via autoregressive Dirichlet priors
Maria De Iorio, Stefano Favaro, Alessandra Guglielmi +1
In this paper we consider the problem of dynamic clustering, where cluster memberships may change over time and clusters may split and merge over time, thus creating new clusters a…
Determinantal point process mixtures via spectral density approach
Ilaria Bianchini, Alessandra Guglielmi, Fernando A. Quintana
We consider mixture models where location parameters are a priori encouraged to be well separated. We explore a class of determinantal point process (DPP) mixture models, which pro…