Variational Bayes (VB) is a common strategy for approximate Bayesian inference, but simple
methods are only available for specific classes of models including, in particular …

Spatial Product Partition Models Page 1 Bayesian Analysis (2016) 11, Number 1, pp. 265–298
Spatial Product Partition Models ∗ Garritt L. Page † and Fernando A. Quintana ‡ Abstract …

A nonparametric Bayesian contextual focused topic model (cFTM) is proposed. The cFTM
infers a sparse (" focused") set of topics for each document, while also leveraging contextual …

Owing to the tremendous diversity and complexity of data in today's world, some new
insights for clustering on data are often desired by developing an alternative to the existing …

There is a growing interest in learning how the distribution of a response variable changes
with a set of observed predictors. Bayesian nonparametric dependent mixture models …

Relational model learning is useful for numerous practical applications. Many algorithms
have been proposed in recent years to tackle this important yet challenging problem …

Most existing image denoising methods assume to know the noise distributions, eg,
Gaussian noise, impulse noise, etc. However, in practice the noise distribution is usually …

Predicting insurance losses is an eternal focus of actuarial science in the insurance sector.
Due to the existence of complicated features such as skewness, heavy tail, and multi …

The increasing prevalence of network data in a vast variety of fields and the need to extract
useful information out of them have spurred fast developments in related models and …

For exchangeable data, mixture models are an extremely useful tool for density estimation
due to their attractive balance between smoothness and flexibility. When additional …