4 papers
Hierarchical Random Measures without Tables
Marta Catalano, Claudio Del Sole
The hierarchical Dirichlet process is the cornerstone of Bayesian nonparametric multilevel models. Its generative model can be described through a set of latent variables, commonly…
Measures of Dependence based on Wasserstein distances
Marta Catalano, Hugo Lavenant
Measuring dependence between random variables is a fundamental problem in Statistics, with applications across diverse fields. While classical measures such as Pearson's correlatio…
Measuring Partial Exchangeability with Reproducing Kernel Hilbert Spaces
Marta Catalano, Hugo Lavenant, Francesco Mascari
In Bayesian multilevel models, the data are structured in interconnected groups, and their posteriors borrow information from one another due to prior dependence between latent par…
Merging Rate of Opinions via Optimal Transport on Random Measures
Marta Catalano, Hugo Lavenant
Random measures provide flexible parameters for Bayesian nonparametric models. Given two different priors for a random measure, we develop a natural framework to investigate the ra…