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math.ST2025
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…
math.ST2025
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…
math.ST2025
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…