9 citations · 13 across the 19 of their papers we have counts for
6 papers · 1 filter
Bayesian Causal Effect Estimation for Categorical Data using Staged Tree Models
Andrea Cremaschi, Manuele Leonelli, Gherardo Varando
We propose a fully Bayesian approach for causal inference with multivariate categorical data based on staged tree models, a class of probabilistic graphical models capable of repre…
Latent Modularity in Multi-View Data
Andrea Cremaschi, Maria De Iorio, Garritt Page +1
In this article, we consider the problem of clustering multi-view data, that is, information associated to individuals that form heterogeneous data sources (the views). We adopt a…
Repulsive mixtures via the sparsity-inducing partition prior
Alexander Mozdzen, Timothy Wertz, Maria De Iorio +3
We introduce a novel prior distribution for modelling the weights in mixture models based on a generalisation of the Dirichlet distribution, the Selberg Dirichlet distribution. Thi…
Understanding support for AI regulation: A Bayesian network perspective
Andrea Cremaschi, Dae-Jin Lee, Manuele Leonelli
As artificial intelligence (AI) becomes increasingly embedded in public and private life, understanding how citizens perceive its risks, benefits, and regulatory needs is essential…
Will AI Take My Job? Evolving Perceptions of Automation and Labor Risk in Latin America
Andrea Cremaschi, Dae-Jin Lee, Manuele Leonelli
As artificial intelligence and robotics increasingly reshape the global labor market, understanding public perceptions of these technologies becomes critical. We examine how these…
A Bayesian semi-parametric model for longitudinal growth and appetite phenotypes in children
Andrea Cremaschi, Beatrice Franzolini, Maria De Iorio +8
This study develops a Bayesian semi-parametric model to examine the longitudinal growth and appetite phenotypes in children from the GUSTO cohort, with a focus on understanding the…