1 citations · 1 across the 1 of their papers we have counts for
8 papers
A Bayesian time-varying random partition model for large spatio-temporal datasets
Giulio Beltramin, Andrea Cremaschi, Annalisa Cadonna +2
Spatio-temporal areal data can be seen as a collection of time series which are spatially correlated, according to a specific neighbouring structure. Motivated by a dataset on mobi…
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…
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…
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…