1 citations · 1 across the 2 of their papers we have counts for
2 papers
stat.ME2023
Bayesian causal discovery from unknown general interventions
Alessandro Mascaro, Federico Castelletti
We consider the problem of learning causal Directed Acyclic Graphs (DAGs) using combinations of observational and interventional experimental data. Current methods tailored to this…
stat.ML2022★ 1 cited
BCDAG: An R package for Bayesian structure and Causal learning of Gaussian DAGs
Federico Castelletti, Alessandro Mascaro
Directed Acyclic Graphs (DAGs) provide a powerful framework to model causal relationships among variables in multivariate settings; in addition, through the do-calculus theory, the…