56 citations · 178 across the 22 of their papers we have counts for
Showing stat.COShow all
3 papers · 1 filter
stat.CO2024
Exact discovery is polynomial for certain sparse causal Bayesian networks
Felix L. Rios, Giusi Moffa, Jack Kuipers
Causal Bayesian networks are widely used tools for summarising the dependencies between variables and elucidating their putative causal relationships. By restricting the search to…
stat.CO2021
Bayesian structure learning and sampling of Bayesian networks with the R package BiDAG
Polina Suter, Jack Kuipers, Giusi Moffa +1
The R package BiDAG implements Markov chain Monte Carlo (MCMC) methods for structure learning and sampling of Bayesian networks. The package includes tools to search for a maximum…
stat.CO2012★ 20 cited
Uniform random generation of large acyclic digraphs
Jack Kuipers, Giusi Moffa
Directed acyclic graphs are the basic representation of the structure underlying Bayesian networks, which represent multivariate probability distributions. In many practical applic…