Web: http://arxiv.org/abs/2201.12003

Jan. 31, 2022, 2:11 a.m. | Federico Castelletti, Alessandro Mascaro

cs.LG updates on arXiv.org arxiv.org

Directed Acyclic Graphs (DAGs) provide a powerful framework to model causal
relationships among variables in multivariate settings; in addition, through
the do-calculus theory, they allow for the identification and estimation of
causal effects between variables also from pure observational data. In this
setting, the process of inferring the DAG structure from the data is referred
to as causal structure learning or causal discovery. We introduce BCDAG, an R
package for Bayesian causal discovery and causal effect estimation from
Gaussian observational …

arxiv bayesian learning ml package

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