4 papers
Binned semiparametric Bayesian networks for efficient kernel density estimation
Rafael Sojo, Javier DÃaz-Rozo, Concha Bielza +1
This paper introduces a new type of probabilistic semiparametric model that takes advantage of data binning to reduce the computational cost of kernel density estimation in nonpara…
Optimal Transport Group Counterfactual Explanations
Enrique Valero-Leal, Bernd Bischl, Pedro Larrañaga +2
Group counterfactual explanations find a set of counterfactual instances to explain a group of input instances contrastively. However, existing methods either (i) optimize counterf…
Actionable Counterfactual Explanations Using Bayesian Networks and Path Planning with Applications to Environmental Quality Improvement
Enrique Valero-Leal, Pedro Larrañaga, Concha Bielza
Counterfactual explanations study what should have changed in order to get an alternative result, enabling end-users to understand machine learning mechanisms with counterexamples.…
Bandwidth Selectors on Semiparametric Bayesian Networks
Victor Alejandre, Concha Bielza, Pedro Larrañaga
Semiparametric Bayesian networks (SPBNs) integrate parametric and non-parametric probabilistic models, offering flexibility in learning complex data distributions from samples. In…