research
          
      
      ∙
      06/28/2023
    Joint structure learning and causal effect estimation for categorical graphical models
We consider a a collection of categorical random variables. Of special i...
          
            research
          
      
      ∙
      06/01/2022
    Bayesian sample size determination for causal discovery
Graphical models based on Directed Acyclic Graphs (DAGs) are widely used...
          
            research
          
      
      ∙
      01/28/2022
    BCDAG: An R package for Bayesian structure and Causal learning of Gaussian DAGs
Directed Acyclic Graphs (DAGs) provide a powerful framework to model cau...
          
            research
          
      
      ∙
      06/06/2021
    Bayesian graphical modelling for heterogeneous causal effects
Our motivation stems from current medical research aiming at personalize...
          
            research
          
      
      ∙
      02/12/2021
    Equivalence class selection of categorical graphical models
Learning the structure of dependence relations between variables is a pe...
          
            research
          
      
      ∙
      09/10/2020