Detection of Unobserved Common Causes based on NML Code in Discrete,
Mixed, and Continuous Variables
Detection of Unobserved Common Causes based on NML Code in Discrete,
Mixed, and Continuous Variables
Causal discovery in the presence of unobserved common causes from observational data only is a crucial but challenging problem. We categorize all possible causal relationships between two random variables into the following four categories and aim to identify one from observed data: two cases in which either of the direct …