Our paper on “Constraint-based causal discovery with mixed data” is finally out!

We developed new approaches for co-analyzing categorical and continuous data in causal discovery algorithms. Specifically, we devised new conditional independence tests for mixed data that can be directly embedded in constraint-based algorithms like PC and FCI. Check out the open-access paper or the readcube version