51 citations · 87 across the 14 of their papers we have counts for
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cs.LG2022
Explaining the root causes of unit-level changes
Kailash Budhathoki, George Michailidis, Dominik Janzing
Existing methods of explainable AI and interpretable ML cannot explain change in the values of an output variable for a statistical unit in terms of the change in the input values…
stat.ME2022★ 51 cited
DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models
Patrick Blöbaum, Peter Götz, Kailash Budhathoki +2
We present DoWhy-GCM, an extension of the DoWhy Python library, which leverages graphical causal models. Unlike existing causality libraries, which mainly focus on effect estimatio…