  Causal Discovery methods aim to identify a DAG structure that represents
causal relationships from observational data. In this article, we stress that
it is important to test such methods for robustness in practical settings. As
our main example, we analyze the NOTEARS method, for which we demonstrate a
lack of scale-invariance. We show that NOTEARS is a method that aims to
identify a parsimonious DAG from the data that explains the residual variance.
We conclude that NOTEARS is not suitable for identifying truly causal
relationships from the data.
