Reviews: The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data

Although the paper is a good attempt at this space, and the messages should be echoed wide in the community, the paper could benefit from various improvements. Specifically, I am unsure if some of the performed experiments are supportive of the claims made in the paper. Details are as follows: Line 79: Authors discuss evaluating interventional distribution. But if the structure learning part is correct, then the learned distribution will also be correct as long as the parameterization is known or for discrete variables. After reading the rest, I guess authors are concerned about approximately learning the structure, and then depending on whether strong or weak edges are omitted can be determined by such an evaluation.