  Wang and Blei (2019) studies multiple causal inference and proposes the
deconfounder algorithm. The paper discusses theoretical requirements and
presents empirical studies. Several refinements have been suggested around the
theory of the deconfounder. Among these, Imai and Jiang clarified the
assumption of "no unobserved single-cause confounders." Using their assumption,
this paper clarifies the theory. Furthermore, Ogburn et al. (2020) proposes
counterexamples to the theory. But the proposed counterexamples do not satisfy
the required assumptions.
