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Towards Clarifying the Theory of the Deconfounder

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arxiv 2003.04948 v1 pith:7EVEHGPP submitted 2020-03-10 stat.ML cs.LG

Towards Clarifying the Theory of the Deconfounder

classification stat.ML cs.LG
keywords theorydeconfounderassumptioncounterexamplesproposesstudiesalgorithmaround
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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