mlsanityData to 7 Oct 2026

Towards Clarifying the Theory of the Deconfounder

arXiv 2003.04948 ↗First posted 10 Mar 2020stat.ML cs.LGcited by 9

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Abstract (arXiv)

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.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Mar 2020.

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Citing papers per year: 2021: 2; 2022: 4; 2023: 2; 2024: 1.

9 papers.