Estimation of Individual Treatment Effect in Latent Confounder Models via Adversarial Learning

Causality: Models, Reasoning, and Inference

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Earlier work this paper cites.

The costs of low birth weight

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Earlier work this paper cites.

Introducing new data on gestation-specific infant mortality among babies born in 2005 in england and wales

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Earlier work this paper cites.

Nonparametric tests for treatment effect heterogeneity

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Earlier work this paper cites.

Identifiability of parameters in latent structure models with many observed variables

Elizabeth S Allman, Catherine Matias, and John A Rhodes · 2009

Earlier work this paper cites.

On measurement bias in causal inference

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Earlier work this paper cites.

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Bart: Bayesian additive regression trees

Hugh A. Chipman, Edward I. George, and Robert E. McCulloch · 2010

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Bayesian nonparametric modeling for causal inference

Jennifer L. Hill · 2011

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Outcomes in preterm infants

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Bayesian inference of individualized treatment effects using multi-task gaussian processes

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