The Counterfactual $\chi$-GAN

Averitt Amelia J.
Averitt Amelia J.
Vanitchanant Natnicha
Vanitchanant Natnicha
Cited by: 0|Views13

Abstract:

Causal inference often relies on the counterfactual framework, which requires that treatment assignment is independent of the outcome, known as strong ignorability. Approaches to enforcing strong ignorability in causal analyses of observational data include weighting and matching methods. Effect estimates, such as the average treatment ...More

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