A neural architecture that runs gradient matching before covariate matching, using a known anchor variable, is proposed for treatment effect estimation; the supporting theorem's proof has a critical gap.
9 HYPERPARAMETERS We describe the various hyperparameters used in all our experiments here for all the methods which have been used for the comparison of results
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Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
A neural architecture that runs gradient matching before covariate matching, using a known anchor variable, is proposed for treatment effect estimation; the supporting theorem's proof has a critical gap.