treatment effect estimation
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Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators
Second, they lack a specific focus on selecting a robust CA TE estimator.
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OnInductiveBiasesforHeterogeneousTreatment EffectEstimation
At this point, a range of sophisticated solutions exist which reduce the effect of confounding by balancing the covariate space [3, 4], importance weighting [11, 12, 13, 14] or propensity drop-out [15].
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