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Found 2 papers, 2 papers with code
Efficient Estimation and Evaluation of Prediction Rules in Semi-Supervised Settings under Stratified Sampling
In step II, we augment the initial imputations to ensure the consistency of the resulting estimators regardless of the specification of the prediction model or the imputation model.
Fast and Powerful Conditional Randomization Testing via Distillation
We propose the distilled CRT, a novel approach to using state-of-the-art machine learning algorithms in the CRT while drastically reducing the number of times those algorithms need to be run, thereby taking advantage of their power and the CRT's statistical guarantees without suffering the usual computational expense.
Methodology
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