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Found 3 papers, 2 papers with code
Targeting Learning: Robust Statistics for Reproducible Research
Targeted Learning is a subfield of statistics that unifies advances in causal inference, machine learning and statistical theory to help answer scientifically impactful questions with statistical confidence.
A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology
The widespread availability of high-dimensional biological data has made the simultaneous screening of many biological characteristics a central problem in computational biology and allied sciences.
Methodology
Data-adaptive statistics for multiple hypothesis testing in high-dimensional settings
Current statistical inference problems in areas like astronomy, genomics, and marketing routinely involve the simultaneous testing of thousands -- even millions -- of null hypotheses.
