2 papers
stat.ME2023
Scalable Causal Structure Learning via Amortized Conditional Independence Testing
James Leiner, Brian Manzo, Aaditya Ramdas +1
Controlling false positives (Type I errors) through statistical hypothesis testing is a foundation of modern scientific data analysis. Existing causal structure discovery algorithm…
stat.ML2021
Normalizing Flows for Knockoff-free Controlled Feature Selection
Derek Hansen, Brian Manzo, Jeffrey Regier
Controlled feature selection aims to discover the features a response depends on while limiting the false discovery rate (FDR) to a predefined level. Recently, multiple deep-learni…