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stat.ME2026
Empirically Calibrated Conditional Independence Tests
Milleno Pan, Antoine de Mathelin, Wesley Tansey
Conditional independence tests (CIT) are widely used for causal discovery and feature selection. Even with false discovery rate (FDR) control procedures, they often fail to provide…
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…