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math.ST2026
Semi-knockoffs: a model-agnostic conditional independence testing method with finite-sample guarantees
Angel Reyero-Lobo, Bertrand Thirion, Pierre Neuvial
Conditional independence testing (CIT) is essential for reliable scientific discovery. It prevents spurious findings and enables controlled feature selection. Recent CIT methods ha…
math.ST2026★ 1 cited
Conditional Feature Importance revisited: Double Robustness, Efficiency and Inference
Angel Reyero-Lobo, Pierre Neuvial, Bertrand Thirion
Conditional Feature Importance (CFI) is a classical variable importance measure that accounts for the relationship between the studied feature and the others. However, CFI has not…
math.ST2025
Cluster Size Matters: A Comparative Study of Notip and pARI for Post Hoc Inference in fMRI
Nils Peyrouset, Pierre Neuvial, Bertrand Thirion
All Resolutions Inference (ARI) is a post hoc inference method for functional Magnetic Resonance Imaging (fMRI) data analysis that provides valid lower bounds on the proportion of…