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FDP control in multivariate linear models using the bootstrap
Samuel Davenport, Bertrand Thirion, Pierre Neuvial
In this article we develop a method for performing post hoc inference of the False Discovery Proportion (FDP) over multiple contrasts of interest in the multivariate linear model.…
Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps
Alexandre Pasquiou, Yair Lakretz, John Hale +2
Neural Language Models (NLMs) have made tremendous advances during the last years, achieving impressive performance on various linguistic tasks. Capitalizing on this, studies in ne…
Aligning individual brains with Fused Unbalanced Gromov-Wasserstein
Alexis Thual, Huy Tran, Tatiana Zemskova +4
Individual brains vary in both anatomy and functional organization, even within a given species. Inter-individual variability is a major impediment when trying to draw generalizabl…
A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension
Binh T. Nguyen, Bertrand Thirion, Sylvain Arlot
Identifying the relevant variables for a classification model with correct confidence levels is a central but difficult task in high-dimension. Despite the core role of sparse logi…
Notip: Non-parametric True Discovery Proportion control for brain imaging
Alexandre Blain, Bertrand Thirion, Pierre Neuvial
Cluster-level inference procedures are widely used for brain mapping. These methods compare the size of clusters obtained by thresholding brain maps to an upper bound under the glo…