activity
20182021
collaborators

5 papers

stat.ME2021

Spatially relaxed inference on high-dimensional linear models

Jérôme-Alexis Chevalier, Tuan-Binh Nguyen, Bertrand Thirion +1

We consider the inference problem for high-dimensional linear models, when covariates have an underlying spatial organization reflected in their correlation. A typical example of s…

stat.ML2020

Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso

Jérôme-Alexis Chevalier, Alexandre Gramfort, Joseph Salmon +1

Detecting where and when brain regions activate in a cognitive task or in a given clinical condition is the promise of non-invasive techniques like magnetoencephalography (MEG) or…

math.ST2020

Aggregation of Multiple Knockoffs

Tuan-Binh Nguyen, Jérôme-Alexis Chevalier, Bertrand Thirion +1

We develop an extension of the Knockoff Inference procedure, introduced by Barber and Candes (2015). This new method, called Aggregation of Multiple Knockoffs (AKO), addresses the…

math.ST2019

ECKO: Ensemble of Clustered Knockoffs for multivariate inference on fMRI data

Tuan-Binh Nguyen, Jérôme-Alexis Chevalier, Bertrand Thirion

Continuous improvement in medical imaging techniques allows the acquisition of higher-resolution images. When these are used in a predictive setting, a greater number of explanator…

stat.AP2018

Statistical Inference with Ensemble of Clustered Desparsified Lasso

Jérôme-Alexis Chevalier, Joseph Salmon, Bertrand Thirion

Medical imaging involves high-dimensional data, yet their acquisition is obtained for limited samples. Multivariate predictive models have become popular in the last decades to fit…