63.6k citations · 66.4k across the 51 of their papers we have counts for
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Shared Independent Component Analysis for Multi-Subject Neuroimaging
Hugo Richard, Pierre Ablin, Bertrand Thirion +2
We consider shared response modeling, a multi-view learning problem where one wants to identify common components from multiple datasets or views. We introduce Shared Independent C…
Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction
Marc-Andre Schulz, Bertrand Thirion, Alexandre Gramfort +2
High-quality data accumulation is now becoming ubiquitous in the health domain. There is increasing opportunity to exploit rich data from normal subjects to improve supervised esti…
Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data
Sergul Aydore, Bertrand Thirion, Gael Varoquaux
In many applications where collecting data is expensive, for example neuroscience or medical imaging, the sample size is typically small compared to the feature dimension. It is ch…
Machine Learning for Neuroimaging with Scikit-Learn
Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg +6
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate…
HRF estimation improves sensitivity of fMRI encoding and decoding models
Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion +1
Extracting activation patterns from functional Magnetic Resonance Images (fMRI) datasets remains challenging in rapid-event designs due to the inherent delay of blood oxygen level-…
Improved brain pattern recovery through ranking approaches
Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux +3
Inferring the functional specificity of brain regions from functional Magnetic Resonance Images (fMRI) data is a challenging statistical problem. While the General Linear Model (GL…