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Bertrand Thirion

24 papers · 2009–2025 · 6 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) πŸƒ Academic Marathon (16) 🐝 Cross-Pollinator (11) πŸ† Keyword Champion (3) πŸ—ƒοΈ Keyword Collector (99) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (7) πŸš€ Conference Pioneer πŸ’Ž Century Club (24)

Conferences

NIPS (13) ICML (6) MICCAI (2) AAAI (1) AISTATS (1) JMLR (1)

Top co-authors

Gael Varoquaux (8) Alexandre Gramfort (5) Olivier Grisel (3) Arthur Mensch (3) Pierre Ablin (2) Ahmad CHAMMA (2) Julien Mairal (2) Sylvain Arlot (2) Alexandre Blain (2) Hugo Richard (2)

Research topics

Statistics (1)

Keywords

brain imaging (5) feature selection (3) variable selection (3) statistical inference (3) high-dimensional inference (3) fmri analysis (3) independent component analysis (2) feature grouping (2) dictionary learning (2) variable importance (2) cognitive neuroscience (2) false discovery rate (2) functional connectivity (2) permutation importance (2) multi-task learning (2) functional magnetic resonance imaging (2) high-dimensional datum (2) bayesian inference (1) semi-supervised learning (1) probabilistic modeling (1)

Papers

Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence ICML 2025
False Coverage Proportion Control for Conformal Prediction ICML 2025
Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments AISTATS 2025
Variable Importance in High-Dimensional Settings Requires Grouping AAAI 2024
NeuroConText: Contrastive Text-to-Brain Mapping for Neuroscientific Literature MICCAI 2024
Across-subject ensemble-learning alleviates the need for large samples for fMRI decoding MICCAI 2024
False Discovery Proportion control for aggregated Knockoffs NIPS 2023
Statistically Valid Variable Importance Assessment through Conditional Permutations NIPS 2023
Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps ICML 2022
A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension NIPS 2022
Aligning individual brains with fused unbalanced Gromov Wasserstein NIPS 2022
Shared Independent Component Analysis for Multi-Subject Neuroimaging NIPS 2021
Modeling Shared responses in Neuroimaging Studies through MultiView ICA NIPS 2020
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso NIPS 2020
Aggregation of Multiple Knockoffs ICML 2020
Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data ICML 2019
Learning Neural Representations of Human Cognition across Many fMRI Studies NIPS 2017
Learning brain regions via large-scale online structured sparse dictionary learning NIPS 2016
Dictionary Learning for Massive Matrix Factorization ICML 2016
Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data NIPS 2015
Mapping paradigm ontologies to and from the brain NIPS 2013
Scikit-learn: Machine Learning in Python JMLR 2011
Brain covariance selection: better individual functional connectivity models using population prior NIPS 2010
Discriminative Network Models of Schizophrenia NIPS 2009