Varoquaux, Gael

34 publications

AISTATS 2025 Decision from Suboptimal Classifiers: Excess Risk Pre- and Post-Calibration Alexandre Perez-Lebel, Gael Varoquaux, Sanmi Koyejo, Matthieu Doutreligne, Marine Le Morvan

ICLR 2025 Imputation for Prediction: Beware of Diminishing Returns. Marine Le Morvan, Gael Varoquaux

TMLR 2025 Retrieve, Merge, Predict: Augmenting Tables with Data Lakes Riccardo Cappuzzo, Aimee Coelho, Félix Lefebvre, Paolo Papotti, Gaël Varoquaux

NeurIPS 2025 Scalable Feature Learning on Huge Knowledge Graphs for Downstream Machine Learning Félix Lefebvre, Gaël Varoquaux

AISTATS 2025 Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks Julie Alberge, Vincent Maladiere, Olivier Grisel, Judith Abécassis, Gael Varoquaux

ICML 2025 TabICL: A Tabular Foundation Model for In-Context Learning on Large Data Jingang Qu, David Holzmüller, Gaël Varoquaux, Marine Le Morvan

TMLR 2025 Table Foundation Models: On Knowledge Pre-Training for Tabular Learning Myung Jun Kim, Félix Lefebvre, Gaëtan Brison, Alexandre Perez-Lebel, Gaël Varoquaux

ICML 2024 CARTE: Pretraining and Transfer for Tabular Learning Myung Jun Kim, Leo Grinsztajn, Gael Varoquaux

ICLR 2023 Beyond Calibration: Estimating the Grouping Loss of Modern Neural Networks Alexandre Perez-Lebel, Marine Le Morvan, Gael Varoquaux

NeurIPSW 2023 Modeling String Entries for Tabular Data Prediction: Do We Need Big Large Language Models? Leo Grinsztajn, Myung Jun Kim, Edouard Oyallon, Gael Varoquaux

MLJ 2023 Relational Data Embeddings for Feature Enrichment with Background Information Alexis Cvetkov-Iliev, Alexandre Allauzen, Gaël Varoquaux

NeurIPS 2022 Why Do Tree-Based Models Still Outperform Deep Learning on Typical Tabular Data? Leo Grinsztajn, Edouard Oyallon, Gael Varoquaux

AAAI 2021 A Lightweight Neural Model for Biomedical Entity Linking Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek

NeurIPSW 2021 AI as Statistical Methods for Imperfect Theories Gael Varoquaux

NeurIPS 2021 What’s a Good Imputation to Predict with Missing Values? Marine Le Morvan, Julie Josse, Erwan Scornet, Gael Varoquaux

AISTATS 2020 Linear Predictor on Linearly-Generated Data with Missing Values: Non Consistency and Solutions Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gael Varoquaux

NeurIPS 2020 NeuMiss Networks: Differentiable Programming for Supervised Learning with Missing Values. Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gael Varoquaux

NeurIPS 2019 Comparing Distributions: $\ell_1$ Geometry Improves Kernel Two-Sample Testing Meyer Scetbon, Gael Varoquaux

ICML 2019 Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data Sergul Aydore, Bertrand Thirion, Gael Varoquaux

NeurIPS 2019 Manifold-Regression to Predict from MEG/EEG Brain Signals Without Source Modeling David Sabbagh, Pierre Ablin, Gael Varoquaux, Alexandre Gramfort, Denis A. Engemann

NeurIPSW 2019 What’s in a Functional Brain Parcellation? Gaël Varoquaux, Kamalakar Dadi, Arthur Mensch

MLJ 2018 Similarity Encoding for Learning with Dirty Categorical Variables Patricio Cerda, Gaël Varoquaux, Balázs Kégl

NeurIPS 2017 Learning Neural Representations of Human Cognition Across Many fMRI Studies Arthur Mensch, Julien Mairal, Danilo Bzdok, Bertrand Thirion, Gael Varoquaux

ICML 2017 Learning to Discover Sparse Graphical Models Eugene Belilovsky, Kyle Kastner, Gael Varoquaux, Matthew B. Blaschko

ICLR 2017 Learning to Discover Sparse Graphical Models Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko

ICML 2016 Dictionary Learning for Massive Matrix Factorization Arthur Mensch, Julien Mairal, Bertrand Thirion, Gael Varoquaux

NeurIPS 2016 Learning Brain Regions via Large-Scale Online Structured Sparse Dictionary Learning Elvis Dohmatob, Arthur Mensch, Gael Varoquaux, Bertrand Thirion

NeurIPS 2016 Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity Eugene Belilovsky, Gaël Varoquaux, Matthew B Blaschko

MLJ 2015 Convex Relaxations of Penalties for Sparse Correlated Variables with Bounded Total Variation Eugene Belilovsky, Andreas Argyriou, Gaël Varoquaux, Matthew B. Blaschko

NeurIPS 2015 Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data Danilo Bzdok, Michael Eickenberg, Olivier Grisel, Bertrand Thirion, Gael Varoquaux

NeurIPS 2013 Mapping Paradigm Ontologies to and from the Brain Yannick Schwartz, Bertrand Thirion, Gael Varoquaux

ICML 2012 Small-Sample Brain Mapping: Sparse Recovery on Spatially Correlated Designs with Randomization and Clustering Gaël Varoquaux, Alexandre Gramfort, Bertrand Thirion

MLOSS 2011 Scikit-Learn: Machine Learning in Python Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Édouard Duchesnay

NeurIPS 2010 Brain Covariance Selection: Better Individual Functional Connectivity Models Using Population Prior Gael Varoquaux, Alexandre Gramfort, Jean-baptiste Poline, Bertrand Thirion