Gaël Varoquaux

Orcid: 0000-0003-1076-5122

Affiliations:
  • Inria Saclay, Palaiseau, France


According to our database1, Gaël Varoquaux authored at least 158 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Teaching Models To Survive: Proper Scoring Rule and Stochastic Optimization with Competing Risks.
CoRR, 2024

CARTE: pretraining and transfer for tabular learning.
CoRR, 2024

Retrieve, Merge, Predict: Augmenting Tables with Data Lakes.
CoRR, 2024

Reconfidencing LLMs from the Grouping Loss Perspective.
CoRR, 2024

Learning High-Quality and General-Purpose Phrase Representations.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

2023
Relational data embeddings for feature enrichment with background information.
Mach. Learn., February, 2023

Vectorizing string entries for data processing on tables: when are larger language models better?
CoRR, 2023

Confidence intervals for performance estimates in 3D medical image segmentation.
CoRR, 2023

Understanding metric-related pitfalls in image analysis validation.
CoRR, 2023

How to select predictive models for causal inference?
CoRR, 2023

Beyond calibration: estimating the grouping loss of modern neural networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

The Locality and Symmetry of Positional Encodings.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

GLADIS: A General and Large Acronym Disambiguation Benchmark.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

2022
Employee salaries in Texas administrations.
Dataset, January, 2022

Encoding High-Cardinality String Categorical Variables.
IEEE Trans. Knowl. Data Eng., 2022

International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality.
npj Digit. Medicine, 2022

Machine learning for medical imaging: methodological failures and recommendations for the future.
npj Digit. Medicine, 2022

Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery.
NeuroImage, 2022

Why do tree-based models still outperform deep learning on tabular data?
CoRR, 2022

Metrics reloaded: Pitfalls and recommendations for image analysis validation.
CoRR, 2022

Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost.
CoRR, 2022

Benchmarking missing-values approaches for predictive models on health databases.
CoRR, 2022

Analytics on Non-Normalized Data Sources: More Learning, Rather Than More Cleaning.
IEEE Access, 2022

Why do tree-based models still outperform deep learning on typical tabular data?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Imputing Out-of-Vocabulary Embeddings with LOVE Makes LanguageModels Robust with Little Cost.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Extracting representations of cognition across neuroimaging studies improves brain decoding.
PLoS Comput. Biol., 2021

Decoding with confidence: Statistical control on decoder maps.
NeuroImage, 2021

Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction.
CoRR, 2021

Preventing dataset shift from breaking machine-learning biomarkers.
CoRR, 2021

How I failed machine learning in medical imaging - shortcomings and recommendations.
CoRR, 2021

Accounting for Variance in Machine Learning Benchmarks.
CoRR, 2021

What's a good imputation to predict with missing values?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


A Lightweight Neural Model for Biomedical Entity Linking.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.
npj Digit. Medicine, 2020

Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.
NeuroImage, 2020

Fine-grain atlases of functional modes for fMRI analysis.
NeuroImage, 2020

Neumann networks: differential programming for supervised learning with missing values.
CoRR, 2020

NeuMiss networks: differentiable programming for supervised learning with missing values.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Linear predictor on linearly-generated data with missing values: non consistency and solutions.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Recursive Nearest Agglomeration (ReNA): Fast Clustering for Approximation of Structured Signals.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Benchmarking functional connectome-based predictive models for resting-state fMRI.
NeuroImage, 2019

Population shrinkage of covariance (PoSCE) for better individual brain functional-connectivity estimation.
Medical Image Anal., 2019

Comparing distributions: 𝓁<sub>1</sub> geometry improves kernel two-sample testing.
CoRR, 2019

On the consistency of supervised learning with missing values.
CoRR, 2019

Comparing distributions: 퓁<sub>1</sub> geometry improves kernel two-sample testing.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Manifold-regression to predict from MEG/EEG brain signals without source modeling.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Stochastic Subsampling for Factorizing Huge Matrices.
IEEE Trans. Signal Process., 2018

Atlases of cognition with large-scale human brain mapping.
PLoS Comput. Biol., 2018

Cross-validation failure: Small sample sizes lead to large error bars.
NeuroImage, 2018

Decoding fMRI activity in the time domain improves classification performance.
NeuroImage, 2018

FReM - Scalable and stable decoding with fast regularized ensemble of models.
NeuroImage, 2018

Similarity encoding for learning with dirty categorical variables.
Mach. Learn., 2018

Computational and informatics advances for reproducible data analysis in neuroimaging.
CoRR, 2018

Approximate message-passing for convex optimization with non-separable penalties.
CoRR, 2018

Extracting Universal Representations of Cognition across Brain-Imaging Studies.
CoRR, 2018

Using Feature Grouping as a Stochastic Regularizer for High-Dimensional Noisy Data.
CoRR, 2018

Controlling a confound in predictive models with a test set minimizing its effect.
Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018

Text to Brain: Predicting the Spatial Distribution of Neuroimaging Observations from Text Reports.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017
BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.
PLoS Comput. Biol., 2017

Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines.
NeuroImage, 2017

Joint prediction of multiple scores captures better individual traits from brain images.
NeuroImage, 2017

Predicting brain-age from multimodal imaging data captures cognitive impairment.
NeuroImage, 2017

Seeing it all: Convolutional network layers map the function of the human visual system.
NeuroImage, 2017

Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example.
NeuroImage, 2017

Subsampling Enables Fast Factorisation of Huge Matrices into Sparse Signals.
ERCIM News, 2017

Convolutional Network Layers Map the Function of the Human Visual Cortex.
ERCIM News, 2017

Multi-output predictions from neuroimaging: assessing reduced-rank linear models.
Proceedings of the 2017 International Workshop on Pattern Recognition in Neuroimaging, 2017

Towards a faster randomized parcellation based inference.
Proceedings of the 2017 International Workshop on Pattern Recognition in Neuroimaging, 2017

Learning Neural Representations of Human Cognition across Many fMRI Studies.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Population-Shrinkage of Covariance to Estimate Better Brain Functional Connectivity.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging.
Proceedings of the Information Processing in Medical Imaging, 2017

Learning to Discover Sparse Graphical Models.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Transport on Riemannian Manifold for Connectivity-Based Brain Decoding.
IEEE Trans. Medical Imaging, 2016

Formal Models of the Network Co-occurrence Underlying Mental Operations.
PLoS Comput. Biol., 2016

NeuroVault.org: A repository for sharing unthresholded statistical maps, parcellations, and atlases of the human brain.
NeuroImage, 2016

Exploring the anatomical encoding of voice with a mathematical model of the vocal system.
NeuroImage, 2016

Transmodal Learning of Functional Networks for Alzheimer's Disease Prediction.
IEEE J. Sel. Top. Signal Process., 2016

Compressed Online Dictionary Learning for Fast fMRI Decomposition.
CoRR, 2016

Social-sparsity brain decoders: faster spatial sparsity.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

Fast brain decoding with random sampling and random projections.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

Comparing functional connectivity based predictive models across datasets.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

Learning brain regions via large-scale online structured sparse dictionary learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Compressed online dictionary learning for fast resting-state fMRI decomposition.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

Dictionary Learning for Massive Matrix Factorization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Local Q-linear convergence and finite-time active set identification of ADMM on a class of penalized regression problems.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2015
Scikit-learn: Machine Learning Without Learning the Machinery.
GetMobile Mob. Comput. Commun., 2015

Robust regression for large-scale neuroimaging studies.
NeuroImage, 2015

Convex relaxations of penalties for sparse correlated variables with bounded total variation.
Mach. Learn., 2015

NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain.
Frontiers Neuroinformatics, 2015

FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging.
CoRR, 2015

Fast clustering for scalable statistical analysis on structured images.
CoRR, 2015

Improving Sparse Recovery on Structured Images with Bagged Clustering.
Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015

Speeding-Up Model-Selection in Graphnet via Early-Stopping and Univariate Feature-Screening.
Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015

Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer's Disease.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

Grouping Total Variation and Sparsity: Statistical Learning with Segmenting Penalties.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

2014
Group-PCA for very large fMRI datasets.
NeuroImage, 2014

Randomized parcellation based inference.
NeuroImage, 2014

Generic Machine Learning Pattern for Neuroimaging-Genetic Studies in the Cloud.
Frontiers Neuroinformatics, 2014

Machine learning for neuroimaging with scikit-learn.
Frontiers Neuroinformatics, 2014

Region segmentation for sparse decompositions: better brain parcellations from rest fMRI.
CoRR, 2014

Benchmarking solvers for TV-ℓ1 least-squares and logistic regression in brain imaging.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

Principal Component Regression Predicts Functional Responses across Individuals.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

Deriving a Multi-subject Functional-Connectivity Atlas to Inform Connectome Estimation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

Transport on Riemannian Manifold for Functional Connectivity-Based Classification.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

2013
A Framework for Inter-Subject Prediction of Functional Connectivity From Structural Networks.
IEEE Trans. Medical Imaging, 2013

Learning and comparing functional connectomes across subjects.
NeuroImage, 2013

Publishing scientific software matters.
J. Comput. Sci., 2013

Mapping cognitive ontologies to and from the brain.
CoRR, 2013

API design for machine learning software: experiences from the scikit-learn project.
CoRR, 2013

A Comparison of Metrics and Algorithms for Fiber Clustering.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Identifying Predictive Regions from fMRI with TV-L1 Prior.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Robust Group-Level Inference in Neuroimaging Genetic Studies.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Hemodynamic Estimation Based on Consensus Clustering.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Mapping paradigm ontologies to and from the brain.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Implications of Inconsistencies between fMRI and dMRI on Multimodal Connectivity Estimation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

Extracting Brain Regions from Rest fMRI with Total-Variation Constrained Dictionary Learning.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

Cohort-Level Brain Mapping: Learning Cognitive Atoms to Single Out Specialized Regions.
Proceedings of the Information Processing in Medical Imaging, 2013

A Novel Sparse Group Gaussian Graphical Model for Functional Connectivity Estimation.
Proceedings of the Information Processing in Medical Imaging, 2013

2012
Changing computational research. The challenges ahead.
Source Code Biol. Medicine, 2012

A supervised clustering approach for fMRI-based inference of brain states.
Pattern Recognit., 2012

Detecting outliers in high-dimensional neuroimaging datasets with robust covariance estimators.
Medical Image Anal., 2012

PyXNAT: XNAT in Python.
Frontiers Neuroinformatics, 2012

On Spatial Selectivity and Prediction across Conditions with fMRI.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012

Improved Brain Pattern Recovery through Ranking Approaches.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012

Connectivity-informed Sparse Classifiers for fMRI Brain Decoding.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012

Decoding Visual Percepts Induced by Word Reading with fMRI.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012

Improving Accuracy and Power with Transfer Learning Using a Meta-analytic Database.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Learning to Rank from Medical Imaging Data.
Proceedings of the Machine Learning in Medical Imaging - Third International Workshop, 2012

A Novel Sparse Graphical Approach for Multimodal Brain Connectivity Inference.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Non-parametric Density Modeling and Outlier-Detection in Medical Imaging Datasets.
Proceedings of the Machine Learning in Medical Imaging - Third International Workshop, 2012

Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clustering.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Total Variation Regularization for fMRI-Based Prediction of Behavior.
IEEE Trans. Medical Imaging, 2011

Scikit-learn: Machine Learning in Python.
J. Mach. Learn. Res., 2011

The NumPy Array: A Structure for Efficient Numerical Computation.
Comput. Sci. Eng., 2011

Mayavi: 3D Visualization of Scientific Data.
Comput. Sci. Eng., 2011

Total variation regularization for fMRI-based prediction of behaviour
CoRR, 2011

Statistical Learning for Resting-State fMRI: Successes and Challenges.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011

A Comparative Study of Algorithms for Intra- and Inter-subjects fMRI Decoding.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011

Beyond Brain Reading: Randomized Sparsity and Clustering to Simultaneously Predict and Identify.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011

Relating Brain Functional Connectivity to Anatomical Connections: Model Selection.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011

Connectivity-Informed fMRI Activation Detection.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011

Detecting Outlying Subjects in High-Dimensional Neuroimaging Datasets with Regularized Minimum Covariance Determinant.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011

Multifractal analysis of Resting State Networks in functional MRI.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

Multi-subject Dictionary Learning to Segment an Atlas of Brain Spontaneous Activity.
Proceedings of the Information Processing in Medical Imaging, 2011

A Probabilistic Framework to Infer Brain Functional Connectivity from Anatomical Connections.
Proceedings of the Information Processing in Medical Imaging, 2011

2010
A group model for stable multi-subject ICA on fMRI datasets.
NeuroImage, 2010

Mayavi: a package for 3D visualization of scientific data
CoRR, 2010

Brain covariance selection: better individual functional connectivity models using population prior.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Detection of Brain Functional-Connectivity Difference in Post-stroke Patients Using Group-Level Covariance Modeling.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010

Accurate Definition of Brain Regions Position through the Functional Landmark Approach.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010

ICA-based sparse features recovery from FMRI datasets.
Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010

2009
CanICA: Model-based extraction of reproducible group-level ICA patterns from fMRI time series
CoRR, 2009

2008
Agile Computer Control of a Complex Experiment.
Comput. Sci. Eng., 2008


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