G. Varoquaux

发表

Scikit-learn: Machine Learning in Python

Gaël Varoquaux, Bertrand Thirion, Ron Weiss, 2011, J. Mach. Learn. Res..

The NumPy Array: A Structure for Efficient Numerical Computation

Gaël Varoquaux, Stéfan van der Walt, S. Chris Colbert, 2011, Computing in Science & Engineering.

Hyperfrontality and hypoconnectivity during refreshing in schizophrenia

G. Varoquaux, B. Thirion, M. Grillon, 2013, Psychiatry Research: Neuroimaging.

Independent consultant pdf

Gilles Louppe, Gaël Varoquaux, Vlad Niculae, 2013 .

Mayavi: 3D Visualization of Scientific Data

Gaël Varoquaux, Prabhu Ramachandran, G. Varoquaux, 2010, Computing in Science & Engineering.

A supervised clustering approach for fMRI-based inference of brain states

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2011, Pattern Recognit..

Total Variation Regularization Enhances Regression-Based Brain Activity Prediction

G. Varoquaux, A. Gramfort, V. Michel, 2010, 2010 First Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging.

Population modeling with machine learning can enhance measures of mental health

G. Varoquaux, B. Thirion, D. Engemann, 2020, bioRxiv.

Different shades of default mode disturbance in schizophrenia: Subnodal covariance estimation in structure and function

Danielle S Bassett, Danilo Bzdok, Gaël Varoquaux, 2018, Human brain mapping.

Patterns of schizophrenia symptoms: hidden structure in the PANSS questionnaire

G. Varoquaux, B. Thirion, A. Aleman, 2018, Translational Psychiatry.

Prediction and inference diverge in biomedicine: Simulations and real-world data

Danilo Bzdok, Gaël Varoquaux, Bertrand Thirion, 2018, bioRxiv.

University of Groningen Patterns of schizophrenia symptoms

G. Varoquaux, B. Thirion, A. Aleman, 2018 .

International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium

Brett K. Beaulieu-Jones, Jeffrey G. Klann, Robert W. Follett, 2020, npj Digital Medicine.

Connectivity‐based parcellation: Critique and implications

G. Varoquaux, B. Thirion, S. Eickhoff, 2015, Human brain mapping.

Brain‐based ranking of cognitive domains to predict schizophrenia

G. Varoquaux, B. Thirion, O. Grisel, 2019, Human brain mapping.

Brain-based ranking of cognitive domains to predict schizophrenia

G. Varoquaux, B. Thirion, O. Grisel, 2019 .

Light-pulse atom interferometry in microgravity

G. Varoquaux, W. Chaibi, P. Bouyer, 2009, 0903.3284.

Subspecialization within default mode nodes characterized in 10,000 UK Biobank participants

G. Varoquaux, A. Gramfort, B. Thirion, 2018, Proceedings of the National Academy of Sciences.

Spatial vs. Temporal Features in ICA of Resting-State fMRI – A Quantitative and Qualitative Investigation in the Context of Response Inhibition

Yufeng Zang, Gaël Varoquaux, Lixia Tian, 2013, PloS one.

Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping

Gaël Varoquaux, Bertrand Thirion, Lucie Hertz-Pannier, 2018, Scientific Data.

Learning for Massive Matrix Factorization

G. Varoquaux, B. Thirion, J. Mairal, 2017 .

Neuroimaging Research: From Null-Hypothesis Falsification to Out-of-Sample Generalization

Danilo Bzdok, Gaël Varoquaux, Bertrand Thirion, 2017, Educational and psychological measurement.

Sagnac effect in superfluid liquids

G. Varoquaux, E. Varoquaux, 2008 .

Shared endo-phenotypes of default mode dysfunction in attention deficit/hyperactivity disorder and autism spectrum disorder

Danilo Bzdok, Gaël Varoquaux, Bertrand Thirion, 2018, Translational Psychiatry.

Predicting brain-age from multimodal imaging data captures cognitive impairment

Daniel S. Margulies, Julia M. Huntenburg, Leonie Lampe, 2016 .

The Brain Imaging Data Structure, a new format for organizing and describing outputs of neuroimaging experiments

Satrajit S. Ghosh, David B. Keator, Jessica A. Turner, 2016, bioRxiv.

Securing Trustworthy Digital Repositories

G. Varoquaux, A. Gramfort, V. Michel, 2016 .

Atomic sources for long-time-of-flight interferometric inertial sensors

G. Varoquaux, 2008 .

Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging

Bruno Hebling Vieira, G. Varoquaux, A. Gramfort, 2022, Neurobiology of Aging.

Centering inclusivity in the design of online conferences-An OHBM-Open Science perspective.

Pradeep Reddy Raamana, Samuel A. Nastase, Katherine L. Bottenhorn, 2021, GigaScience.

International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium

Brett K. Beaulieu-Jones, Jeffrey G. Klann, Robert W. Follett, 2020, npj Digital Medicine.

I.C.E.: a transportable atomic inertial sensor for test in microgravity

A. Clairon, G. Santarelli, G. Varoquaux, 2006, International Conference on Space Optics.

I.C.E.: a transportable atomic inertial sensor for test in microgravity

G. Varoquaux, A. Clairon, G. Santarelli, 2006, cond-mat/0605057.

Causal inference methods for combining randomized trials and observational studies: a review

Shu Yang, Jean-Philippe Vert, Julie Josse, 2020, 2011.08047.

AI as statistical methods for imperfect theories

G. Varoquaux, 2021 .

Nipype 2012: More packages, reusable workflows and reproducible science

Satrajit S. Ghosh, Gaël Varoquaux, Krzysztof J. Gorgolewski, 2012 .

Software and Platforms - Scikit learn

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2013 .

Comprehensive decoding mental processes from Web repositories of functional brain images

G. Varoquaux, B. Thirion, Jérôme Dockès, 2022, Scientific Reports.

Dissemination - Animation of the scientific community

Jean-Baptiste Poline, Bertrand Thirion, Fabian Pedregosa, 2010 .

Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction

Danilo Bzdok, Gaël Varoquaux, Bertrand Thirion, 2017, NIPS 2017.

Software and Platforms - Nilearn

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2013 .

Machine learning for medical imaging: methodological failures and recommendations for the future

G. Varoquaux, V. Cheplygina, 2021, npj Digital Medicine.

International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

Jason W. Moore, Brett K. Beaulieu-Jones, Florence T. Bourgeois, 2022, npj Digital Medicine.

Proceedings of the 19th Python in Science Conference

G. Varoquaux, T. Vaught, J. Millman, 2020 .

Tapered-ampliﬁed AR-coated laser diodes for Potassium and Rubidium atomic-physics experiments

G. Varoquaux, A. Aspect, P. Bouyer, 2017 .

Total Variation Regularization for fMRI-Based Prediction of Behavior

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2011, IEEE Transactions on Medical Imaging.

Randomized parcellation based inference

Vincent Frouin, Jean-Baptiste Poline, Gaël Varoquaux, 2014, NeuroImage.

Decoding with Conﬁdence: 1 Statistical Control on Decoder Maps

G. Varoquaux, B. Thirion, J. Salmon, 2021 .

New Results - Randomized parcellation-based inference

Gaël Varoquaux, Bertrand Thirion, Virgile Fritsch, 2013 .

How to estimate the differential acceleration in a two-species atom interferometer to test the equivalence principle

Gaël Varoquaux, Philippe Bouyer, Arnaud Landragin, 2009, 0910.2412.

I.C.E.: An Ultra-Cold Atom Source for Long-Baseline Interferometric Inertial Sensors in Reduced Gravity

G. Varoquaux, W. Chaibi, A. Landragin, 2007, 0705.2922.

Mayavi2: 3D Scientific Data Visualization and Plottin'

Prabhu Ramachandran, Gaël Varoquaux, G. Varoquaux, 2012 .

Convolutional Network Layers Map the Function of the Human Visual Cortex

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2017, ERCIM News.

New Software and Platforms - Nilearn

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2014 .

New Software and Platforms - Nipy

Gaël Varoquaux, Bertrand Thirion, Elvis Dohmatob, 2014 .

Which fMRI clustering gives good brain parcellations?

Jean-Baptiste Poline, Gaël Varoquaux, Bertrand Thirion, 2014, Front. Neurosci..

Software and Platforms - Nipy

Gaël Varoquaux, Bertrand Thirion, Virgile Fritsch, 2013 .

New Results - Which fMRI clustering gives good brain parcellations?

Gaël Varoquaux, Bertrand Thirion, Elvis Dohmatob, 2014 .

Software - Scikit learn

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2011 .

New Results - Benchmarking solvers for TV-l1 least-squares and logistic regression in brain imaging

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2014 .

Mayavi: a package for 3D visualization of scientific data pdf

Gaël Varoquaux, Prabhu Ramachandran, G. Varoquaux, 2010, ArXiv.

Subsampling Enables Fast Factorisation of Huge Matrices into Sparse Signals

Gaël Varoquaux, Bertrand Thirion, Arthur Mensch, 2017, ERCIM News.

Extracting Universal Representations of Cognition across Brain-Imaging Studies pdf

Gaël Varoquaux, Bertrand Thirion, Arthur Mensch, 2018, ArXiv.

Proceedings of the 20th Python in Science Conference 2021 (SciPy 2021), Virtual Conference, July 12 - July 18, 2021

Gaël Varoquaux, Stefan van der Walt, Jarrod Millman, 2008, SciPy.

A Comparative Study of Algorithms for Intra- and Inter-subjects fMRI Decoding

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2011, MLINI.

New Software and Platforms - Scikit learn

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2014 .

Extracting representations of cognition across neuroimaging studies improves brain decoding

Gaël Varoquaux, Bertrand Thirion, Arthur Mensch, 2018, PLoS Comput. Biol..

Association of Antihypertensive Agents with the Risk of In-Hospital Death in Patients with Covid-19

G. Varoquaux, O. Grisel, A. Burgun, 2020, Cardiovascular Drugs and Therapy.

Hydroxychloroquine with or without azithromycin and in-hospital mortality or discharge in patients hospitalized for COVID-19 infection: a cohort study of 4,642 in-patients in France

G. Varoquaux, O. Grisel, M. Lavielle, 2020, medRxiv.

New Results - Identifying predictive regions from fMRI with TV-ℓ1 prior

Bertrand Thirion, Alexandre Gramfort, Gaël Varoquaux, 2013 .

Reweighting the RCT for generalization: ﬁnite sample analysis and variable selection

G. Varoquaux, Erwan Scornet, J. Josse, 2022 .

Metrics reloaded: Recommendations for image analysis validation

Anne L. Martel, Charles E. Kahn, Bjoern H Menze, 2022, 2206.01653.

Reweighting the RCT for generalization: finite sample analysis and variable selection

G. Varoquaux, Erwan Scornet, J. Josse, 2022, 2208.07614.

Tapered-amplified antireflection-coated laser diodes for potassium and rubidium atomic-physics experiments

G. Varoquaux, A. Aspect, P. Bouyer, 2005, cond-mat/0511737.

Analytics on Non-Normalized Data Sources: More Learning, Rather Than More Cleaning

G. Varoquaux, A. Allauzen, Alexis Cvetkov-Iliev, 2022, IEEE Access.

Reweighting the RCT for generalization: finite sample error and variable selection

G. Varoquaux, Erwan Scornet, J. Josse, 2022, 2208.07614.

Advancing brain network models to reconcile functional neuroimaging and clinical research

Mohit H. Adhikari, G. Varoquaux, A. Dagher, 2022, NeuroImage: Clinical.

Beyond calibration: estimating the grouping loss of modern neural networks

Marine Le Morvan, G. Varoquaux, Alexandre Perez-Lebel, 2022, ArXiv.

Body-weight variability and risk of cardiovascular outcomes in patients with type 1 diabetes: a retrospective observational analysis of data from the DCCT/EDIC population

G. Varoquaux, J. Vie, R. Roussel, 2022, Cardiovascular Diabetology.

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

G. Varoquaux, Edouard Oyallon, Léo Grinsztajn, 2022, ArXiv.

Light-shift tomography in an optical-dipole trap for neutral atoms

G. Varoquaux, A. Aspect, P. Bouyer, 2008, 0807.3672.

Fine-grain atlases of functional modes for fMRI analysis

Bertrand Thirion, Kamalaker Dadi, Gael Varoquaux, 2020, NeuroImage.

Stochastic Subsampling for Factorizing Huge Matrices

Gaël Varoquaux, Bertrand Thirion, Arthur Mensch, 2017, IEEE Transactions on Signal Processing.

Subsampled online matrix factorization with convergence guarantees

Bertrand Thirion, Gael Varoquaux, Arthur Mensch, 2016, NIPS 2016.

Exploring the anatomical encoding of voice with a mathematical model of the vocal system

Mariano Sigman, Gael Varoquaux, M. Florencia Assaneo, 2016, NeuroImage.

Benchmarking functional connectome-based predictive models for resting-state fMRI

Gaël Varoquaux, Bertrand Thirion, Kamalaker Dadi, 2019, NeuroImage.

Predicting brain-age from multimodal imaging data captures cognitive impairment

Daniel S. Margulies, Julia M. Huntenburg, Leonie Lampe, 2016, NeuroImage.

Comparing functional connectivity based predictive models across datasets

Gaël Varoquaux, Bertrand Thirion, Kamalaker Dadi, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Detection of Brain Functional-Connectivity Difference in Post-stroke Patients Using Group-Level Covariance Modeling

Gaël Varoquaux, Bertrand Thirion, Andreas Kleinschmidt, 2010, MICCAI.

External validation of prognostic scores for COVID-19: a multicenter cohort study of patients hospitalized in Greater Paris University Hospitals

G. Varoquaux, O. Grisel, A. Burgun, 2021, Intensive Care Medicine.

Subject‐specific segregation of functional territories based on deep phenotyping

Ana Luísa Pinho, G. Varoquaux, B. Thirion, 2020, Human brain mapping.

Individual Brain Charting dataset extension, second release of high-resolution fMRI data for cognitive mapping

Mathias Pessiglione, Gaël Varoquaux, Bertrand Thirion, 2020, Scientific data.

Learning and comparing functional connectomes across subjects

Gaël Varoquaux, R. Cameron Craddock, G. Varoquaux, 2013, NeuroImage.

Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

G. Varoquaux, A. Gramfort, J. B. Poline, 2012, Journal of Physiology-Paris.

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

Andres Hoyos Idrobo, Gaël Varoquaux, Bertrand Thirion, 2016, NeuroImage.

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments

Satrajit S. Ghosh, Thomas E. Nichols, Jean-Baptiste Poline, 2016, Scientific Data.

What's a good imputation to predict with missing values? pdf

Julie Josse, Erwan Scornet, Marine Le Morvan, 2021, NeurIPS.

Linear predictor on linearly-generated data with missing values: non consistency and solutions

Marine Le Morvan, G. Varoquaux, Erwan Scornet, 2020, AISTATS.

Benchmarking solvers for TV-ℓ1 least-squares and logistic regression in brain imaging

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2014, 2014 International Workshop on Pattern Recognition in Neuroimaging.

A group model for stable multi-subject ICA on fMRI datasets

Jean-Baptiste Poline, Gaël Varoquaux, Bertrand Thirion, 2010, NeuroImage.

Machine learning for medical imaging: methodological failures and recommendations for the future

G. Varoquaux, V. Cheplygina, 2022, npj Digital Medicine.

Population modeling with machine learning can enhance measures of mental health

G. Varoquaux, B. Thirion, D. Engemann, 2021, bioRxiv.

In Situ Synchrotron Microtomography Reveals Multiple Reaction Pathways During Soda‐Lime Glass Synthesis

G. Varoquaux, L. Salvo, E. Gouillart, 2012, 1201.2389.

Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity

Matthew B. Blaschko, Gaël Varoquaux, Eugene Belilovsky, 2015, NIPS.

How machine learning is shaping cognitive neuroimaging

Bertrand Thirion, Gael Varoquaux, G. Varoquaux, 2014, GigaScience.

Encoding High-Cardinality String Categorical Variables pdf

Gael Varoquaux, Patricio Cerda, G. Varoquaux, 2019, IEEE Transactions on Knowledge and Data Engineering.

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

Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann, 2019, NeuroImage.

Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example

Dimitris Samaras, Gaël Varoquaux, Bertrand Thirion, 2016, NeuroImage.

Multinational characterization of neurological phenotypes in patients hospitalized with COVID-19

Jason W. Moore, Brett K. Beaulieu-Jones, Florence T. Bourgeois, 2021, Scientific Reports.

Distinct alterations in Parkinson's medication-state and disease-state connectivity

Bernard Ng, Bertrand Thirion, Michael D. Greicius, 2017, NeuroImage: Clinical.

Inter-subject Registration of Functional Images: Do We Need Anatomical Images?

Bertrand Thirion, Gael Varoquaux, Elvis Dohmatob, 2018, Front. Neurosci..

Evolving phenotypes of non-hospitalized patients that indicate long COVID

Jason W. Moore, Brett K. Beaulieu-Jones, Tiago K. Colicchio, 2021, BMC Medicine.

Hospitalizations Associated With Mental Health Conditions Among Adolescents in the US and France During the COVID-19 Pandemic

Jason W. Moore, Florence T. Bourgeois, Tiago K. Colicchio, 2022, JAMA network open.

Association Between FIASMAs and Reduced Risk of Intubation or Death in Individuals Hospitalized for Severe COVID‐19: An Observational Multicenter Study

G. Varoquaux, O. Grisel, N. Hoertel, 2021, Clinical pharmacology and therapeutics.

International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium

Jeffrey G. Klann, Robert W. Follett, I. Krantz, 2020, npj Digital Medicine.

Combining magnetoencephalography with magnetic resonance imaging enhances learning of surrogate-biomarkers

Gaël Varoquaux, Alexandre Gramfort, Franziskus Liem, 2020, eLife.

Formal Models of the Network Co-occurrence Underlying Mental Operations

Danilo Bzdok, Michael Eickenberg, Gaël Varoquaux, 2016, PLoS Comput. Biol..

Which fMRI clustering gives good brain parcellations?

Jean-Baptiste Poline, Gaël Varoquaux, Bertrand Thirion, 2014, Front. Neurosci..

Machine learning for neuroimaging with scikit-learn

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2014, Front. Neuroinform..

Combining electrophysiology with MRI enhances learning of surrogate-biomarkers

Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann, 2019, bioRxiv.

Decoding with confidence: Statistical control on decoder maps

Gaël Varoquaux, Bertrand Thirion, Joseph Salmon, 2021, NeuroImage.

NeuroQuery, comprehensive meta-analysis of human brain mapping

Fabian M. Suchanek, Bertrand Thirion, Gael Varoquaux, 2020, eLife.

Computational and informatics advances for reproducible data analysis in neuroimaging pdf

Russell A. Poldrack, Gaël Varoquaux, Krzysztof J. Gorgolewski, 2018, ArXiv.

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

Daniel S. Margulies, Satrajit S. Ghosh, Russell A. Poldrack, 2014, bioRxiv.

Principal Component Regression Predicts Functional Responses across Individuals

Gaël Varoquaux, Bertrand Thirion, Cyril Poupon, 2014, MICCAI.

Identification of Mood-Relevant Brain Connections Using a Continuous, Subject-Driven Rumination Paradigm.

Bernard Ng, Bertrand Thirion, Anna-Clare Milazzo, 2016, Cerebral cortex.

Transport on Riemannian Manifold for Connectivity-Based Brain Decoding

Jean-Baptiste Poline, Bernard Ng, Gaël Varoquaux, 2016, IEEE Transactions on Medical Imaging.

Transport on Riemannian Manifold for Functional Connectivity-Based Classification

Jean-Baptiste Poline, Bernard Ng, Gaël Varoquaux, 2014, MICCAI.

Seeing it all: Convolutional network layers map the function of the human visual system

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2017, NeuroImage.

Loading and plotting of cortical surface representations in Nilearn

Julia M. Huntenburg, Gaël Varoquaux, Franziskus Liem, 2017 .

Establishment of Best Practices for Evidence for Prediction: A Review.

Gael Varoquaux, Russell A Poldrack, Grace Huckins, 2019, JAMA psychiatry.

Manifold-regression to predict from MEG/EEG brain signals without source modeling

Gael Varoquaux, Alexandre Gramfort, Denis A. Engemann, 2019, NeurIPS.

On the consistency of supervised learning with missing values pdf

Gaël Varoquaux, Julie Josse, Erwan Scornet, 2019, ArXiv.

Cross-validation failure: Small sample sizes lead to large error bars

Gaël Varoquaux, G. Varoquaux, 2017, NeuroImage.

Causal inference methods for combining randomized trials and observational studies: a review

G. Varoquaux, Jean-Philippe Vert, Shu Yang, 2020, 2011.08047.

How to remove or control confounds in predictive models, with applications to brain biomarkers

G. Varoquaux, B. Thirion, M. Milham, 2022, GigaScience.

PyXNAT: XNAT in Python

Benjamin Thyreau, Vincent Frouin, Jean-Baptiste Poline, 2012, Front. Neuroinform..

Prediction, Not Association, Paves the Road to Precision Medicine.

Danilo Bzdok, Gael Varoquaux, Ewout W Steyerberg, 2020, JAMA psychiatry.

BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods

Satrajit S. Ghosh, Anisha Keshavan, Mark Jenkinson, 2016, bioRxiv.

Group-PCA for very large fMRI datasets

Aapo Hyvärinen, Stephen M. Smith, Gaël Varoquaux, 2014, NeuroImage.

Joint prediction of multiple scores captures better individual traits from brain images

Irène Buvat, Danilo Bzdok, Gaël Varoquaux, 2017, NeuroImage.

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

Daniel S. Margulies, Satrajit S. Ghosh, Russell A. Poldrack, 2016, NeuroImage.

Brain covariance selection: better individual functional connectivity models using population prior

Jean-Baptiste Poline, Gaël Varoquaux, Bertrand Thirion, 2010, NIPS.

Transmodal Learning of Functional Networks for Alzheimer's Disease Prediction

Gaël Varoquaux, Bertrand Thirion, Claude Comtat, 2016, IEEE Journal of Selected Topics in Signal Processing.

FReM – Scalable and stable decoding with fast regularized ensemble of models

Andres Hoyos Idrobo, Gaël Varoquaux, Bertrand Thirion, 2017, NeuroImage.

Multi-subject Dictionary Learning to Segment an Atlas of Brain Spontaneous Activity

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2011, IPMI.

Scale-Free and Multifractal Time Dynamics of fMRI Signals during Rest and Task

P. Abry, A. Kleinschmidt, P. Ciuciu, 2012, Front. Physio..

Deriving robust biomarkers from multi-site resting-state data: An Autism-based example

Dimitris Samaras, Gaël Varoquaux, Bertrand Thirion, 2016, bioRxiv.

Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery

Joris Van den Bossche, B. Kégl, T. Bourgeron, 2021, NeuroImage.

Scikit-learn: Machine Learning Without Learning the Machinery

Gilles Louppe, Gaël Varoquaux, Lars Buitinck, 2015, GETMBL.

How to estimate the differential acceleration in a two-species atom interferometer to test the equivalence principle

Philippe Bouyer, Arnaud Landragin, Robert A. Nyman, 2009, 0910.2412.

Correlations of correlations are not reliable statistics: implications for multivariate pattern analysis.

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2015, ICML 2015.

Accounting for Variance in Machine Learning Benchmarks pdf

Tal Arbel, Dmitriy Serdyuk, Edward Raff, 2021, MLSys.

NeuroVault.org: A web-based repository for collecting and sharing unthresholded statistical maps of the human brain

Daniel S. Margulies, Satrajit S. Ghosh, Russell A. Poldrack, 2014, bioRxiv.

Social-sparsity brain decoders: faster spatial sparsity

Gaël Varoquaux, Bertrand Thirion, Matthieu Kowalski, 2016, 2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Total Variation meets Sparsity: statistical learning with segmenting penalties

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2015 .

Grouping Total Variation and Sparsity: Statistical Learning with Segmenting Penalties

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2015, MICCAI.

FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging pdf

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2015, ArXiv.

Convex relaxations of penalties for sparse correlated variables with bounded total variation

Matthew B. Blaschko, Gaël Varoquaux, Andreas Argyriou, 2015, Machine Learning.

Predictive models avoid excessive reductionism in cognitive neuroimaging

Gaël Varoquaux, Russell A Poldrack, G. Varoquaux, 2019, Current Opinion in Neurobiology.

Risk of Death in Individuals Hospitalized for COVID-19 With and Without Psychiatric Disorders: An Observational Multicenter Study in France

M. Leboyer, G. Varoquaux, O. Grisel, 2022, Biological Psychiatry Global Open Science.

Patterns of autism symptoms: hidden structure in the ADOS and ADI-R instruments

G. Varoquaux, B. Thirion, K. Vogeley, 2019, Translational Psychiatry.

Comparing distributions: 𝓁1 geometry improves kernel two-sample testing

G. Varoquaux, M. Scetbon, G. Varoquaux, 2019, NeurIPS 2019.

Preventing dataset shift from breaking machine-learning biomarkers

Jean-Baptiste Poline, J B Poline, Gael Varoquaux, 2021, GigaScience.

Author response: NeuroQuery, comprehensive meta-analysis of human brain mapping

Russell A. Poldrack, Fabian M. Suchanek, Fabian M. Suchanek, 2020 .

Causal effect on a target population: A sensitivity analysis to handle missing covariates

Julie Josse, Erwan Scornet, B'en'edicte Colnet, 2021, Journal of Causal Inference.

Generalizing a causal effect: sensitivity analysis and missing covariates

G. Varoquaux, Erwan Scornet, J. Josse, 2021 .

Benchmarking missing-values approaches for predictive models on health databases

Marine Le Morvan, G. Varoquaux, J. Poline, 2022, GigaScience.

Neumann networks: differential programming for supervised learning with missing values

Marine Le Morvan, G. Varoquaux, Erwan Scornet, 2020, ArXiv.

Balázs Kégl, Gaël Varoquaux, Patricio Cerda, 2018, Machine Learning.

Using and understanding cross-validation strategies. Perspectives on Saeb et al.

Max A. Little, Gael Varoquaux, Konrad P. Kording, 2017, GigaScience.

Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study

Jason W. Moore, Brett K. Beaulieu-Jones, Florence T. Bourgeois, 2022, eClinicalMedicine.

Improving Sparse Recovery on Structured Images with Bagged Clustering

Andres Hoyos Idrobo, Gaël Varoquaux, Bertrand Thirion, 2015, 2015 International Workshop on Pattern Recognition in NeuroImaging.

Mapping cognitive ontologies to and from the brain pdf

Gaël Varoquaux, Bertrand Thirion, Yannick Schwartz, 2013, NIPS 2013.

Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations

Vincent Frouin, Jean-Baptiste Poline, Gaël Varoquaux, 2013, MICCAI.

A Novel Sparse Group Gaussian Graphical Model for Functional Connectivity Estimation

Jean-Baptiste Poline, Bernard Ng, Gaël Varoquaux, 2013, IPMI.

A Novel Sparse Graphical Approach for Multimodal Brain Connectivity Inference

Jean-Baptiste Poline, Bernard Ng, Gaël Varoquaux, 2012, MICCAI.

Improving Accuracy and Power with Transfer Learning Using a Meta-analytic Database

Jean-Baptiste Poline, Gaël Varoquaux, Bertrand Thirion, 2012, MICCAI.

Connectivity-informed Sparse Classifiers for fMRI Brain Decoding

Jean-Baptiste Poline, Bernard Ng, Gaël Varoquaux, 2012, 2012 Second International Workshop on Pattern Recognition in NeuroImaging.

Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clustering

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2012, ICML.

Beyond Brain Reading: Randomized Sparsity and Clustering to Simultaneously Predict and Identify

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2011, MLINI.

Euroscipy 2011: Python in Neuroscience workshop

Gaël Varoquaux, Bertrand Thirion, Romain Brette, 2011 .

Towards a faster randomized parcellation based inference

Andres Hoyos Idrobo, Gaël Varoquaux, Bertrand Thirion, 2017, 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Robust regression for large-scale neuroimaging studies

Vincent Frouin, Jean-Baptiste Poline, Gaël Varoquaux, 2015, NeuroImage.

Detecting outliers in high-dimensional neuroimaging datasets with robust covariance estimators

Benjamin Thyreau, Jean-Baptiste Poline, Gaël Varoquaux, 2012, Medical Image Anal..

A fast computational framework for genome-wide association studies with neuroimaging data

Jean-Baptiste Poline, Gaël Varoquaux, Bertrand Thirion, 2012 .

Identifying Predictive Regions from fMRI with TV-L1 Prior

Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort, 2013, 2013 International Workshop on Pattern Recognition in Neuroimaging.

Machine learning patterns for neuroimaging-genetic studies in the cloud

Vincent Frouin, Jean-Baptiste Poline, Gaël Varoquaux, 2014, Front. Neuroinform..

Survey of machine-learning experimental methods at NeurIPS2019 and ICLR2020

Xavier Bouthillier, Gaël Varoquaux, Xavier Bouthillier, 2020 .

Recursive Nearest Agglomeration (ReNA): Fast Clustering for Approximation of Structured Signals

Gaël Varoquaux, Bertrand Thirion, Jonas Kahn, 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Why do tree-based models still outperform deep learning on typical tabular data?

G. Varoquaux, Edouard Oyallon, Léo Grinsztajn, 2022, NeurIPS.

Brainhack: Developing a culture of open, inclusive, community-driven neuroscience

Julia M. Huntenburg, Satrajit S. Ghosh, Elizabeth A. McDevitt, 2021, Neuron.

Extracting representations of cognition across neuroimaging studies improves brain decoding

G. Varoquaux, B. Thirion, J. Mairal, 2018, PLoS Comput. Biol..

Population-Shrinkage of Covariance to Estimate Better Brain Functional Connectivity

Gaël Varoquaux, Bertrand Thirion, Mehdi Rahim, 2017, MICCAI.

Centering inclusivity in the design of online conferences-An OHBM-Open Science perspective.

Saige Rutherford, Tristan Glatard, Simon B. Eickhoff, 2021, GigaScience.

Detecting Outlying Subjects in High-Dimensional Neuroimaging Datasets with Regularized Minimum Covariance Determinant

Benjamin Thyreau, Jean-Baptiste Poline, Gaël Varoquaux, 2011, MICCAI.

Compressed online dictionary learning for fast resting-state fMRI decomposition

Gaël Varoquaux, Bertrand Thirion, Arthur Mensch, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Risk ratio, odds ratio, risk difference... Which causal measure is easier to generalize?

G. Varoquaux, Erwan Scornet, J. Josse, 2023, 2303.16008.

Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer's Disease

Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, 2015, MICCAI.

Big data and extreme-scale computing

Franck Cappello, Satoshi Matsuoka, Alexander S. Szalay, 2018, Int. J. High Perform. Comput. Appl..

Multifractal analysis of Resting State Networks in functional MRI

Gaël Varoquaux, Patrice Abry, Philippe Ciuciu, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

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

Jean-Baptiste Poline, Gaël Varoquaux, Bertrand Thirion, 2009, ArXiv.

Numerical uncertainty in analytical pipelines lead to impactful variability in brain networks

Alan C. Evans, G. Varoquaux, B. Mišić, 2021, PloS one.

Numerical Instabilities in Analytical Pipelines Lead to Large and Meaningful Variability in Brain Networks

Gaël Varoquaux, Gregory Kiar, Yohan Chatelain, 2020, bioRxiv.

Deriving a Multi-subject Functional-Connectivity Atlas to Inform Connectome Estimation

Ronald Phlypo, Gaël Varoquaux, Bertrand Thirion, 2014, MICCAI.

A Framework for Inter-Subject Prediction of Functional Connectivity From Structural Networks

Daniel Rueckert, Fani Deligianni, Gaël Varoquaux, 2013, IEEE Transactions on Medical Imaging.

A Probabilistic Framework to Infer Brain Functional Connectivity from Anatomical Connections

Daniel Rueckert, Fani Deligianni, Gaël Varoquaux, 2011, IPMI.

Region segmentation for sparse decompositions: better brain parcellations from rest fMRI pdf

Dimitris Samaras, Gaël Varoquaux, Bertrand Thirion, 2014, ArXiv.

Population shrinkage of covariance (PoSCE) for better individual brain functional‐connectivity estimation☆

Gaël Varoquaux, Bertrand Thirion, Mehdi Rahim, 2019, Medical Image Anal..

Multi-output predictions from neuroimaging: assessing reduced-rank linear models

Gaël Varoquaux, Bertrand Thirion, Mehdi Rahim, 2017, 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Learning Neural Representations of Human Cognition across Many fMRI Studies

Thomas E. Nichols, Danilo Bzdok, Gaël Varoquaux, 2017, NIPS.

Atlases of cognition with large-scale human brain mapping

Jean-Baptiste Poline, Danilo Bzdok, Bertrand Thirion, 2018, PLoS Comput. Biol..

Text to brain: predicting the spatial distribution of neuroimaging observations from text reports pdf

Russell A. Poldrack, Fabian M. Suchanek, Gaël Varoquaux, 2018, MICCAI.

Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data

Danilo Bzdok, Michael Eickenberg, Gaël Varoquaux, 2015, NIPS.

How to select predictive models for causal inference?

G. Varoquaux, Matthieu Doutreligne, 2023, ArXiv.

Beyond calibration: estimating the grouping loss of modern neural networks

Marine Le Morvan, G. Varoquaux, Alexandre Perez-Lebel, 2022, ICLR.

nipy/nibabel: 3.2.1

Krzysztof J. Gorgolewski, Felix C. Morency, Gregory R. Lee, 2020 .

Understanding Brain Network Dynamics in Autism Begs for Generalization

G. Varoquaux, Yong Liu, 2022, Biological Psychiatry.

Learning brain regions via large-scale online structured sparse dictionary learning

Gaël Varoquaux, Bertrand Thirion, Arthur Mensch, 2016, NIPS.

A Lightweight Neural Model for Biomedical Entity Linking

Fabian M. Suchanek, Lihu Chen, Gael Varoquaux, 2020, AAAI.

How to select predictive models for causal inference?

G. Varoquaux, Matthieu Doutreligne, M. Doutreligne, 2023, ArXiv.

sphinx-gallery/sphinx-gallery: Release v0.7.0

Alyssa M. Batula, jaeilepp, G. Varoquaux, 2020 .

Scikit-learn: Machine Learning Without Learning the Machinery

Fabian Pedregosa, G. Varoquaux, O. Grisel, 2015, GETMBL.

Connectivity-Informed fMRI Activation Detection

Jean-Baptiste Poline, Bernard Ng, Gaël Varoquaux, 2011, MICCAI.

Atlases of cognition with large-scale brain mapping

Russell A. Poldrack, Jean-Baptiste Poline, Danilo Bzdok, 2018 .

GLADIS: A General and Large Acronym Disambiguation Benchmark

Fabian M. Suchanek, G. Varoquaux, Lihu Chen, 2023, Conference of the European Chapter of the Association for Computational Linguistics.

Dictionary Learning for Massive Matrix Factorization pdf

Gaël Varoquaux, Bertrand Thirion, Arthur Mensch, 2016, ICML.

ICA-based sparse features recovery from fMRI datasets

Jean-Baptiste Poline, Gaël Varoquaux, Bertrand Thirion, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Dictionary Learning for Massive Matrix Factorization Dictionary Learning for Massive Matrix Factorization

G. Varoquaux, B. Thirion, J. Mairal, 2022 .

Statistical Learning for Resting-State fMRI: Successes and Challenges

Gaël Varoquaux, Bertrand Thirion, G. Varoquaux, 2011, MLINI.

Learning to Discover Sparse Graphical Models

Matthew B. Blaschko, Gaël Varoquaux, Eugene Belilovsky, 2016, ICML.

Beyond brain age: Empirically-derived proxy measures of mental health

G. Varoquaux, B. Thirion, D. Engemann, 2020 .

Population modeling with machine learning can enhance measures of mental health

G. Varoquaux, D. Engemann, J. Houenou, 2021 .

Beyond brain age: Empirically-derived proxy measures of mental health

G. Varoquaux, D. Engemann, J. Houenou, 2020 .

Imputing Out-of-Vocabulary Embeddings with LOVE Makes LanguageModels Robust with Little Cost

Fabian M. Suchanek, G. Varoquaux, Lihu Chen, 2022, ACL.

Agile Computer Control of a Complex Experiment

Gaël Varoquaux, G. Varoquaux, 2008, Computing in Science & Engineering.

Mapping paradigm ontologies to and from the brain

Gaël Varoquaux, Bertrand Thirion, Yannick Schwartz, 2013, NIPS.

Causal thinking for decision making on Electronic Health Records: why and how

G. Varoquaux, L. Celi, C. Morgand, 2023, 2308.01605.

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Thomas E. Nichols, Krzysztof J. Gorgolewski, Adam G. Thomas, 2023, 2309.05768.

Metrics reloaded: Pitfalls and recommendations for image analysis validation

M. Jorge Cardoso, Anne L. Martel, Bjoern H Menze, 2022, ArXiv.

A MapReduce Approach for Ridge Regression in Neuroimaging-Genetic Studies

Jean-Baptiste Poline, Michael Eickenberg, Gaël Varoquaux, 2012, MICCAI 2012.

Extracting Brain Regions from Rest fMRI with Total-Variation Constrained Dictionary Learning

Dimitris Samaras, Gaël Varoquaux, Bertrand Thirion, 2013, MICCAI.

Learning and comparing functional connectomes across subjects

G. Varoquaux, R. Craddock, R. Cameron Craddock, 2013, NeuroImage.

Relating Brain Functional Connectivity to Anatomical Connections: Model Selection

Daniel Rueckert, Fani Deligianni, Gaël Varoquaux, 2011, MLINI.

Transport on Riemannian Manifold for Connectivity-Based Brain Decoding

G. Varoquaux, B. Thirion, M. Greicius, 2016, IEEE Transactions on Medical Imaging.

Fast clustering for scalable statistical analysis on structured images pdf

Andres Hoyos Idrobo, Gaël Varoquaux, Bertrand Thirion, 2015, ICML 2015.

Robust regression for large-scale neuroimaging studies

G. Varoquaux, B. Thirion, T. Paus, 2015, NeuroImage.

Robust Group-Level Inference in Neuroimaging Genetic Studies

Vincent Frouin, Jean-Baptiste Poline, Gaël Varoquaux, 2013, 2013 International Workshop on Pattern Recognition in Neuroimaging.

A Probabilistic Framework to Infer Brain Functional Connectivity from Anatomical Connections

G. Varoquaux, E. Robinson, F. Deligianni, 2011, IPMI.

Predictive models can overcome reductionism in cognitive neuroimaging

Russell A. Poldrack, Gaël Varoquaux, G. Varoquaux, 2018 .

Brain-based ranking of cognitive domains to predict schizophrenia

G. Varoquaux, B. Thirion, O. Grisel, 2018, bioRxiv.

Metrics reloaded: Recommendations for image analysis validation

Anne L. Martel, Charles E. Kahn, Bjoern H Menze, 2022, 2206.01653.

Learning to rank from medical imaging data pdf

Bertrand Thirion, Gael Varoquaux, Alexandre Gramfort, 2012, MLMI.

Learning to Discover Graphical Model Structures

Matthew B. Blaschko, Gaël Varoquaux, Eugene Belilovsky, 2016 .

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

J B Poline, G. Varoquaux, B. Thirion, 2009, ArXiv.

Cohort-Level Brain Mapping: Learning Cognitive Atoms to Single Out Specialized Regions

Gaël Varoquaux, Bertrand Thirion, Philippe Pinel, 2013, IPMI.

A Framework for Inter-Subject Prediction of Functional Connectivity From Structural Networks

G. Varoquaux, C. Ledig, F. Deligianni, 2013, IEEE Transactions on Medical Imaging.

Comparing distributions: 퓁1 geometry improves kernel two-sample testing

G. Varoquaux, M. Scetbon, 2019, NeurIPS.

FReM – Scalable and stable decoding with fast regularized ensemble of models

G. Varoquaux, B. Thirion, Y. Schwartz, 2017, NeuroImage.

Decoding fMRI activity in the time domain improves classification performance

Gaël Varoquaux, Bertrand Thirion, João Loula, 2017, NeuroImage.

NeuMiss networks: differentiable programming for supervised learning with missing values

Marine Le Morvan, G. Varoquaux, Erwan Scornet, 2020, NeurIPS.

A group model for stable multi-subject ICA on fMRI datasets

G. Varoquaux, B. Thirion, A. Kleinschmidt, 2010, NeuroImage.

Confidence intervals for performance estimates in 3D medical image segmentation

Rosana El Jurdi, G. Varoquaux, O. Colliot, 2023, ArXiv.

Independent consultant

Fabian Pedregosa, G. Varoquaux, O. Grisel, 2013 .

Relating Brain Structures To Open-Ended Descriptions Of Cognition

Fabian M. Suchanek, Gaël Varoquaux, Bertrand Thirion, 2017 .

Causal Inference Methods for Combining Randomized Trials and Observational Studies: A Review

G. Varoquaux, Jean-Philippe Vert, Shu Yang, 2020, Statistical Science.

Metrics reloaded: recommendations for image analysis validation.

Anne L. Martel, Charles E. Kahn, Bjoern H Menze, 2022, Nature methods.

Machine learning for medical imaging: methodological failures and recommendations for the future

G. Varoquaux, V. Cheplygina, 2022, npj Digital Medicine.

CARTE: pretraining and transfer for tabular learning

G. Varoquaux, Léo Grinsztajn, Myung Jun Kim, 2024, ArXiv.

Changing computational research. The challenges ahead

Egon L. Willighagen, Peter Murray-Rust, Gaël Varoquaux, 2012, Source Code for Biology and Medicine.

Understanding metric-related pitfalls in image analysis validation.

Bjoern H Menze, G. Varoquaux, P. Jannin, 2023, Nature methods.

Exploring Network Structure , Dynamics , and Function using NetworkX 11

G. Varoquaux, T. Vaught, J. Millman, 2008 .

Approximate message-passing for convex optimization with non-separable penalties pdf

Florent Krzakala, Lenka Zdeborová, Gaël Varoquaux, 2018, ArXiv.

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

A. Boulesteix, G. Varoquaux, M. Sendak, 2024, BMJ.

Controlling a confound in predictive models with a test set minimizing its effect

Gaël Varoquaux, Bertrand Thirion, Michael P. Milham, 2018, 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging

Danilo Bzdok, Michael Eickenberg, Gaël Varoquaux, 2017, IPMI.