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Gaël Varoquaux
Gaël Varoquaux
Research director, INRIA
Verifisert e-postadresse på normalesup.org - Startside
Tittel
Sitert av
Sitert av
År
Scikit-learn: Machine learning in Python
F Pedregosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ...
the Journal of machine Learning research 12, 2825-2830, 2011
1074702011
The NumPy array: a structure for efficient numerical computation
S Van Der Walt, SC Colbert, G Varoquaux
Computing in Science & Engineering 13 (2), 22-30, 2011
123102011
API design for machine learning software: experiences from the scikit-learn project
L Buitinck, G Louppe, M Blondel, F Pedregosa, A Mueller, O Grisel, ...
arXiv preprint arXiv:1309.0238, 2013
38652013
Machine learning for neuroimaging with scikit-learn
A Abraham, F Pedregosa, M Eickenberg, P Gervais, A Mueller, J Kossaifi, ...
Frontiers in neuroinformatics 8, 14, 2014
21562014
The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments
KJ Gorgolewski, T Auer, VD Calhoun, RC Craddock, S Das, EP Duff, ...
Scientific data 3 (1), 1-9, 2016
16302016
Why do tree-based models still outperform deep learning on typical tabular data?
L Grinsztajn, E Oyallon, G Varoquaux
Advances in neural information processing systems 35, 507-520, 2022
15292022
Mayavi: 3D visualization of scientific data
P Ramachandran, G Varoquaux
Computing in Science & Engineering 13 (2), 40-51, 2011
8092011
Scikit-Learn 0.22. 1 Documentation
F Pedregosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ...
Scikit-Learn 0.22 2, 2020
748*2020
Assessing and tuning brain decoders: cross-validation, caveats, and guidelines
G Varoquaux, PR Raamana, DA Engemann, A Hoyos-Idrobo, Y Schwartz, ...
NeuroImage 145, 166-179, 2017
7102017
Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example
A Abraham, MP Milham, A Di Martino, RC Craddock, D Samaras, ...
NeuroImage 147, 736-745, 2017
7032017
Establishment of best practices for evidence for prediction: a review
RA Poldrack, G Huckins, G Varoquaux
JAMA psychiatry 77 (5), 534-540, 2020
6812020
Cross-validation failure: Small sample sizes lead to large error bars
G Varoquaux
Neuroimage 180, 68-77, 2018
6712018
Scikit-learn: Machine learning without learning the machinery
G Varoquaux, L Buitinck, G Louppe, O Grisel, F Pedregosa, A Mueller
GetMobile: Mobile Computing and Communications 19 (1), 29-33, 2015
667*2015
NeuroVault. org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain
KJ Gorgolewski, G Varoquaux, G Rivera, Y Schwarz, SS Ghosh, ...
Frontiers in neuroinformatics 9, 8, 2015
6452015
Predicting brain-age from multimodal imaging data captures cognitive impairment
F Liem, G Varoquaux, J Kynast, F Beyer, SK Masouleh, JM Huntenburg, ...
Neuroimage 148, 179-188, 2017
4932017
Machine learning for medical imaging: methodological failures and recommendations for the future
G Varoquaux, V Cheplygina
NPJ digital medicine 5 (1), 48, 2022
4812022
Seeing it all: Convolutional network layers map the function of the human visual system
M Eickenberg, A Gramfort, G Varoquaux, B Thirion
NeuroImage 152, 184-194, 2017
4402017
Which fMRI clustering gives good brain parcellations?
B Thirion, G Varoquaux, E Dohmatob, JB Poline
Frontiers in neuroscience 8, 167, 2014
4002014
Brain covariance selection: better individual functional connectivity models using population prior
G Varoquaux, A Gramfort, JB Poline, B Thirion
Advances in neural information processing systems 23, 2010
3542010
Benchmarking functional connectome-based predictive models for resting-state fMRI
K Dadi, M Rahim, A Abraham, D Chyzhyk, M Milham, B Thirion, ...
NeuroImage 192, 115-134, 2019
3422019
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Artikler 1–20