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ORCIDGaël Varoquaux
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- affiliation: Inria Saclay, Palaiseau, France
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2020 – today
- 2023
[j52]Alexis Cvetkov-Iliev
, Alexandre Allauzen, Gaël Varoquaux:
Relational data embeddings for feature enrichment with background information. Mach. Learn. 112(2): 687-720 (2023)- [c69]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
GLADIS: A General and Large Acronym Disambiguation Benchmark. EACL 2023: 2065-2080 - [i50]Matthieu Doutreligne, Gaël Varoquaux:
How to select predictive models for causal inference? CoRR abs/2302.00370 (2023) - [i49]Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew B. Blaschko, Florian Büttner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir M. Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein:
Understanding metric-related pitfalls in image analysis validation. CoRR abs/2302.01790 (2023) - [i48]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
GLADIS: A General and Large Acronym Disambiguation Benchmark. CoRR abs/2302.01860 (2023) - 2022
- [j51]Alexis Cvetkov-Iliev, Alexandre Allauzen, Gaël Varoquaux:
Analytics on Non-Normalized Data Sources: More Learning, Rather Than More Cleaning. IEEE Access 10: 42420-42431 (2022) - [j50]Nicolas Traut, Katja Heuer, Guillaume Lemaître, Anita Beggiato, David Germanaud, Monique Elmaleh, Alban Bethegnies, Laurent Bonnasse-Gahot, Weidong Cai, Stanislas Chambon, Freddy Cliquet, Ayoub Ghriss, Nicolas Guigui, Amicie de Pierrefeu, Meng Wang, Valentina Zantedeschi, Alexandre Boucaud, Joris Van den Bossche, Balázs Kégl, Richard Delorme, Thomas Bourgeron, Roberto Toro, Gaël Varoquaux:
Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery. NeuroImage 255: 119171 (2022) - [j49]Gaël Varoquaux, Veronika Cheplygina:
Machine learning for medical imaging: methodological failures and recommendations for the future. npj Digit. Medicine 5 (2022) - [j48]Griffin M. Weber, Chuan Hong, Zongqi Xia, Nicolas Paris, Miguel Pedrera-Jiménez, Ashley C. Pfaff, Emily R. Pfaff, Danielle Pillion, Sara Pizzimenti, Hans-Ulrich Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Domínguez, Pablo Rojo, Paula Rubio-Mayo, Paolo Sacchi, Carlos Sáez, Elisa Salamanca, Malarkodi Jebathilagam Samayamuthu, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C. C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Jürgen Schüttler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Mohsin Shah, Zahra Shakeri Hossein Abad, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Andrew M. South, Francesca Sperotto, Zachary H. Strasser, Bryce W. Q. Tan, Suzana E. Tanni, Deanne M. Taylor, Ana I. Terriza-Torres, Patric Tippmann, Emma M. S. Toh, Yi-Ju Tseng, Andrew K. Vallejos, Gaël Varoquaux, Margaret E. Vella, Guillaume Verdy, Jill-Jênn Vie, Michele Vitacca, Kavishwar B. Wagholikar, Lemuel R. Waitman, Demian Wassermann, Martin Wolkewitz, Scott Wong, Xin Xiong, Ye Ye, Nadir Yehya, William Yuan, Alberto Zambelli, Harrison G. Zhang, Daniela Zöller, Valentina Zuccaro, Chiara Zucco:
International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality. npj Digit. Medicine 5 (2022) - [j47]Patricio Cerda, Gaël Varoquaux:
Encoding High-Cardinality String Categorical Variables. IEEE Trans. Knowl. Data Eng. 34(3): 1164-1176 (2022) - [c68]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
Imputing Out-of-Vocabulary Embeddings with LOVE Makes LanguageModels Robust with Little Cost. ACL (1) 2022: 3488-3504 - [c67]Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux:
Why do tree-based models still outperform deep learning on typical tabular data? NeurIPS 2022 - [d1]Alexis Cvetkov-Iliev, Alexandre Allauzen, Gaël Varoquaux:
Employee salaries in Texas administrations. IEEE DataPort, 2022
- [i47]Alexandre Perez-Lebel, Gaël Varoquaux, Marine Le Morvan, Julie Josse, Jean-Baptiste Poline:
Benchmarking missing-values approaches for predictive models on health databases. CoRR abs/2202.10580 (2022) - [i46]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost. CoRR abs/2203.07860 (2022) - [i45]Lena Maier-Hein, Annika Reinke, Evangelia Christodoulou, Ben Glocker, Patrick Godau, Fabian Isensee, Jens Kleesiek, Michal Kozubek, Mauricio Reyes, Michael A. Riegler, Manuel Wiesenfarth, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Minu Dietlinde Tizabi, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Peter Bankhead, Arriel Benis, M. Jorge Cardoso, Veronika Cheplygina, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Bram van Ginneken, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Pierre Jannin, Charles E. Kahn, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Annette Kopp-Schneider, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, David Moher, Karel G. M. Moons, Henning Müller, Felix Nickel, Brennan Nichyporuk, Jens Petersen, Nasir M. Rajpoot, Nicola Rieke, Julio Saez-Rodriguez, Clarisa Sánchez Gutiérrez, Shravya Shetty, Maarten van Smeden, Carole H. Sudre, Ronald M. Summers, Abdel A. Taha, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Paul F. Jäger:
Metrics reloaded: Pitfalls and recommendations for image analysis validation. CoRR abs/2206.01653 (2022) - [i44]Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux:
Why do tree-based models still outperform deep learning on tabular data? CoRR abs/2207.08815 (2022) - [i43]Alexandre Perez-Lebel, Marine Le Morvan, Gaël Varoquaux:
Beyond calibration: estimating the grouping loss of modern neural networks. CoRR abs/2210.16315 (2022) - 2021
- [j46]Jérôme-Alexis Chevalier, Tuan-Binh Nguyen, Joseph Salmon, Gaël Varoquaux, Bertrand Thirion:
Decoding with confidence: Statistical control on decoder maps. NeuroImage 234: 117921 (2021) - [j45]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Extracting representations of cognition across neuroimaging studies improves brain decoding. PLoS Comput. Biol. 17(5) (2021) - [c66]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
A Lightweight Neural Model for Biomedical Entity Linking. AAAI 2021: 12657-12665 - [c65]Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Nazanin Mohammadi Sepahvand, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent:
Accounting for Variance in Machine Learning Benchmarks. MLSys 2021 - [c64]Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux:
What's a good imputation to predict with missing values? NeurIPS 2021: 11530-11540 - [i42]Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent:
Accounting for Variance in Machine Learning Benchmarks. CoRR abs/2103.03098 (2021) - [i41]Gaël Varoquaux, Veronika Cheplygina:
How I failed machine learning in medical imaging - shortcomings and recommendations. CoRR abs/2103.10292 (2021) - [i40]Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux:
What's a good imputation to predict with missing values? CoRR abs/2106.00311 (2021) - [i39]Jérôme Dockès, Gaël Varoquaux, Jean-Baptiste Poline:
Preventing dataset shift from breaking machine-learning biomarkers. CoRR abs/2107.09947 (2021) - [i38]Marc-Andre Schulz, Bertrand Thirion, Alexandre Gramfort, Gaël Varoquaux, Danilo Bzdok:
Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction. CoRR abs/2110.06135 (2021) - 2020
- [j44]Kamalaker Dadi, Gaël Varoquaux, Antonia Machlouzarides-Shalit, Krzysztof J. Gorgolewski, Demian Wassermann, Bertrand Thirion, Arthur Mensch:
Fine-grain atlases of functional modes for fMRI analysis. NeuroImage 221: 117126 (2020) - [j43]David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann:
Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states. NeuroImage 222: 116893 (2020) - [j42]Gabriel A. Brat, Griffin M. Weber, Nils Gehlenborg, Paul Avillach, Nathan P. Palmer, Luca Chiovato, James J. Cimino, Lemuel R. Waitman, Gilbert S. Omenn, Alberto Malovini, Jason H. Moore, Brett K. Beaulieu-Jones, Valentina Tibollo, Shawn N. Murphy, Sehi L'Yi, Mark S. Keller, Riccardo Bellazzi, David A. Hanauer, Arnaud Serret-Larmande, Alba Gutiérrez-Sacristán, John J. Holmes, Douglas S. Bell, Kenneth D. Mandl, Robert W. Follett, Jeffrey G. Klann, Douglas A. Murad, Luigia Scudeller, Mauro Bucalo, Katie G. Kirchoff, Jean B. Craig, Jihad S. Obeid, Vianney Jouhet, Romain Griffier, Sébastien Cossin, Bertrand Moal, Lav P. Patel, Antonio Bellasi, Hans-Ulrich Prokosch, Detlef Kraska, Piotr Sliz, Amelia L. M. Tan, Kee Yuan Ngiam, Alberto Zambelli, Danielle L. Mowery, Emily Schiver, Batsal Devkota, Robert L. Bradford, Mohamad Daniar, Christel Daniel, Vincent Benoit, Romain Bey, Nicolas Paris, Patricia Serre, Nina Orlova, Julien Dubiel, Martin Hilka, Anne-Sophie Jannot, Stéphane Bréant, Judith Leblanc, Nicolas Griffon, Anita Burgun, Mélodie Bernaux, Arnaud Sandrin, Elisa Salamanca, Sylvie Cormont, Thomas Ganslandt, Tobias Gradinger, Julien Champ, Martin Boeker, Patricia Martel, Loic Esteve, Alexandre Gramfort, Olivier Grisel, Damien Leprovost, Thomas Moreau, Gaël Varoquaux, Jill-Jênn Vie, Demian Wassermann, Arthur Mensch, Charlotte Caucheteux, Christian Haverkamp, Guillaume Lemaitre, Silvano Bosari, Ian D. Krantz, Andrew M. South, Tianxi Cai, Isaac S. Kohane:
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium. npj Digit. Medicine 3 (2020) - [c63]Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gaël Varoquaux:
Linear predictor on linearly-generated data with missing values: non consistency and solutions. AISTATS 2020: 3165-3174 - [c62]Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux:
NeuMiss networks: differentiable programming for supervised learning with missing values. NeurIPS 2020 - [i37]Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gaël Varoquaux:
Linear predictor on linearly-generated data with missing values: non consistency and solutions. CoRR abs/2002.00658 (2020) - [i36]Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux:
Neumann networks: differential programming for supervised learning with missing values. CoRR abs/2007.01627 (2020) - [i35]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
A Lightweight Neural Model for Biomedical Entity Linking. CoRR abs/2012.08844 (2020)
2010 – 2019
- 2019
- [j41]Mehdi Rahim, Bertrand Thirion, Gaël Varoquaux:
Population shrinkage of covariance (PoSCE) for better individual brain functional-connectivity estimation. Medical Image Anal. 54: 138-148 (2019) - [j40]Kamalaker Dadi, Mehdi Rahim, Alexandre Abraham, Darya Chyzhyk, Michael P. Milham, Bertrand Thirion, Gaël Varoquaux:
Benchmarking functional connectome-based predictive models for resting-state fMRI. NeuroImage 192: 115-134 (2019) - [j39]Andrés Hoyos Idrobo, Gaël Varoquaux, Jonas Kahn, Bertrand Thirion:
Recursive Nearest Agglomeration (ReNA): Fast Clustering for Approximation of Structured Signals. IEEE Trans. Pattern Anal. Mach. Intell. 41(3): 669-681 (2019) - [c61]Sergül Aydöre, Bertrand Thirion, Gaël Varoquaux:
Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data. ICML 2019: 385-394 - [c60]David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann:
Manifold-regression to predict from MEG/EEG brain signals without source modeling. NeurIPS 2019: 7321-7332 - [c59]Meyer Scetbon, Gaël Varoquaux:
Comparing distributions: 퓁1 geometry improves kernel two-sample testing. NeurIPS 2019: 12306-12316 - [i34]Julie Josse, Nicolas Prost, Erwan Scornet, Gaël Varoquaux:
On the consistency of supervised learning with missing values. CoRR abs/1902.06931 (2019) - [i33]David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann:
Manifold-regression to predict from MEG/EEG brain signals without source modeling. CoRR abs/1906.02687 (2019) - [i32]Patricio Cerda, Gaël Varoquaux:
Encoding high-cardinality string categorical variables. CoRR abs/1907.01860 (2019) - [i31]Meyer Scetbon, Gaël Varoquaux:
Comparing distributions: 𝓁1 geometry improves kernel two-sample testing. CoRR abs/1909.09264 (2019) - 2018
- [j38]Patricio Cerda, Gaël Varoquaux, Balázs Kégl:
Similarity encoding for learning with dirty categorical variables. Mach. Learn. 107(8-10): 1477-1494 (2018) - [j37]Gaël Varoquaux:
Cross-validation failure: Small sample sizes lead to large error bars. NeuroImage 180(Part): 68-77 (2018) - [j36]Andrés Hoyos Idrobo, Gaël Varoquaux, Yannick Schwartz, Bertrand Thirion:
FReM - Scalable and stable decoding with fast regularized ensemble of models. NeuroImage 180(Part): 160-172 (2018) - [j35]João Loula, Gaël Varoquaux, Bertrand Thirion:
Decoding fMRI activity in the time domain improves classification performance. NeuroImage 180(Part): 203-210 (2018) - [j34]Gaël Varoquaux, Yannick Schwartz, Russell A. Poldrack, Baptiste Gauthier, Danilo Bzdok, Jean-Baptiste Poline, Bertrand Thirion:
Atlases of cognition with large-scale human brain mapping. PLoS Comput. Biol. 14(11) (2018) - [j33]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Stochastic Subsampling for Factorizing Huge Matrices. IEEE Trans. Signal Process. 66(1): 113-128 (2018) - [c58]Jérôme Dockès, Demian Wassermann, Russell A. Poldrack, Fabian M. Suchanek, Bertrand Thirion, Gaël Varoquaux:
Text to Brain: Predicting the Spatial Distribution of Neuroimaging Observations from Text Reports. MICCAI (3) 2018: 584-592 - [c57]Darya Chyzhyk, Gaël Varoquaux, Bertrand Thirion, Michael P. Milham:
Controlling a confound in predictive models with a test set minimizing its effect. PRNI 2018: 1-4 - [i30]Patricio Cerda, Gaël Varoquaux, Balázs Kégl:
Similarity encoding for learning with dirty categorical variables. CoRR abs/1806.00979 (2018) - [i29]Jérôme Dockès, Demian Wassermann, Russell A. Poldrack, Fabian M. Suchanek, Bertrand Thirion, Gaël Varoquaux:
Text to brain: predicting the spatial distribution of neuroimaging observations from text reports. CoRR abs/1806.01139 (2018) - [i28]Sergül Aydöre, Bertrand Thirion, Olivier Grisel, Gaël Varoquaux:
Using Feature Grouping as a Stochastic Regularizer for High-Dimensional Noisy Data. CoRR abs/1807.11718 (2018) - [i27]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Extracting Universal Representations of Cognition across Brain-Imaging Studies. CoRR abs/1809.06035 (2018) - [i26]Andre Manoel, Florent Krzakala, Gaël Varoquaux, Bertrand Thirion, Lenka Zdeborová:
Approximate message-passing for convex optimization with non-separable penalties. CoRR abs/1809.06304 (2018) - [i25]Russell A. Poldrack, Krzysztof J. Gorgolewski, Gaël Varoquaux:
Computational and informatics advances for reproducible data analysis in neuroimaging. CoRR abs/1809.10024 (2018) - 2017
- [j32]Gaël Varoquaux, Pradeep Reddy Raamana, Denis A. Engemann, Andrés Hoyos Idrobo, Yannick Schwartz, Bertrand Thirion:
Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines. NeuroImage 145: 166-179 (2017) - [j31]Alexandre Abraham, Michael P. Milham, Adriana Di Martino, R. Cameron Craddock, Dimitris Samaras, Bertrand Thirion, Gaël Varoquaux:
Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example. NeuroImage 147: 736-745 (2017) - [j30]Franziskus Liem, Gaël Varoquaux, Jana Kynast, Frauke Beyer, Shahrzad Kharabian Masouleh, Julia M. Huntenburg, Leonie Lampe, Mehdi Rahim, Alexandre Abraham, R. Cameron Craddock, Steffi Riedel-Heller, Tobias Luck, Markus Loeffler, Matthias L. Schroeter, Anja Veronica Witte, Arno Villringer, Daniel S. Margulies:
Predicting brain-age from multimodal imaging data captures cognitive impairment. NeuroImage 148: 179-188 (2017) - [j29]Michael Eickenberg, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion:
Seeing it all: Convolutional network layers map the function of the human visual system. NeuroImage 152: 184-194 (2017) - [j28]Mehdi Rahim, Bertrand Thirion, Danilo Bzdok, Irène Buvat, Gaël Varoquaux:
Joint prediction of multiple scores captures better individual traits from brain images. NeuroImage 158: 145-154 (2017) - [j27]Krzysztof J. Gorgolewski, Fidel Alfaro-Almagro, Tibor Auer, Pierre Bellec, Mihai Capota, M. Mallar Chakravarty, Nathan William Churchill, Alexander Li Cohen, R. Cameron Craddock, Gabriel A. Devenyi, Anders Eklund, Oscar Esteban, Guillaume Flandin, Satrajit S. Ghosh, J. Swaroop Guntupalli, Mark Jenkinson, Anisha Keshavan, Gregory Kiar, Franziskus Liem, Pradeep Reddy Raamana, David Raffelt, Christopher John Steele, Pierre-Olivier Quirion, Robert E. Smith, Stephen C. Strother, Gaël Varoquaux, Yida Wang, Tal Yarkoni, Russell A. Poldrack:
BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods. PLoS Comput. Biol. 13(3) (2017) - [c56]Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko:
Learning to Discover Sparse Graphical Models. ICLR (Workshop) 2017 - [c55]Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko:
Learning to Discover Sparse Graphical Models. ICML 2017: 440-448 - [c54]Danilo Bzdok, Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion:
Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging. IPMI 2017: 323-335 - [c53]Mehdi Rahim, Bertrand Thirion, Gaël Varoquaux:
Population-Shrinkage of Covariance to Estimate Better Brain Functional Connectivity. MICCAI (1) 2017: 460-468 - [c52]Arthur Mensch, Julien Mairal, Danilo Bzdok, Bertrand Thirion, Gaël Varoquaux:
Learning Neural Representations of Human Cognition across Many fMRI Studies. NIPS 2017: 5883-5893 - [c51]Andrés Hoyos Idrobo, Gaël Varoquaux, Bertrand Thirion:
Towards a faster randomized parcellation based inference. PRNI 2017: 1-4 - [c50]Mehdi Rahim, Bertrand Thirion, Gaël Varoquaux:
Multi-output predictions from neuroimaging: assessing reduced-rank linear models. PRNI 2017: 1-4 - [i24]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Stochastic Subsampling for Factorizing Huge Matrices. CoRR abs/1701.05363 (2017) - [i23]Arthur Mensch, Julien Mairal, Danilo Bzdok, Bertrand Thirion, Gaël Varoquaux:
Learning Neural Representations of Human Cognition across Many fMRI Studies. CoRR abs/1710.11438 (2017) - [i22]Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort:
Convolutional Network Layers Map the Function of the Human Visual Cortex. ERCIM News 2017(108) (2017) - [i21]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Subsampling Enables Fast Factorisation of Huge Matrices into Sparse Signals. ERCIM News 2017(108) (2017) - 2016
- [j26]Mehdi Rahim, Bertrand Thirion, Claude Comtat, Gaël Varoquaux:
Transmodal Learning of Functional Networks for Alzheimer's Disease Prediction. IEEE J. Sel. Top. Signal Process. 10(7): 1204-1213 (2016) - [j25]Krzysztof J. Gorgolewski, Gaël Varoquaux, Gabriel Rivera, Yannick Schwartz, Vanessa V. Sochat, Satrajit S. Ghosh, Camille Maumet, Thomas E. Nichols, Jean-Baptiste Poline, Tal Yarkoni, Daniel S. Margulies, Russell A. Poldrack:
NeuroVault.org: A repository for sharing unthresholded statistical maps, parcellations, and atlases of the human brain. NeuroImage 124: 1242-1244 (2016) - [j24]M. Florencia Assaneo, Jacobo D. Sitt, Gaël Varoquaux, Mariano Sigman, Laurent Cohen, Marcos Alberto Trevisan:
Exploring the anatomical encoding of voice with a mathematical model of the vocal system. NeuroImage 141: 31-39 (2016) - [j23]Danilo Bzdok, Gaël Varoquaux, Olivier Grisel, Michael Eickenberg, Cyril Poupon, Bertrand Thirion:
Formal Models of the Network Co-occurrence Underlying Mental Operations. PLoS Comput. Biol. 12(6) (2016) - [j22]Bernard Ng, Gaël Varoquaux, Jean-Baptiste Poline, Michael D. Greicius, Bertrand Thirion:
Transport on Riemannian Manifold for Connectivity-Based Brain Decoding. IEEE Trans. Medical Imaging 35(1): 208-216 (2016) - [c49]Elvis Dohmatob, Michael Eickenberg, Bertrand Thirion, Gaël Varoquaux:
Local Q-linear convergence and finite-time active set identification of ADMM on a class of penalized regression problems. ICASSP 2016: 4752-4756 - [c48]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Dictionary Learning for Massive Matrix Factorization. ICML 2016: 1737-1746 - [c47]Arthur Mensch, Gaël Varoquaux, Bertrand Thirion:
Compressed online dictionary learning for fast resting-state fMRI decomposition. ISBI 2016: 1282-1285 - [c46]Eugene Belilovsky, Gaël Varoquaux, Matthew B. Blaschko:
Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity. NIPS 2016: 595-603 - [c45]Elvis Dohmatob, Arthur Mensch, Gaël Varoquaux, Bertrand Thirion:
Learning brain regions via large-scale online structured sparse dictionary learning. NIPS 2016: 4610-4618 - [c44]Kamalaker Dadi, Alexandre Abraham, Mehdi Rahim, Bertrand Thirion, Gaël Varoquaux:
Comparing functional connectivity based predictive models across datasets. PRNI 2016: 1-4 - [c43]Andrés Hoyos Idrobo, Gaël Varoquaux, Bertrand Thirion:
Fast brain decoding with random sampling and random projections. PRNI 2016: 1-4 - [c42]Gaël Varoquaux, Matthieu Kowalski, Bertrand Thirion:
Social-sparsity brain decoders: faster spatial sparsity. PRNI 2016: 1-4 - [i20]Arthur Mensch, Gaël Varoquaux, Bertrand Thirion:
Compressed Online Dictionary Learning for Fast fMRI Decomposition. CoRR abs/1602.02701 (2016) - [i19]Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux:
Dictionary Learning for Massive Matrix Factorization. CoRR abs/1605.00937 (2016) - [i18]Gaël Varoquaux, Matthieu Kowalski, Bertrand Thirion:
Social-sparsity brain decoders: faster spatial sparsity. CoRR abs/1606.06439 (2016) - [i17]Andrés Hoyos Idrobo, Gaël Varoquaux, Jonas Kahn, Bertrand Thirion:
Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signals. CoRR abs/1609.04608 (2016) - 2015
- [j21]Krzysztof J. Gorgolewski, Gaël Varoquaux, Gabriel Rivera, Yannick Schwartz, Satrajit S. Ghosh, Camille Maumet, Vanessa V. Sochat, Thomas E. Nichols, Russell A. Poldrack, Jean-Baptiste Poline, Tal Yarkoni, Daniel S. Margulies:
NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain. Frontiers Neuroinformatics 9: 8 (2015) - [j20]Eugene Belilovsky, Andreas Argyriou, Gaël Varoquaux, Matthew B. Blaschko:
Convex relaxations of penalties for sparse correlated variables with bounded total variation. Mach. Learn. 100(2-3): 533-553 (2015) - [j19]Virgile Fritsch, Benoit Da Mota, Eva Loth, Gaël Varoquaux, Tobias Banaschewski, Gareth J. Barker, Arun L. W. Bokde, Rüdiger Brühl, Brigitte Butzek, Patricia J. Conrod, Herta Flor, Hugh Garavan, Hervé Lemaître, Karl Mann, Frauke Nees, Tomás Paus, Daniel J. Schad, Gunter Schümann, Vincent Frouin, Jean-Baptiste Poline, Bertrand Thirion:
Robust regression for large-scale neuroimaging studies. NeuroImage 111: 431-441 (2015) - [j18]Gaël Varoquaux, Lars Buitinck, Gilles Louppe, Olivier Grisel, Fabian Pedregosa, Andreas Mueller:
Scikit-learn: Machine Learning Without Learning the Machinery. GetMobile Mob. Comput. Commun. 19(1): 29-33 (2015) - [c41]Mehdi Rahim, Bertrand Thirion, Alexandre Abraham, Michael Eickenberg, Elvis Dohmatob, Claude Comtat, Gaël Varoquaux:
Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer's Disease. MICCAI (1) 2015: 207-214 - [c40]Michael Eickenberg, Elvis Dohmatob, Bertrand Thirion, Gaël Varoquaux:
Grouping Total Variation and Sparsity: Statistical Learning with Segmenting Penalties. MICCAI (1) 2015: 685-693 - [c39]Danilo Bzdok, Michael Eickenberg, Olivier Grisel, Bertrand Thirion, Gaël Varoquaux:
Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data. NIPS 2015: 3348-3356 - [c38]Elvis Dohmatob, Michael Eickenberg, Bertrand Thirion, Gaël Varoquaux:
Speeding-Up Model-Selection in Graphnet via Early-Stopping and Univariate Feature-Screening. PRNI 2015: 17-20 - [c37]Andrés Hoyos Idrobo, Yannick Schwartz, Gaël Varoquaux, Bertrand Thirion:
Improving Sparse Recovery on Structured Images with Bagged Clustering. PRNI 2015: 73-76 - [i16]Bertrand Thirion, Andrés Hoyos Idrobo, Jonas Kahn, Gaël Varoquaux:
Fast clustering for scalable statistical analysis on structured images. CoRR abs/1511.04898 (2015) - [i15]