Gaël Varoquaux

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 114

Top Venues

Publications

Lihu Chen, Alexandre Perez-Lebel, Fabian M. Suchanek, Gaël Varoquaux
Reconfidencing LLMs from the Grouping Loss Perspective. CoRR (2024)
Marine Le Morvan, Gaël Varoquaux
Imputation for prediction: beware of diminishing returns. CoRR (2024)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
Learning High-Quality and General-Purpose Phrase Representations. EACL (Findings) (2024)
Myung Jun Kim, Léo Grinsztajn, Gaël Varoquaux
CARTE: pretraining and transfer for tabular learning. CoRR (2024)
Julie Alberge, Vincent Maladière, Olivier Grisel, Judith Abécassis, Gaël Varoquaux
Teaching Models To Survive: Proper Scoring Rule and Stochastic Optimization with Competing Risks. CoRR (2024)
Riccardo Cappuzzo, Gaël Varoquaux, Aimee Coelho, Paolo Papotti
Retrieve, Merge, Predict: Augmenting Tables with Data Lakes. CoRR (2024)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
Learning High-Quality and General-Purpose Phrase Representations. CoRR (2024)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
The Locality and Symmetry of Positional Encodings. CoRR (2023)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
GLADIS: A General and Large Acronym Disambiguation Benchmark. EACL (2023)
Léo Grinsztajn, Edouard Oyallon, Myung Jun Kim, Gaël Varoquaux
Vectorizing string entries for data processing on tables: when are larger language models better? CoRR (2023)
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 (2023)
Rosana El Jurdi, Gaël Varoquaux, Olivier Colliot
Confidence intervals for performance estimates in 3D medical image segmentation. CoRR (2023)
Alexandre Perez-Lebel, Marine Le Morvan, Gaël Varoquaux
Beyond calibration: estimating the grouping loss of modern neural networks. ICLR (2023)
Alexis Cvetkov-Iliev, Alexandre Allauzen, Gaël Varoquaux
Relational data embeddings for feature enrichment with background information. Mach. Learn. 112 (2) (2023)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
GLADIS: A General and Large Acronym Disambiguation Benchmark. CoRR (2023)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
The Locality and Symmetry of Positional Encodings. EMNLP (Findings) (2023)
Alexandre Perez-Lebel, Gaël Varoquaux, Marine Le Morvan, Julie Josse, Jean-Baptiste Poline
Benchmarking missing-values approaches for predictive models on health databases. CoRR (2022)
Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux
Why do tree-based models still outperform deep learning on typical tabular data? NeurIPS (2022)
Gaël Varoquaux, Veronika Cheplygina
Machine learning for medical imaging: methodological failures and recommendations for the future. npj Digit. Medicine 5 (2022)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost. CoRR (2022)
Patricio Cerda, Gaël Varoquaux
Encoding High-Cardinality String Categorical Variables. IEEE Trans. Knowl. Data Eng. 34 (3) (2022)
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 (2022)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
Imputing Out-of-Vocabulary Embeddings with LOVE Makes LanguageModels Robust with Little Cost. ACL (1) (2022)
Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux
Why do tree-based models still outperform deep learning on tabular data? CoRR (2022)
Alexandre Perez-Lebel, Marine Le Morvan, Gaël Varoquaux
Beyond calibration: estimating the grouping loss of modern neural networks. CoRR (2022)
Alexis Cvetkov-Iliev, Alexandre Allauzen, Gaël Varoquaux
Analytics on Non-Normalized Data Sources: More Learning, Rather Than More Cleaning. IEEE Access 10 (2022)
Griffin M. Weber, Chuan Hong, Zongqi Xia, Nathan P. Palmer, Paul Avillach, Sehi L'Yi, Mark S. Keller, Shawn N. Murphy, Alba Gutiérrez-Sacristán, Clara-Lea Bonzel, Arnaud Serret-Larmande, Antoine Neuraz, Gilbert S. Omenn, Shyam Visweswaran, Jeffrey G. Klann, Andrew M. South, Ne-Hooi Will Loh, Mario Cannataro, Brett K. Beaulieu-Jones, Riccardo Bellazzi, Giuseppe Agapito, Mario Alessiani, Bruce J. Aronow, Douglas S. Bell, Vincent Benoit, Florence T. Bourgeois, Luca Chiovato, Kelly Cho, Arianna Dagliati, Scott L. DuVall, Noelia García-Barrio, David A. Hanauer, Yuk-Lam Ho, John H. Holmes, Richard W. Issitt, Molei Liu, Yuan Luo, Kristine E. Lynch, Sarah Maidlow, Alberto Malovini, Kenneth D. Mandl, Chengsheng Mao, Michael E. Matheny, Jason H. Moore, Jeffrey S. Morris, Michele Morris, Danielle L. Mowery, Kee Yuan Ngiam, Lav P. Patel, Miguel Pedrera-Jiménez, Rachel B. Ramoni, Emily Schriver, Petra Schubert, Pablo Serrano-Balazote, Anastasia Spiridou, Amelia L. M. Tan, Byorn W. L. Tan, Valentina Tibollo, Carlo Torti, Enrico M. Trecarichi, Xuan Wang, James R. Aaron, Adem Albayrak, Giuseppe Albi, Anna Alloni, Danilo F. Amendola, François Angoulvant, Anthony L. L. J. Li, Fatima Ashraf, Andrew Atz, Paul Avillach, Paula S. Azevedo, James Balshi, Brett K. Beaulieu-Jones, Antonio Bellasi, Vincent Benoit, Michele Beraghi, José Luis Bernal-Sobrino, Mélodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Javier Blanco-Martínez, Martin Boeker, John Booth, Silvano Bosari, Robert L. Bradford, Gabriel A. Brat, Stéphane Bréant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Emily Bucholz, Anita Burgun, Tianxi Cai, Aldo Carmona, Charlotte Caucheteux, Julien Champ, Krista Y. Chen, Jin Chen, Lorenzo Chiudinelli, Kelly Cho, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sébastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermúdez, Jaime Cruz-Rojo, Mohamad Daniar, Christel Daniel, Priyam Das, Batsal Devkota, Audrey Dionne, Rui Duan, Julien Dubiel, Loic Esteve, Hossein Estiri, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Noelia García-Barrio, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Alba Gutiérrez-Sacristán, Larry Han, David A. Hanauer, Christian Haverkamp, Derek Y. Hazard, Bing He, Darren W. Henderson, Martin Hilka, Kenneth M. Huling, Meghan R. Hutch, Richard W. Issitt, Anne-Sophie Jannot, Vianney Jouhet, Ramakanth Kavuluru, Chris J. Kennedy, Kate F. Kernan, Daniel A. Key, Katie Kirchoff, Jeffrey G. Klann, Isaac S. Kohane, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Trang T. Le, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Qi Long, Sara Lozano-Zahonero, Sadiqa Mahmood, Sarah Maidlow, Adeline Makoudjou, Anupama Maram, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Bertrand Moal, Taha Mohseni Ahooyi, Jason H. Moore, Cinta Moraleda, Jeffrey S. Morris, Karyn L. Moshal, Sajad Mousavi, Douglas A. Murad, Shawn N. Murphy, Thomas Naughton, Carlos Tadeu Breda Neto, Jane Newburger, Kee Yuan Ngiam, Wanjiku F. M. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Gilbert S. Omenn, Nina Orlova, Brian Ostasiewski, Nathan P. Palmer, Nicolas Paris, Lav P. Patel, Miguel Pedrera-Jiménez, Ashley C. Pfaff, Emily R. Pfaff, Danielle Pillion, Sara Pizzimenti, Hans-Ulrich Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Rachel B. Ramoni, 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, Amelia L. M. Tan, 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, Shyam Visweswaran, Michele Vitacca, Kavishwar B. Wagholikar, Lemuel R. Waitman, Demian Wassermann, Griffin M. Weber, Martin Wolkewitz, Scott Wong, Zongqi Xia, Xin Xiong, Ye Ye, Nadir Yehya, William Yuan, Alberto Zambelli, Harrison G. Zhang, Daniela Zöller, Valentina Zuccaro, Chiara Zucco, Isaac S. Kohane, Tianxi Cai, Gabriel A. Brat
International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality. npj Digit. Medicine 5 (2022)
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 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 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 (2022)
Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux
What's a good imputation to predict with missing values? NeurIPS (2021)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
A Lightweight Neural Model for Biomedical Entity Linking. AAAI (2021)
Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux
What's a good imputation to predict with missing values? CoRR (2021)
Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux
Extracting representations of cognition across neuroimaging studies improves brain decoding. PLoS Comput. Biol. 17 (5) (2021)
Gaël Varoquaux, Veronika Cheplygina
How I failed machine learning in medical imaging - shortcomings and recommendations. CoRR (2021)
Jérôme Dockès, Gaël Varoquaux, Jean-Baptiste Poline
Preventing dataset shift from breaking machine-learning biomarkers. CoRR (2021)
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)
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 (2021)
Marc-Andre Schulz, Bertrand Thirion, Alexandre Gramfort, Gaël Varoquaux, Danilo Bzdok
Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction. CoRR (2021)
Jérôme-Alexis Chevalier, Tuan-Binh Nguyen, Joseph Salmon, Gaël Varoquaux, Bertrand Thirion
Decoding with confidence: Statistical control on decoder maps. NeuroImage 234 (2021)
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)
Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux
Neumann networks: differential programming for supervised learning with missing values. CoRR (2020)
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 Kirchoff, Jean B. Craig, Jihad 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)
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 (2020)
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 (2020)
Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux
NeuMiss networks: differentiable programming for supervised learning with missing values. NeurIPS (2020)
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 (2020)
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
A Lightweight Neural Model for Biomedical Entity Linking. CoRR (2020)
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) (2019)
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)
Meyer Scetbon, Gaël Varoquaux
geometry improves kernel two-sample testing. CoRR (2019)
Meyer Scetbon, Gaël Varoquaux
geometry improves kernel two-sample testing. NeurIPS (2019)
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 (2019)
Patricio Cerda, Gaël Varoquaux
Encoding high-cardinality string categorical variables. CoRR (2019)
Sergül Aydöre, Bertrand Thirion, Gaël Varoquaux
Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data. ICML (2019)
Julie Josse, Nicolas Prost, Erwan Scornet, Gaël Varoquaux
On the consistency of supervised learning with missing values. CoRR (2019)
Mehdi Rahim, Bertrand Thirion, Gaël Varoquaux
Population shrinkage of covariance (PoSCE) for better individual brain functional-connectivity estimation. Medical Image Anal. 54 (2019)
David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann
Manifold-regression to predict from MEG/EEG brain signals without source modeling. CoRR (2019)
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)
Patricio Cerda, Gaël Varoquaux, Balázs Kégl
Similarity encoding for learning with dirty categorical variables. CoRR (2018)
Darya Chyzhyk, Gaël Varoquaux, Bertrand Thirion, Michael P. Milham
Controlling a confound in predictive models with a test set minimizing its effect. PRNI (2018)
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)
Andre Manoel, Florent Krzakala, Gaël Varoquaux, Bertrand Thirion, Lenka Zdeborová
Approximate message-passing for convex optimization with non-separable penalties. CoRR (2018)
João Loula, Gaël Varoquaux, Bertrand Thirion
Decoding fMRI activity in the time domain improves classification performance. NeuroImage 180 (Part) (2018)
Andrés Hoyos Idrobo, Gaël Varoquaux, Yannick Schwartz, Bertrand Thirion
FReM - Scalable and stable decoding with fast regularized ensemble of models. NeuroImage 180 (Part) (2018)
Russell A. Poldrack, Krzysztof J. Gorgolewski, Gaël Varoquaux
Computational and informatics advances for reproducible data analysis in neuroimaging. CoRR (2018)
Sergül Aydöre, Bertrand Thirion, Olivier Grisel, Gaël Varoquaux
Using Feature Grouping as a Stochastic Regularizer for High-Dimensional Noisy Data. CoRR (2018)
Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux
Extracting Universal Representations of Cognition across Brain-Imaging Studies. CoRR (2018)
Gaël Varoquaux
Cross-validation failure: Small sample sizes lead to large error bars. NeuroImage 180 (Part) (2018)
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 (2018)
Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux
Stochastic Subsampling for Factorizing Huge Matrices. IEEE Trans. Signal Process. 66 (1) (2018)
Patricio Cerda, Gaël Varoquaux, Balázs Kégl
Similarity encoding for learning with dirty categorical variables. Mach. Learn. 107 (8-10) (2018)
Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux
Subsampling Enables Fast Factorisation of Huge Matrices into Sparse Signals. ERCIM News 2017 (108) (2017)
Mehdi Rahim, Bertrand Thirion, Gaël Varoquaux
Population-Shrinkage of Covariance to Estimate Better Brain Functional Connectivity. MICCAI (1) (2017)
Arthur Mensch, Julien Mairal, Danilo Bzdok, Bertrand Thirion, Gaël Varoquaux
Learning Neural Representations of Human Cognition across Many fMRI Studies. NIPS (2017)
Michael Eickenberg, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion
Seeing it all: Convolutional network layers map the function of the human visual system. NeuroImage 152 (2017)
Danilo Bzdok, Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion
Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging. IPMI (2017)
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 (2017)
Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko
Learning to Discover Sparse Graphical Models. ICLR (Workshop) (2017)
Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort
Convolutional Network Layers Map the Function of the Human Visual Cortex. ERCIM News 2017 (108) (2017)
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 (2017)
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)
Mehdi Rahim, Bertrand Thirion, Gaël Varoquaux
Multi-output predictions from neuroimaging: assessing reduced-rank linear models. PRNI (2017)
Andrés Hoyos Idrobo, Gaël Varoquaux, Bertrand Thirion
Towards a faster randomized parcellation based inference. PRNI (2017)
Arthur Mensch, Julien Mairal, Danilo Bzdok, Bertrand Thirion, Gaël Varoquaux
Learning Neural Representations of Human Cognition across Many fMRI Studies. CoRR (2017)
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 (2017)
Mehdi Rahim, Bertrand Thirion, Danilo Bzdok, Irène Buvat, Gaël Varoquaux
Joint prediction of multiple scores captures better individual traits from brain images. NeuroImage 158 (2017)
Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux
Stochastic Subsampling for Factorizing Huge Matrices. CoRR (2017)
Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko
Learning to Discover Sparse Graphical Models. ICML (2017)
Andrés Hoyos Idrobo, Gaël Varoquaux, Jonas Kahn, Bertrand Thirion
Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signals. CoRR (2016)
Arthur Mensch, Gaël Varoquaux, Bertrand Thirion
Compressed Online Dictionary Learning for Fast fMRI Decomposition. CoRR (2016)
Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux
Dictionary Learning for Massive Matrix Factorization. ICML (2016)
Arthur Mensch, Gaël Varoquaux, Bertrand Thirion
Compressed online dictionary learning for fast resting-state fMRI decomposition. ISBI (2016)
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)
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) (2016)
Gaël Varoquaux, Matthieu Kowalski, Bertrand Thirion
Social-sparsity brain decoders: faster spatial sparsity. CoRR (2016)
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) (2016)
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 (2016)
Eugene Belilovsky, Gaël Varoquaux, Matthew B. Blaschko
Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity. NIPS (2016)
Andrés Hoyos Idrobo, Gaël Varoquaux, Bertrand Thirion
Fast brain decoding with random sampling and random projections. PRNI (2016)
Kamalaker Dadi, Alexandre Abraham, Mehdi Rahim, Bertrand Thirion, Gaël Varoquaux
Comparing functional connectivity based predictive models across datasets. PRNI (2016)
M. Florencia Assaneo, Jacobo 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 (2016)

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Gaël Varoquaux