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Gaël Varoquaux
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- affiliation: Inria Saclay, Palaiseau, France
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2020 – today
- 2024
- [c75]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
Learning High-Quality and General-Purpose Phrase Representations. EACL (Findings) 2024: 983-994 - [c74]Lihu Chen, Alexandre Perez-Lebel, Fabian M. Suchanek, Gaël Varoquaux:
Reconfidencing LLMs from the Grouping Loss Perspective. EMNLP (Findings) 2024: 1567-1581 - [c73]Myung Jun Kim, Léo Grinsztajn, Gaël Varoquaux:
CARTE: Pretraining and Transfer for Tabular Learning. ICML 2024 - [c72]Evangelia Christodoulou, Annika Reinke, Rola Houhou, Piotr Kalinowski, Selen Erkan, Carole H. Sudre, Ninon Burgos, Sofiène Boutaj, Sophie Loizillon, Maëlys Solal, Nicola Rieke, Veronika Cheplygina, Michela Antonelli, Leon D. Mayer, Minu Dietlinde Tizabi, M. Jorge Cardoso, Amber L. Simpson, Paul F. Jäger, Annette Kopp-Schneider, Gaël Varoquaux, Olivier Colliot, Lena Maier-Hein:
Confidence Intervals Uncovered: Are We Ready for Real-World Medical Imaging AI? MICCAI (10) 2024: 124-132 - [i62]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
Learning High-Quality and General-Purpose Phrase Representations. CoRR abs/2401.10407 (2024) - [i61]Lihu Chen, Alexandre Perez-Lebel, Fabian M. Suchanek, Gaël Varoquaux:
Reconfidencing LLMs from the Grouping Loss Perspective. CoRR abs/2402.04957 (2024) - [i60]Riccardo Cappuzzo, Gaël Varoquaux, Aimee Coelho, Paolo Papotti:
Retrieve, Merge, Predict: Augmenting Tables with Data Lakes. CoRR abs/2402.06282 (2024) - [i59]Myung Jun Kim, Léo Grinsztajn, Gaël Varoquaux:
CARTE: pretraining and transfer for tabular learning. CoRR abs/2402.16785 (2024) - [i58]Julie Alberge, Vincent Maladière, Olivier Grisel, Judith Abécassis, Gaël Varoquaux:
Teaching Models To Survive: Proper Scoring Rule and Stochastic Optimization with Competing Risks. CoRR abs/2406.14085 (2024) - [i57]Marine Le Morvan, Gaël Varoquaux:
Imputation for prediction: beware of diminishing returns. CoRR abs/2407.19804 (2024) - [i56]Lihu Chen, Gaël Varoquaux:
What is the Role of Small Models in the LLM Era: A Survey. CoRR abs/2409.06857 (2024) - [i55]Gaël Varoquaux, Alexandra Sasha Luccioni, Meredith Whittaker:
Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI. CoRR abs/2409.14160 (2024) - [i54]Julie Alberge, Vincent Maladière, Olivier Grisel, Judith Abécassis, Gaël Varoquaux:
Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks. CoRR abs/2410.16765 (2024) - 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) - [c71]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
GLADIS: A General and Large Acronym Disambiguation Benchmark. EACL 2023: 2065-2080 - [c70]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
The Locality and Symmetry of Positional Encodings. EMNLP (Findings) 2023: 14313-14331 - [c69]Alexandre Perez-Lebel, Marine Le Morvan, Gaël Varoquaux:
Beyond calibration: estimating the grouping loss of modern neural networks. ICLR 2023 - [d69]Matthew Brett
nipy/nibabel: 5.1.0. Version 5.1.0. Zenodo, 2023 [all versions] - [d68]Matthew Brett
nipy/nibabel: 5.0.0. Version 5.0.0. Zenodo, 2023 [all versions] - [d67]Matthew Brett
nipy/nibabel: 5.0.1. Version 5.0.1. Zenodo, 2023 [all versions] - [d66]Matthew Brett
nipy/nibabel: 5.2.0. Version 5.2.0. Zenodo, 2023 [all versions] - [d65]Nilearn Contributors, Ahmad Chamma
nilearn. Zenodo, 2023 - [d64]Aaron Oliver-Taylor, Adam Li, Adam G. Thomas
bids-specification. Zenodo, 2023 - [d63]Thomas Petit-Jean
eds-scikit: data analysis on OMOP databases. Version v0.1.3. Zenodo, 2023 [all versions] - [d62]Thomas Petit-Jean
eds-scikit: data analysis on OMOP databases. Version v0.1.4. Zenodo, 2023 [all versions] - [d61]Thomas Petit-Jean
eds-scikit: data analysis on OMOP databases. Version v0.1.5. Zenodo, 2023 [all versions] - [d60]Thomas Petit-Jean
eds-scikit: data analysis on OMOP databases. Version v0.1.6. Zenodo, 2023 [all versions] - [i53]Matthieu Doutreligne, Gaël Varoquaux:
How to select predictive models for causal inference? CoRR abs/2302.00370 (2023) - [i52]Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación
Understanding metric-related pitfalls in image analysis validation. CoRR abs/2302.01790 (2023) - [i51]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
GLADIS: A General and Large Acronym Disambiguation Benchmark. CoRR abs/2302.01860 (2023) - [i50]Rosana El Jurdi, Gaël Varoquaux, Olivier Colliot:
Confidence intervals for performance estimates in 3D medical image segmentation. CoRR abs/2307.10926 (2023) - [i49]Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek:
The Locality and Symmetry of Positional Encodings. CoRR abs/2310.12864 (2023) - [i48]Léo Grinsztajn, Edouard Oyallon, Myung Jun Kim, Gaël Varoquaux:
Vectorizing string entries for data processing on tables: when are larger language models better? CoRR abs/2312.09634 (2023) - 2022
- [j51]Alexis Cvetkov-Iliev
Analytics on Non-Normalized Data Sources: More Learning, Rather Than More Cleaning. IEEE Access 10: 42420-42431 (2022) - [j50]Nicolas Traut, Katja Heuer
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
International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality. npj Digit. Medicine 5 (2022) - [j47]Patricio Cerda
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 - [d59]Matthew Brett
nipy/nibabel: 3.2.2. Version 3.2.2. Zenodo, 2022 [all versions] - [d58]Matthew Brett
nipy/nibabel: 4.0.0rc0. Version 4.0.0rc0. Zenodo, 2022 [all versions] - [d57]Matthew Brett
nipy/nibabel. Version 4.0.0. Zenodo, 2022 [all versions] - [d56]Alexis Cvetkov-Iliev, Alexandre Allauzen, Gaël Varoquaux:
Employee salaries in Texas administrations. IEEE DataPort, 2022 - [d55]Oscar Esteban
nipy/nipype: 1.7.1. Version 1.7.1. Zenodo, 2022 [all versions] - [d54]Oscar Esteban
nipy/nipype: 1.8.0. Version 1.8.0. Zenodo, 2022 [all versions] - [d53]Oscar Esteban
nipy/nipype: 1.8.1. Version 1.8.1. Zenodo, 2022 [all versions] - [d52]Oscar Esteban
nipy/nipype: 1.8.3. Version 1.8.3. Zenodo, 2022 [all versions] - [d51]Thomas Petit-Jean
eds-scikit: data analysis on OMOP databases. Version v0.1.2. Zenodo, 2022 [all versions] - [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
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
Beyond calibration: estimating the grouping loss of modern neural networks. CoRR abs/2210.16315 (2022) - 2021
- [j46]Jérôme-Alexis Chevalier
Decoding with confidence: Statistical control on decoder maps. NeuroImage 234: 117921 (2021) - [j45]Arthur Mensch, Julien Mairal, Bertrand Thirion
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 - [d50]Oscar Esteban
nipy/nipype: 1.7.0. Version 1.7.0. Zenodo, 2021 [all versions] - [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
Fine-grain atlases of functional modes for fMRI analysis. NeuroImage 221: 117126 (2020) - [j43]David Sabbagh
Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states. NeuroImage 222: 116893 (2020) - [j42]Gabriel A. Brat
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 - [d49]Matthew Brett
nipy/nibabel: 2.5.2. Version 2.5.2. Zenodo, 2020 [all versions] - [d48]Matthew Brett
nipy/nibabel: 3.0.1. Version 3.0.1. Zenodo, 2020 [all versions] - [d47]Matthew Brett
nipy/nibabel: 3.0.2. Version 3.0.2. Zenodo, 2020 [all versions] - [d46]Matthew Brett
nipy/nibabel: 3.1.0. Version 3.1.0. Zenodo, 2020 [all versions] - [d45]Matthew Brett
nipy/nibabel: 3.1.1. Version 3.1.1. Zenodo, 2020 [all versions] - [d44]Matthew Brett
nipy/nibabel: 3.2.0. Version 3.2.0. Zenodo, 2020 [all versions] - [d43]Matthew Brett
nipy/nibabel: 3.2.1. Version 3.2.1. Zenodo, 2020 [all versions] - [d42]Oscar Esteban
nipy/nipype: 1.5.0. Version 1.5.0. Zenodo, 2020 [all versions] - [d41]Oscar Esteban
nipy/nipype: 1.5.1. Version 1.5.1. Zenodo, 2020 [all versions] - [d40]Oscar Esteban
nipy/nipype: 1.4.1. Version 1.4.1. Zenodo, 2020 [all versions] - [d39]Oscar Esteban
nipy/nipype: 1.4.2. Version 1.4.2. Zenodo, 2020 [all versions] - [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
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
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 - [d38]Matthew Brett
nipy/nibabel: 2.4.0. Version 2.4.0. Zenodo, 2019 [all versions] - [d37]Matthew Brett
nipy/nibabel: 2.4.1. Version 2.4.1. Zenodo, 2019 [all versions] - [d36]Matthew Brett
nipy/nibabel: 2.5.0. Version 2.5.0. Zenodo, 2019 [all versions] - [d35]Matthew Brett
nipy/nibabel: 2.5.1. Version 2.5.1. Zenodo, 2019 [all versions] - [d34]Matthew Brett
nipy/nibabel: 3.0.0rc1. Version 3.0.0rc1. Zenodo, 2019 [all versions] - [d33]Matthew Brett
nipy/nibabel: 3.0.0rc2. Version 3.0.0rc2. Zenodo, 2019 [all versions] - [d32]Matthew Brett
nipy/nibabel: 3.0.0. Version 3.0.0. Zenodo, 2019 [all versions] - [d31]Oscar Esteban
nipy/nipype: 1.4.0. Version 1.4.0. Zenodo, 2019 [all versions] - [d30]Oscar Esteban
nipy/nipype: 1.3.0-rc1. Version 1.3.0rc1. Zenodo, 2019 [all versions] - [d29]Oscar Esteban
nipy/nipype: 1.3.0. Version 1.3.0. Zenodo, 2019 [all versions] - [d28]Oscar Esteban
nipy/nipype: 1.2.3. Version 1.2.3. Zenodo, 2019 [all versions] - [d27]Krzysztof J. Gorgolewski
nipy/nipype: 1.2.1. Version 1.2.1. Zenodo, 2019 [all versions] - [d26]Krzysztof J. Gorgolewski
nipy/nipype: 1.2.2. Version 1.2.2. Zenodo, 2019 [all versions] - [d25]Krzysztof J. Gorgolewski
nipy/nipype: 1.2.2. Version 1.2.2. Zenodo, 2019 [all versions] - [d24]Krzysztof J. Gorgolewski
nipy/nipype: 1.1.8. Version 1.1.8. Zenodo, 2019 [all versions] - [d23]Krzysztof J. Gorgolewski
nipy/nipype: 1.1.9. Version 1.1.9. Zenodo, 2019 [all versions] - [d22]Krzysztof J. Gorgolewski
nipy/nipype: 1.2.0. Version 1.2.0. Zenodo, 2019 [all versions] - [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
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
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
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 - [d21]Krzysztof J. Gorgolewski
nipy/nipype: 1.1.3. Version 1.1.3. Zenodo, 2018 [all versions] - [d20]Krzysztof J. Gorgolewski
nipy/nipype: 1.1.4. Version 1.1.4. Zenodo, 2018 [all versions] - [d19]Krzysztof J. Gorgolewski
nipy/nipype: 1.1.5. Version 1.1.5. Zenodo, 2018 [all versions] - [d18]Krzysztof J. Gorgolewski
nipy/nipype: 1.1.6. Version 1.1.6. Zenodo, 2018 [all versions] - [d17]Krzysztof J. Gorgolewski
nipy/nipype: 1.1.7. Version 1.1.7. Zenodo, 2018 [all versions] - [d16]Krzysztof J. Gorgolewski
nipy/nipype: 1.0.4. Version 1.0.4. Zenodo, 2018 [all versions] - [d15]Krzysztof J. Gorgolewski
nipy/nipype: 1.0.4. Version 1.0.4. Zenodo, 2018 [all versions] - [d14]Krzysztof J. Gorgolewski
nipy/nipype: Nipype 1.1.0. Version 1.1.0. Zenodo, 2018 [all versions] - [d13]Krzysztof J. Gorgolewski
nipy/nipype: 1.1.1. Version 1.1.1. Zenodo, 2018 [all versions] - [d12]Krzysztof J. Gorgolewski
nipy/nipype: 1.1.2. Version 1.1.2. Zenodo, 2018 [all versions] - [d11]Krzysztof J. Gorgolewski
nipy/nipype: 1.0.2. Version 1.0.2. Zenodo, 2018 [all versions] - [d10]Krzysztof J. Gorgolewski
nipy/nipype: 1.0.1. Version 1.0.1. Zenodo, 2018 [all versions] - [d9]Krzysztof J. Gorgolewski
nipy/nipype: Nipype 1.0.3. Version 1.0.3. Zenodo, 2018 [all versions] - [d8]Krzysztof J. Gorgolewski
nipy/nipype: Nipype - v1.0.0. Version v1.0.0. Zenodo, 2018 [all versions] - [d7]Nicolas Traut
IMaging-PsychiAtry Challenge rfMRI data. Zenodo, 2018 - [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
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
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
Predicting brain-age from multimodal imaging data captures cognitive impairment. NeuroImage 148: 179-188 (2017) - [j29]Michael Eickenberg, Alexandre Gramfort
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
Joint prediction of multiple scores captures better individual traits from brain images. NeuroImage 158: 145-154 (2017) - [j27]Krzysztof J. Gorgolewski
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 - [d6]Krzysztof J. Gorgolewski
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.0. Version 0.13.0. Zenodo, 2017 [all versions] - [d5]Krzysztof J. Gorgolewski
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.1. Version 0.13.1. Zenodo, 2017 [all versions] - [d4]Krzysztof J. Gorgolewski
nipy/nipype: 0.14.0-rc1. Version 0.14.0-rc1. Zenodo, 2017 [all versions] - [d3]Krzysztof J. Gorgolewski
nipy/nipype: 0.14.0-rc1. Version 0.14.0-rc1. Zenodo, 2017 [all versions] - [d2]Krzysztof J. Gorgolewski
nipy/nipype: 0.14.0. Version v0.14.0. Zenodo, 2017 [all versions] - [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
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
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 - [d1]Krzysztof J. Gorgolewski
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.12.0-rc1. Version 0.12.0-rc1. Zenodo, 2016 [all versions] - [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
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
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
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]Gaël Varoquaux, Michael Eickenberg, Elvis Dohmatob, Bertrand Thirion:
FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging. CoRR abs/1512.06999 (2015) - 2014
- [j17]Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi
Machine learning for neuroimaging with scikit-learn. Frontiers Neuroinformatics 8: 14 (2014) - [j16]Benoit Da Mota, Radu Tudoran, Alexandru Costan
Generic Machine Learning Pattern for Neuroimaging-Genetic Studies in the Cloud. Frontiers Neuroinformatics 8: 31 (2014) - [j15]Benoit Da Mota, Virgile Fritsch, Gaël Varoquaux
Randomized parcellation based inference. NeuroImage 89: 203-215 (2014) - [j14]Stephen M. Smith
Group-PCA for very large fMRI datasets. NeuroImage 101: 738-749 (2014) - [c36]Ronald Phlypo, Bertrand Thirion, Gaël Varoquaux
Deriving a Multi-subject Functional-Connectivity Atlas to Inform Connectome Estimation. MICCAI (3) 2014: 185-192 - [c35]Bernard Ng, Martin Dressler, Gaël Varoquaux
Transport on Riemannian Manifold for Functional Connectivity-Based Classification. MICCAI (2) 2014: 405-412 - [c34]Bertrand Thirion, Gaël Varoquaux
Principal Component Regression Predicts Functional Responses across Individuals. MICCAI (2) 2014: 741-748 - [c33]Elvis Dopgima Dohmatob, Alexandre Gramfort
Benchmarking solvers for TV-ℓ1 least-squares and logistic regression in brain imaging. PRNI 2014: 1-4 - [i14]Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux:
Machine Learning for Neuroimaging with Scikit-Learn. CoRR abs/1412.3919 (2014) - [i13]Alexandre Abraham, Elvis Dohmatob, Bertrand Thirion, Dimitris Samaras, Gaël Varoquaux:
Region segmentation for sparse decompositions: better brain parcellations from rest fMRI. CoRR abs/1412.3925 (2014) - 2013
- [j13]Christophe Pradal
Publishing scientific software matters. J. Comput. Sci. 4(5): 311-312 (2013) - [j12]Gaël Varoquaux
Learning and comparing functional connectomes across subjects. NeuroImage 80: 405-415 (2013) - [j11]Fani Deligianni
A Framework for Inter-Subject Prediction of Functional Connectivity From Structural Networks. IEEE Trans. Medical Imaging 32(12): 2200-2214 (2013) - [c32]Bernard Ng, Gaël Varoquaux
A Novel Sparse Group Gaussian Graphical Model for Functional Connectivity Estimation. IPMI 2013: 256-267 - [c31]Gaël Varoquaux
Cohort-Level Brain Mapping: Learning Cognitive Atoms to Single Out Specialized Regions. IPMI 2013: 438-449 - [c30]Benoit Da Mota, Virgile Fritsch, Gaël Varoquaux
Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations. MICCAI (2) 2013: 591-598 - [c29]Alexandre Abraham, Elvis Dohmatob, Bertrand Thirion, Dimitris Samaras, Gaël Varoquaux
Extracting Brain Regions from Rest fMRI with Total-Variation Constrained Dictionary Learning. MICCAI (2) 2013: 607-615 - [c28]Bernard Ng, Gaël Varoquaux
Implications of Inconsistencies between fMRI and dMRI on Multimodal Connectivity Estimation. MICCAI (3) 2013: 652-659 - [c27]Yannick Schwartz, Bertrand Thirion, Gaël Varoquaux:
Mapping paradigm ontologies to and from the brain. NIPS 2013: 1673-1681 - [c26]Alexandre Gramfort
Identifying Predictive Regions from fMRI with TV-L1 Prior. PRNI 2013: 17-20 - [c25]Virgile Fritsch, Benoit Da Mota, Gaël Varoquaux
Robust Group-Level Inference in Neuroimaging Genetic Studies. PRNI 2013: 21-24 - [c24]Viviana Siless
A Comparison of Metrics and Algorithms for Fiber Clustering. PRNI 2013: 190-193 - [c23]Solveig Badillo, Gaël Varoquaux
Hemodynamic Estimation Based on Consensus Clustering. PRNI 2013: 211-215 - [i12]Yannick Schwartz, Alexis Barbot, Benjamin Thyreau, Vincent Frouin, Gaël Varoquaux, Aditya Siram, Daniel S. Marcus, Jean-Baptiste Poline:
PyXNAT: XNAT in Python. CoRR abs/1301.6952 (2013) - [i11]Lars Buitinck, Gilles Louppe, Mathieu Blondel, Fabian Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Alexandre Gramfort, Jaques Grobler, Robert Layton, Jake VanderPlas, Arnaud Joly, Brian Holt, Gaël Varoquaux:
API design for machine learning software: experiences from the scikit-learn project. CoRR abs/1309.0238 (2013) - [i10]Yannick Schwartz, Bertrand Thirion, Gaël Varoquaux:
Mapping cognitive ontologies to and from the brain. CoRR abs/1311.3859 (2013) - 2012
- [j10]Yannick Schwartz, Alexis Barbot, Benjamin Thyreau, Vincent Frouin, Gaël Varoquaux
PyXNAT: XNAT in Python. Frontiers Neuroinformatics 6: 12 (2012) - [j9]Virgile Fritsch, Gaël Varoquaux
Detecting outliers in high-dimensional neuroimaging datasets with robust covariance estimators. Medical Image Anal. 16(7): 1359-1370 (2012) - [j8]Vincent Michel, Alexandre Gramfort
A supervised clustering approach for fMRI-based inference of brain states. Pattern Recognit. 45(6): 2041-2049 (2012) - [j7]Cameron Neylon
Changing computational research. The challenges ahead. Source Code Biol. Medicine 7: 2 (2012) - [c22]Gaël Varoquaux, Alexandre Gramfort, Bertrand Thirion:
Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clustering. ICML 2012 - [c21]Virgile Fritsch, Gaël Varoquaux
Non-parametric Density Modeling and Outlier-Detection in Medical Imaging Datasets. MLMI 2012: 210-217 - [c20]Fabian Pedregosa, Elodie Cauvet, Gaël Varoquaux
Learning to Rank from Medical Imaging Data. MLMI 2012: 234-241 - [c19]Yannick Schwartz, Gaël Varoquaux, Christophe Pallier, Philippe Pinel, Jean-Baptiste Poline, Bertrand Thirion:
Improving Accuracy and Power with Transfer Learning Using a Meta-analytic Database. MICCAI (3) 2012: 248-255 - [c18]Bernard Ng, Gaël Varoquaux, Jean-Baptiste Poline, Bertrand Thirion:
A Novel Sparse Graphical Approach for Multimodal Brain Connectivity Inference. MICCAI (1) 2012: 707-714 - [c17]Fabian Pedregosa, Elodie Cauvet, Gaël Varoquaux
Improved Brain Pattern Recovery through Ranking Approaches. PRNI 2012: 9-12 - [c16]Alexandre Gramfort
Decoding Visual Percepts Induced by Word Reading with fMRI. PRNI 2012: 13-16 - [c15]Yannick Schwartz, Gaël Varoquaux
On Spatial Selectivity and Prediction across Conditions with fMRI. PRNI 2012: 53-56 - [c14]Bernard Ng, Viviana Siless
Connectivity-informed Sparse Classifiers for fMRI Brain Decoding. PRNI 2012: 101-104 - [i9]Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake VanderPlas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Edouard Duchesnay:
Scikit-learn: Machine Learning in Python. CoRR abs/1201.0490 (2012) - [i8]Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion, Christophe Pallier, Elodie Cauvet:
Improved brain pattern recovery through ranking approaches. CoRR abs/1207.3520 (2012) - [i7]Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux, Elodie Cauvet, Christophe Pallier, Bertrand Thirion:
Learning to rank from medical imaging data. CoRR abs/1207.3598 (2012) - [i6]Yannick Schwartz, Gaël Varoquaux, Bertrand Thirion:
On spatial selectivity and prediction across conditions with fMRI. CoRR abs/1209.1450 (2012) - 2011
- [j6]Stéfan van der Walt, S. Chris Colbert, Gaël Varoquaux
The NumPy Array: A Structure for Efficient Numerical Computation. Comput. Sci. Eng. 13(2): 22-30 (2011) - [j5]Prabhu Ramachandran
Mayavi: 3D Visualization of Scientific Data. Comput. Sci. Eng. 13(2): 40-51 (2011) - [j4]Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake VanderPlas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Edouard Duchesnay:
Scikit-learn: Machine Learning in Python. J. Mach. Learn. Res. 12: 2825-2830 (2011) - [j3]Vincent Michel, Alexandre Gramfort
Total Variation Regularization for fMRI-Based Prediction of Behavior. IEEE Trans. Medical Imaging 30(7): 1328-1340 (2011) - [c13]Fani Deligianni
A Probabilistic Framework to Infer Brain Functional Connectivity from Anatomical Connections. IPMI 2011: 296-307 - [c12]Gaël Varoquaux
Multi-subject Dictionary Learning to Segment an Atlas of Brain Spontaneous Activity. IPMI 2011: 562-573 - [c11]Philippe Ciuciu, Gaël Varoquaux
Multifractal analysis of Resting State Networks in functional MRI. ISBI 2011: 473-478 - [c10]Virgile Fritsch, Gaël Varoquaux
Detecting Outlying Subjects in High-Dimensional Neuroimaging Datasets with Regularized Minimum Covariance Determinant. MICCAI (3) 2011: 264-271 - [c9]Bernard Ng, Rafeef Abugharbieh, Gaël Varoquaux
Connectivity-Informed fMRI Activation Detection. MICCAI (2) 2011: 285-292 - [c8]Vincent Michel, Alexandre Gramfort
A Comparative Study of Algorithms for Intra- and Inter-subjects fMRI Decoding. MLINI 2011: 1-8 - [c7]Alexandre Gramfort
Beyond Brain Reading: Randomized Sparsity and Clustering to Simultaneously Predict and Identify. MLINI 2011: 9-16 - [c6]Gaël Varoquaux
Statistical Learning for Resting-State fMRI: Successes and Challenges. MLINI 2011: 172-177 - [c5]Fani Deligianni
Relating Brain Functional Connectivity to Anatomical Connections: Model Selection. MLINI 2011: 178-185 - [i5]Vincent Michel, Alexandre Gramfort, Gaël Varoquaux, Evelyn Eger, Bertrand Thirion:
Total variation regularization for fMRI-based prediction of behaviour. CoRR abs/1102.1101 (2011) - [i4]Stéfan van der Walt, S. Chris Colbert, Gaël Varoquaux:
The NumPy array: a structure for efficient numerical computation. CoRR abs/1102.1523 (2011) - [i3]Vincent Michel, Alexandre Gramfort, Gaël Varoquaux, Evelyn Eger, Christine Keribin, Bertrand Thirion:
A supervised clustering approach for fMRI-based inference of brain states. CoRR abs/1104.5304 (2011) - 2010
- [j2]Gaël Varoquaux
A group model for stable multi-subject ICA on fMRI datasets. NeuroImage 51(1): 288-299 (2010) - [c4]Gaël Varoquaux
ICA-based sparse features recovery from FMRI datasets. ISBI 2010: 1177-1180 - [c3]Gaël Varoquaux
Detection of Brain Functional-Connectivity Difference in Post-stroke Patients Using Group-Level Covariance Modeling. MICCAI (1) 2010: 200-208 - [c2]Bertrand Thirion, Gaël Varoquaux
Accurate Definition of Brain Regions Position through the Functional Landmark Approach. MICCAI (2) 2010: 241-248 - [c1]Gaël Varoquaux, Alexandre Gramfort, Jean-Baptiste Poline, Bertrand Thirion:
Brain covariance selection: better individual functional connectivity models using population prior. NIPS 2010: 2334-2342 - [i2]Prabhu Ramachandran, Gaël Varoquaux:
Mayavi: a package for 3D visualization of scientific data. CoRR abs/1010.4891 (2010)
2000 – 2009
- 2009
- [i1]Gaël Varoquaux, Sepideh Sadaghiani, Jean-Baptiste Poline, Bertrand Thirion:
CanICA: Model-based extraction of reproducible group-level ICA patterns from fMRI time series. CoRR abs/0911.4650 (2009) - 2008
- [j1]Gaël Varoquaux
Agile Computer Control of a Complex Experiment. Comput. Sci. Eng. 10(2): 55-59 (2008)
Coauthor Index
Sami Andberg
aka: Sami Kristian Andberg
aka: Sami Kristian Andberg
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d5] [d4] [d3] [d2]
Colin R. Buchanan
aka: Colin Buchanan
aka: Colin Buchanan
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
Matteo di Castello
aka: Matteo Visconti di Oleggio Castello
aka: Matteo Visconti di Oleggio Castello
Matthew Cieslak
aka: Matt Cieslak
aka: Matt Cieslak
[d69] [d68] [d67] [d66] [d65] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2]
Blake Dewey
aka: Blake E. Dewey
aka: Blake E. Dewey
Elvis Dohmatob
aka: Elvis Dopgima Dohmatob
aka: Elvis Dopgima Dohmatob
Elizabeth DuPre
aka: Elizabeth Dupre
aka: Elizabeth Dupre
David Gage Ellis
aka: David G. Ellis
aka: David G. Ellis
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [j27] [d6] [d5] [d4] [d3] [d2] [d1]
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
[d69] [d68] [d67] [d66] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [j27] [d6] [d5] [d4] [d3] [d2] [j25] [d1] [j21]
Ashley Gillman
aka: Ashley G. Gillman
aka: Ashley G. Gillman
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2]
Krzysztof J. Gorgolewski
aka: Chris Gorgolewski
aka: Chris Gorgolewski
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [j44] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [i25] [j27] [d6] [d5] [d4] [d3] [d2] [j25] [d1] [j21]
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [i38] [j43] [j42] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [c60] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [i33] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [j29] [d6] [d5] [d4] [d3] [d2] [i22] [d1] [j17] [c33] [i14] [c26] [i11] [j8] [c22] [c20] [c17] [c16] [i9] [i8] [i7] [j4] [j3] [c12] [c8] [c7] [i5] [i3] [c1]
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
Carlo Hämäläinen
aka: Carlo Hamalainen
aka: Carlo Hamalainen
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d5] [d4] [d3] [d2]
Anibal Sólon Heinsfeld
aka: Anibal Sólon
aka: Anibal Sólon
Oliver Hinds
aka: Oliver P. Hinds
aka: Oliver P. Hinds
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d5] [d4] [d3] [d2]
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d5] [d4] [d3] [d2]
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d5] [d4] [d3] [d2]
[d69] [d68] [d67] [d66] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d4] [d3] [d2]
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
Jon Haitz Legarreta
aka: Jon Haitz Legarreta Gorrono
aka: Jon Haitz Legarreta Gorrono
Franziskus Liem
aka: Franz Liem
aka: Franz Liem
Cindee M. Madison
aka: Cindee Madison
aka: Cindee Madison
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
Alexandre Manhães-Savio
aka: Alexandre Savio
aka: Alexandre Savio
Ross D. Markello
aka: Ross Markello
aka: Ross Markello
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d2]
Christopher J. Markiewicz
aka: Chris Markiewicz
aka: Chris Markiewicz
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
K. Jarrod Millman
aka: Jarrod Millman
aka: Jarrod Millman
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d5] [d4] [d3] [d2] [j7]
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d5] [d4] [d3] [d2]
[d69] [d68] [d67] [d66] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
Dylan Nielson
aka: Dylan M. Nielson
aka: Dylan M. Nielson
Michael Philipp Notter
aka: Michael Notter
aka: Michael Notter
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d5] [d4] [d3] [d2]
Martin Perez-Guevara
aka: Martin Felipe Perez-Guevara
aka: Martin Felipe Perez-Guevara
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
Russell A. Poldrack
aka: Russell Poldrack
aka: Russell Poldrack
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [d6] [d5] [d4] [d3] [d2] [d1]
[d69] [d68] [d67] [d66] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [j36] [j34] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [j32] [d5] [d4] [d3] [d2] [j25] [j21] [c37] [c31] [c27] [i12] [i10] [j10] [c19] [c15] [i6]
Jonathan Stutters
aka: Jon Stutters
aka: Jon Stutters
Alejandro Tabas-Diaz
aka: Alejandro Tabas
aka: Alejandro Tabas
[d69] [d68] [d67] [d66] [d65] [d64] [d59] [d58] [d57] [j46] [j45] [i38] [j44] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [j41] [j40] [j39] [c61] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [j36] [j35] [j34] [j33] [c58] [c57] [i29] [i28] [i27] [i26] [j32] [j31] [j29] [j28] [c54] [c53] [c52] [c51] [c50] [i24] [i23] [i22] [i21] [j26] [j23] [j22] [c49] [c48] [c47] [c45] [c44] [c43] [c42] [i20] [i19] [i18] [i17] [j19] [c41] [c40] [c39] [c38] [c37] [i16] [i15] [j17] [j16] [j15] [c36] [c35] [c34] [c33] [i14] [i13] [j11] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [i10] [j9] [j8] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [i9] [i8] [i7] [i6] [j4] [j3] [c13] [c12] [c10] [c9] [c8] [c7] [c6] [c5] [i5] [i3] [j2] [c4] [c3] [c2] [c1] [i1]
Michael L. Waskom
aka: Michael Waskom
aka: Michael Waskom
[d69] [d68] [d67] [d66] [d65] [j48] [d59] [d58] [d57] [d55] [d54] [d53] [d52] [d50] [j44] [j42] [d49] [d48] [d47] [d46] [d45] [d44] [d43] [d42] [d41] [d40] [d39] [d38] [d37] [d36] [d35] [d34] [d33] [d32] [d31] [d30] [d29] [d28] [d27] [d26] [d25] [d24] [d23] [d22] [c58] [d21] [d20] [d19] [d18] [d17] [d16] [d15] [d14] [d13] [d12] [d11] [d10] [d9] [d8] [i29] [d6] [d5] [d4] [d3] [d2] [d1]
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