Alexandre Gramfort

218 papers A* 25A 7B 2Misc 6Journal 133Unranked 44

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Diffusion posterior sampling for simulation-based inference in tall data settings. Trans. Mach. Learn. Res. Julia Linhart, Gabriel Cardoso, Alexandre Gramfort, Sylvain Le Corff, Pedro L. C. Rodrigues
2026	J	`jnl`	MVICAD IEEE Trans. Biomed. Eng. Ambroise Heurtebise, Omar Chehab, Pierre Ablin, Alexandre Gramfort
2025	J	`jnl`	EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding. CoRR Bruno Aristimunha, Dung Truong, Pierre Guetschel, Seyed Yahya Shirazi, Isabelle Guyon, Alexandre R. Franco, Michael P. Milham, Aviv Dotan, Scott Makeig, Alexandre Gramfort, Jean-Remi King, Marie-Constance Corsi, Pedro A. Valdés-Sosa, Amitava Majumdar, Alan Evans, Terrence J. Sejnowski, Oren Shriki, Sylvain Chevallier, Arnaud Delorme
2025	J	`jnl`	Identifiable Multi-View Causal Discovery Without Non-Gaussianity. CoRR Ambroise Heurtebise, Omar Chehab, Pierre Ablin, Alexandre Gramfort, Aapo Hyvärinen
2025	J	`jnl`	MVICAD2: Multi-View Independent Component Analysis with Delays and Dilations. CoRR Ambroise Heurtebise, Omar Chehab, Pierre Ablin, Alexandre Gramfort
2025	J	`jnl`	PSDNorm: Test-Time Temporal Normalization for Deep Learning on EEG Signals. CoRR Théo Gnassounou, Antoine Collas, Rémi Flamary, Alexandre Gramfort
2025	J	`jnl`	SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities. Trans. Mach. Learn. Res. Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Ambroise Odonnat, Thomas Moreau, Alexandre Gramfort, Rémi Flamary
2024	J	`jnl`	Cycling on the Freeway: The Perilous State of Open Source Neuroscience Software. CoRR Britta U. Westner, Daniel R. McCloy, Eric Larson, Alexandre Gramfort, Daniel S. Katz, Arfon M. Smith, invited co-signees
2024	J	`jnl`	Diffusion posterior sampling for simulation-based inference in tall data settings. CoRR Julia Linhart, Gabriel Victorino Cardoso, Alexandre Gramfort, Sylvain Le Corff, Pedro L. C. Rodrigues
2024	A*	`conf`	Geodesic Optimization for Predictive Shift Adaptation on EEG data. NeurIPS Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis A. Engemann
2024	J	`jnl`	Geodesic Optimization for Predictive Shift Adaptation on EEG data. CoRR Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis A. Engemann
2024	J	`jnl`	Local linear convergence of proximal coordinate descent algorithm. Optim. Lett. Quentin Klopfenstein, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon, Samuel Vaiter
2024	J	`jnl`	Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference. PLoS Comput. Biol. Nicholas Tolley, Pedro L. C. Rodrigues, Alexandre Gramfort, Stephanie R. Jones
2024	J	`jnl`	Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment. CoRR Théo Gnassounou, Antoine Collas, Rémi Flamary, Karim Lounici, Alexandre Gramfort
2024	—	`conf`	Physics-Informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets. EUSIPCO Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis A. Engemann, Alexandre Gramfort
2024	J	`jnl`	Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets. CoRR Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis A. Engemann, Alexandre Gramfort
2024	J	`jnl`	SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation. CoRR Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Oleksii Kachaiev, Ambroise Odonnat, Alexandre Gramfort, Thomas Moreau, Rémi Flamary
2024	J	`jnl`	Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications. CoRR Antoine Collas, Rémi Flamary, Alexandre Gramfort
2024	A*	`conf`	emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography. NeurIPS Viswanath Sivakumar, Jeffrey Seely, Alan Du, Sean R. Bittner, Adam Berenzweig, Anuoluwapo Bolarinwa, Alexandre Gramfort, Michael I. Mandel
2024	J	`jnl`	emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography. CoRR Viswanath Sivakumar, Jeffrey Seely, Alan Du, Sean R. Bittner, Adam Berenzweig, Anuoluwapo Bolarinwa, Alexandre Gramfort, Michael I. Mandel
2023	A*	`conf`	Convolution Monge Mapping Normalization for learning on sleep data. NeurIPS Théo Gnassounou, Rémi Flamary, Alexandre Gramfort
2023	J	`jnl`	Convolutional Monge Mapping Normalization for learning on biosignals. CoRR Théo Gnassounou, Rémi Flamary, Alexandre Gramfort
2023	J	`jnl`	Evaluating the structure of cognitive tasks with transfer learning. CoRR Bruno Aristimunha, Raphael Y. de Camargo, Walter Hugo Lopez Pinaya, Sylvain Chevallier, Alexandre Gramfort, Cédric Rommel
2023	A*	`conf`	FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels. ICML Guillaume Staerman, Cédric Allain, Alexandre Gramfort, Thomas Moreau
2023	A*	`conf`	L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference. NeurIPS Julia Linhart, Alexandre Gramfort, Pedro Rodrigues
2023	J	`jnl`	L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference. CoRR Julia Linhart, Alexandre Gramfort, Pedro L. C. Rodrigues
2023	J	`jnl`	MultiView Independent Component Analysis with Delays. CoRR Ambroise Heurtebise, Pierre Ablin, Alexandre Gramfort
2023	—	`conf`	Multiview Independent Component Analysis with Delays. MLSP Ambroise Heurtebise, Pierre Ablin, Alexandre Gramfort
2023	J	`jnl`	Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation. CoRR Omar Chehab, Alexandre Gramfort, Aapo Hyvärinen
2023	J	`jnl`	Using convolutional dictionary learning to detect task-related neuromagnetic transients and ageing trends in a large open-access dataset. NeuroImage Lindsey Power, Cédric Allain, Thomas Moreau, Alexandre Gramfort, Timothy Bardouille
2022	J	`jnl`	2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets. CoRR Xiaoxi Wei, A. Aldo Faisal, Moritz Grosse-Wentrup, Alexandre Gramfort, Sylvain Chevallier, Vinay Jayaram, Camille Jeunet, Stylianos Bakas, Siegfried Ludwig, Konstantinos Barmpas, Mehdi Bahri, Yannis Panagakis, Nikolaos A. Laskaris, Dimitrios A. Adamos, Stefanos Zafeiriou, William C. Duong, Stephen M. Gordon, Vernon J. Lawhern, Maciej Sliwowski, Vincent Rouanne, Piotr Tempczyk
2022	J	`jnl`	A reusable benchmark of brain-age prediction from M/EEG resting-state signals. NeuroImage Denis A. Engemann, Apolline Mellot, Richard Höchenberger, Hubert J. Banville, David Sabbagh, Lukas Gemein, Tonio Ball, Alexandre Gramfort
2022	J	`jnl`	A unified view on beamformers for M/EEG source reconstruction. NeuroImage Britta U. Westner, Sarang S. Dalal, Alexandre Gramfort, Vladimir Litvak, John C. Mosher, Robert Oostenveld, Jan-Mathijs Schoffelen
2022	J	`jnl`	Averaging Spatio-temporal Signals using Optimal Transport and Soft Alignments. CoRR Hicham Janati, Marco Cuturi, Alexandre Gramfort
2022	A*	`conf`	Benchopt: Reproducible, efficient and collaborative optimization benchmarks. NeurIPS Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cássio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter
2022	J	`jnl`	Benchopt: Reproducible, efficient and collaborative optimization benchmarks. CoRR Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cássio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter
2022	A*	`conf`	CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals. ICLR Cédric Rommel, Thomas Moreau, Joseph Paillard, Alexandre Gramfort
2022	J	`jnl`	Data augmentation for learning predictive models on EEG: a systematic comparison. CoRR Cédric Rommel, Joseph Paillard, Thomas Moreau, Alexandre Gramfort
2022	A*	`conf`	Deep invariant networks with differentiable augmentation layers. NeurIPS Cédric Rommel, Thomas Moreau, Alexandre Gramfort
2022	J	`jnl`	Deep invariant networks with differentiable augmentation layers. CoRR Cédric Rommel, Thomas Moreau, Alexandre Gramfort
2022	J	`jnl`	DiCoDiLe: Distributed Convolutional Dictionary Learning. IEEE Trans. Pattern Anal. Mach. Intell. Thomas Moreau, Alexandre Gramfort
2022	A*	`conf`	DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals. ICLR Cédric Allain, Alexandre Gramfort, Thomas Moreau
2022	J	`jnl`	FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels. CoRR Guillaume Staerman, Cédric Allain, Alexandre Gramfort, Thomas Moreau
2022	J	`jnl`	Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning. J. Mach. Learn. Res. Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
2022	J	`jnl`	Intracranial Electrode Location and Analysis in MNE-Python. J. Open Source Softw. Alexander Rockhill, Eric Larson, Brittany Stedelin, Alessandra Mantovani, Ahmed M. Raslan, Alexandre Gramfort, Nicole C. Swann
2022	—	`conf`	LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso. AutoML Kenan Sehic, Alexandre Gramfort, Joseph Salmon, Luigi Nardi
2022	J	`jnl`	Robust learning from corrupted EEG with dynamic spatial filtering. NeuroImage Hubert J. Banville, Sean U. N. Wood, Chris Aimone, Denis-Alexander Engemann, Alexandre Gramfort
2022	J	`jnl`	The Optimal Noise in Noise-Contrastive Learning Is Not What You Think. CoRR Omar Chehab, Alexandre Gramfort, Aapo Hyvärinen
2022	A	`conf`	The optimal noise in noise-contrastive learning is not what you think. UAI Omar Chehab, Alexandre Gramfort, Aapo Hyvärinen
2022	A*	`conf`	Toward a realistic model of speech processing in the brain with self-supervised learning. NeurIPS Juliette Millet, Charlotte Caucheteux, Pierre Orhan, Yves Boubenec, Alexandre Gramfort, Ewan Dunbar, Christophe Pallier, Jean-Remi King
2022	J	`jnl`	Toward a realistic model of speech processing in the brain with self-supervised learning. CoRR Juliette Millet, Charlotte Caucheteux, Pierre Orhan, Yves Boubenec, Alexandre Gramfort, Ewan Dunbar, Christophe Pallier, Jean-Remi King
2022	J	`jnl`	Validation Diagnostics for SBI algorithms based on Normalizing Flows. CoRR Julia Linhart, Alexandre Gramfort, Pedro L. C. Rodrigues
2021	—	`conf`	2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets. NeurIPS (Competition and Demos) Xiaoxi Wei, A. Aldo Faisal, Moritz Grosse-Wentrup, Alexandre Gramfort, Sylvain Chevallier, Vinay Jayaram, Camille Jeunet, Stylianos Bakas, Siegfried Ludwig, Konstantinos Barmpas, Mehdi Bahri, Yannis Panagakis, Nikolaos A. Laskaris, Dimitrios A. Adamos, Stefanos Zafeiriou, William C. Duong, Stephen M. Gordon, Vernon J. Lawhern, Maciej Sliwowski, Vincent Rouanne, Piotr Tempczyk
2021	J	`jnl`	Adaptive Multi-View ICA: Estimation of noise levels for optimal inference. CoRR Hugo Richard, Pierre Ablin, Aapo Hyvärinen, Alexandre Gramfort, Bertrand Thirion
2021	J	`jnl`	CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals. CoRR Cédric Rommel, Thomas Moreau, Alexandre Gramfort
2021	—	`conf`	Cytoarchitecture Measurements in Brain Gray Matter Using Likelihood-Free Inference. IPMI Maëliss Jallais, Pedro L. C. Rodrigues, Alexandre Gramfort, Demian Wassermann
2021	J	`jnl`	Decomposing lexical and compositional syntax and semantics with deep language models. CoRR Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
2021	J	`jnl`	Deep Recurrent Encoder: A scalable end-to-end network to model brain signals. CoRR Omar Chehab, Alexandre Défossez, Jean-Christophe Loiseau, Alexandre Gramfort, Jean-Remi King
2021	A*	`conf`	Disentangling syntax and semantics in the brain with deep networks. ICML Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
2021	J	`jnl`	DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals. CoRR Cédric Allain, Alexandre Gramfort, Thomas Moreau, A. Preprint
2021	A*	`conf`	HNPE: Leveraging Global Parameters for Neural Posterior Estimation. NeurIPS Pedro Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort
2021	J	`jnl`	Implicit differentiation for fast hyperparameter selection in non-smooth convex learning. CoRR Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
2021	J	`jnl`	Inverting brain grey matter models with likelihood-free inference: a tool for trustable cytoarchitecture measurements. CoRR Maëliss Jallais, Pedro Rodrigues, Alexandre Gramfort, Demian Wassermann
2021	J	`jnl`	Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction. CoRR Marc-Andre Schulz, Bertrand Thirion, Alexandre Gramfort, Gaël Varoquaux, Danilo Bzdok
2021	J	`jnl`	LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso. CoRR Kenan Sehic, Alexandre Gramfort, Joseph Salmon, Luigi Nardi
2021	—	`conf`	Learning with self-supervision on EEG data. BCI Alexandre Gramfort, Hubert J. Banville, Omar Chehab, Aapo Hyvärinen, Denis A. Engemann
2021	J	`jnl`	Leveraging Global Parameters for Flow-based Neural Posterior Estimation. CoRR Pedro L. C. Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort
2021	J	`jnl`	Long-range and hierarchical language predictions in brains and algorithms. CoRR Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
2021	—	`conf`	Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects. EMNLP (Findings) Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
2021	J	`jnl`	Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects. CoRR Charlotte Caucheteux, Alexandre Gramfort, Jean-Rémi King
2021	J	`jnl`	POT: Python Optimal Transport. J. Mach. Learn. Res. Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T. H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer
2021	J	`jnl`	Robust learning from corrupted EEG with dynamic spatial filtering. CoRR Hubert J. Banville, Sean U. N. Wood, Chris Aimone, Denis-Alexander Engemann, Alexandre Gramfort
2021	A*	`conf`	Shared Independent Component Analysis for Multi-Subject Neuroimaging. NeurIPS Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen
2021	J	`jnl`	Shared Independent Component Analysis for Multi-Subject Neuroimaging. CoRR Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen
2021	J	`jnl`	mvlearn: Multiview Machine Learning in Python. J. Mach. Learn. Res. Ronan Perry, Gavin Mischler, Richard Guo, Theo Lee, Alexander Chang, Arman Koul, Cameron Franz, Hugo Richard, Iain Carmichael, Pierre Ablin, Alexandre Gramfort, Joshua T. Vogelstein
2020	J	`jnl`	Comparison of beamformer implementations for MEG source localization. NeuroImage Amit Jaiswal, Jukka Nenonen, Matti Stenroos, Alexandre Gramfort, Sarang S. Dalal, Britta U. Westner, Vladimir Litvak, John C. Mosher, Jan-Mathijs Schoffelen, Caroline Witton, Robert Oostenveld, Lauri Parkkonen
2020	A*	`conf`	Debiased Sinkhorn barycenters. ICML Hicham Janati, Marco Cuturi, Alexandre Gramfort
2020	J	`jnl`	Debiased Sinkhorn barycenters. CoRR Hicham Janati, Marco Cuturi, Alexandre Gramfort
2020	A*	`conf`	Implicit differentiation of Lasso-type models for hyperparameter optimization. ICML Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
2020	J	`jnl`	Implicit differentiation of Lasso-type models for hyperparameter optimization. CoRR Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
2020	J	`jnl`	International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium. npj Digit. Medicine 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 Schriver, 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 Estève, 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
2020	J	`jnl`	Learning summary features of time series for likelihood free inference. CoRR Pedro L. C. Rodrigues, Alexandre Gramfort
2020	J	`jnl`	Model identification and local linear convergence of coordinate descent. CoRR Quentin Klopfenstein, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon, Samuel Vaiter
2020	J	`jnl`	Modeling Shared Responses in Neuroimaging Studies through MultiView ICA. CoRR Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin
2020	A*	`conf`	Modeling Shared responses in Neuroimaging Studies through MultiView ICA. NeurIPS Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin
2020	J	`jnl`	Multi-subject MEG/EEG source imaging with sparse multi-task regression. NeuroImage Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort
2020	J	`jnl`	Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states. NeuroImage David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann
2020	A	`conf`	Spatio-temporal alignments: Optimal transport through space and time. AISTATS Hicham Janati, Marco Cuturi, Alexandre Gramfort
2020	J	`jnl`	Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso. CoRR Jérôme-Alexis Chevalier, Alexandre Gramfort, Joseph Salmon, Bertrand Thirion
2020	A*	`conf`	Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso. NeurIPS Jérôme-Alexis Chevalier, Joseph Salmon, Alexandre Gramfort, Bertrand Thirion
2020	A	`conf`	Support recovery and sup-norm convergence rates for sparse pivotal estimation. AISTATS Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon
2020	J	`jnl`	Support recovery and sup-norm convergence rates for sparse pivotal estimation. CoRR Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon
2020	J	`jnl`	Uncovering the structure of clinical EEG signals with self-supervised learning. CoRR Hubert J. Banville, Omar Chehab, Aapo Hyvärinen, Denis-Alexander Engemann, Alexandre Gramfort
2019	Misc	`conf`	A Quasi-Newton Algorithm on the Orthogonal Manifold for NMF with Transform Learning. ICASSP Pierre Ablin, Dylan Fagot, Herwig Wendt, Alexandre Gramfort, Cédric Févotte
2019	B	`conf`	Beyond Pham's algorithm for joint diagonalization. ESANN Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
2019	J	`jnl`	Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise. CoRR Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon
2019	J	`jnl`	Deep learning-based electroencephalography analysis: a systematic review. CoRR Yannick Roy, Hubert J. Banville, Isabela Albuquerque, Alexandre Gramfort, Tiago H. Falk, Jocelyn Faubert
2019	J	`jnl`	Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals. CoRR Thomas Moreau, Alexandre Gramfort
2019	J	`jnl`	Dual Extrapolation for Sparse Generalized Linear Models. CoRR Mathurin Massias, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
2019	—	`conf`	Group Level MEG/EEG Source Imaging via Optimal Transport: Minimum Wasserstein Estimates. IPMI Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort
2019	J	`jnl`	Group level MEG/EEG source imaging via optimal transport: minimum Wasserstein estimates. CoRR Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort
2019	A*	`conf`	Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso. NeurIPS Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon
2019	A*	`conf`	Learning step sizes for unfolded sparse coding. NeurIPS Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort
2019	J	`jnl`	Learning step sizes for unfolded sparse coding. CoRR Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort
2019	J	`jnl`	MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. J. Open Source Softw. Stefan Appelhoff, Matthew Sanderson, Teon Brooks, Marijn van Vliet, Romain Quentin, Chris Holdgraf, Maximilien Chaumon, Ezequiel Mikulan, Kambiz Tavabi, Richard Höchenberger, Dominik Welke, Clemens Brunner, Alexander Rockhill, Eric Larson, Alexandre Gramfort, Mainak Jas
2019	A*	`conf`	Manifold-regression to predict from MEG/EEG brain signals without source modeling. NeurIPS David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann
2019	J	`jnl`	Manifold-regression to predict from MEG/EEG brain signals without source modeling. CoRR David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann
2019	J	`jnl`	Multi-subject MEG/EEG source imaging with sparse multi-task regression. CoRR Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort
2019	—	`conf`	Self-Supervised Representation Learning from Electroencephalography Signals. MLSP Hubert J. Banville, Graeme Moffat, Isabela Albuquerque, Denis-Alexander Engemann, Aapo Hyvärinen, Alexandre Gramfort
2019	J	`jnl`	Self-supervised representation learning from electroencephalography signals. CoRR Hubert J. Banville, Isabela Albuquerque, Aapo Hyvärinen, Graeme Moffat, Denis-Alexander Engemann, Alexandre Gramfort
2019	J	`jnl`	Spatio-Temporal Alignments: Optimal transport through space and time. CoRR Hicham Janati, Marco Cuturi, Alexandre Gramfort
2019	A	`conf`	Stochastic algorithms with descent guarantees for ICA. AISTATS Pierre Ablin, Alexandre Gramfort, Jean-François Cardoso, Francis R. Bach
2019	A	`conf`	Wasserstein regularization for sparse multi-task regression. AISTATS Hicham Janati, Marco Cuturi, Alexandre Gramfort
2018	—	`conf`	A Deep Learning Architecture to Detect Events in EEG Signals During Sleep. MLSP Stanislas Chambon, Valentin Thorey, Pierrick J. Arnal, Emmanuel Mignot, Alexandre Gramfort
2018	J	`jnl`	A Quasi-Newton algorithm on the orthogonal manifold for NMF with transform learning. CoRR Pierre Ablin, Dylan Fagot, Herwig Wendt, Alexandre Gramfort, Cédric Févotte
2018	J	`jnl`	A deep learning architecture to detect events in EEG signals during sleep. CoRR Stanislas Chambon, Valentin Thorey, Pierrick J. Arnal, Emmanuel Mignot, Alexandre Gramfort
2018	—	`conf`	Accelerating Likelihood Optimization for ICA on Real Signals. LVA/ICA Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
2018	J	`jnl`	Accelerating likelihood optimization for ICA on real signals. CoRR Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
2018	Misc	`conf`	An Ensemble Learning Approach to Detect Epileptic Seizures from Long Intracranial EEG Recordings. ICASSP Jean-Baptiste Schiratti, Jean-Eudes Le Douget, Michel Le Van Quyen, Slim Essid, Alexandre Gramfort
2018	J	`jnl`	Beyond Pham's algorithm for joint diagonalization. CoRR Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
2018	A*	`conf`	Celer: a Fast Solver for the Lasso with Dual Extrapolation. ICML Mathurin Massias, Joseph Salmon, Alexandre Gramfort
2018	J	`jnl`	DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal. CoRR Stanislas Chambon, Valentin Thorey, Pierrick J. Arnal, Emmanuel Mignot, Alexandre Gramfort
2018	—	`conf`	Domain adaptation with optimal transport improves EEG sleep stage classifiers. PRNI Stanislas Chambon, Mathieu N. Galtier, Alexandre Gramfort
2018	Misc	`conf`	Driver Estimation in Non-Linear Autoregressive Models. ICASSP Tom Dupré la Tour, Yves Grenier, Alexandre Gramfort
2018	J	`jnl`	EM algorithms for ICA. CoRR Pierre Ablin, Alexandre Gramfort, Jean-François Cardoso, Francis R. Bach
2018	Misc	`conf`	Faster ICA Under Orthogonal Constraint. ICASSP Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
2018	J	`jnl`	Faster Independent Component Analysis by Preconditioning With Hessian Approximations. IEEE Trans. Signal Process. Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
2018	A	`conf`	Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression. AISTATS Mathurin Massias, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
2018	A*	`conf`	Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals. NeurIPS Tom Dupré la Tour, Thomas Moreau, Mainak Jas, Alexandre Gramfort
2018	J	`jnl`	Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals. CoRR Tom Dupré la Tour, Thomas Moreau, Mainak Jas, Alexandre Gramfort
2018	J	`jnl`	Wasserstein regularization for sparse multi-task regression. CoRR Hicham Janati, Marco Cuturi, Alexandre Gramfort
2017	J	`jnl`	A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series. CoRR Stanislas Chambon, Mathieu Galtier, Pierrick Arnal, Gilles Wainrib, Alexandre Gramfort
2017	A	`conf`	Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere. AISTATS Albert Thomas, Stéphan Clémençon, Alexandre Gramfort, Anne Sabourin
2017	J	`jnl`	Autoreject: Automated artifact rejection for MEG and EEG data. NeuroImage Mainak Jas, Denis A. Engemann, Yousra Bekhti, Federico Raimondo, Alexandre Gramfort
2017	—	`conf`	Caveats with Stochastic Gradient and Maximum Likelihood Based ICA for EEG. LVA/ICA Jair Montoya-Martínez, Jean-François Cardoso, Alexandre Gramfort
2017	J	`jnl`	Convolutional Network Layers Map the Function of the Human Visual Cortex. ERCIM News Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion, Alexandre Gramfort
2017	J	`jnl`	From safe screening rules to working sets for faster Lasso-type solvers. CoRR Mathurin Massias, Alexandre Gramfort, Joseph Salmon
2017	J	`jnl`	Gap Safe Screening Rules for Sparsity Enforcing Penalties. J. Mach. Learn. Res. Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
2017	—	`conf`	Hyperparameter estimation in maximum a posteriori regression using group sparsity with an application to brain imaging. EUSIPCO Yousra Bekhti, Roland Badeau, Alexandre Gramfort
2017	—	`conf`	Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding. NIPS Mainak Jas, Tom Dupré la Tour, Umut Simsekli, Alexandre Gramfort
2017	J	`jnl`	Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy. CoRR Laetitia Le, Camille Marini, Alexandre Gramfort, David Nguyen, Mehdi Cherti, Sana Tfaili, Ali Tfayli, Arlette Baillet-Guffroy, Patrice Prognon, Pierre Chaminade, Eric Caudron, Balázs Kégl
2017	J	`jnl`	Non-linear auto-regressive models for cross-frequency coupling in neural time series. PLoS Comput. Biol. Tom Dupré la Tour, Lucille Tallot, Laetitia Grabot, Valérie Doyère, Virginie van Wassenhove, Yves Grenier, Alexandre Gramfort
2017	J	`jnl`	On the Consistency of Ordinal Regression Methods. J. Mach. Learn. Res. Fabian Pedregosa, Francis R. Bach, Alexandre Gramfort
2017	Misc	`conf`	Parametric estimation of spectrum driven by an exogenous signal. ICASSP Tom Dupré la Tour, Yves Grenier, Alexandre Gramfort
2017	J	`jnl`	Seeing it all: Convolutional network layers map the function of the human visual system. NeuroImage Michael Eickenberg, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion
2016	—	`conf`	Automated rejection and repair of bad trials in MEG/EEG. PRNI Mainak Jas, Denis A. Engemann, Federico Raimondo, Yousra Bekhti, Alexandre Gramfort
2016	J	`jnl`	Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression. CoRR Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Vincent Leclère, Joseph Salmon
2016	—	`conf`	GAP Safe Screening Rules for Sparse-Group Lasso. NIPS Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
2016	J	`jnl`	GAP Safe Screening Rules for Sparse-Group-Lasso. CoRR Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
2016	J	`jnl`	Gap Safe screening rules for sparsity enforcing penalties. CoRR Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
2016	—	`conf`	M/EEG source localization with multi-scale time-frequency dictionaries. PRNI Yousra Bekhti, Daniel Strohmeier, Mainak Jas, Roland Badeau, Alexandre Gramfort
2016	J	`jnl`	The Iterative Reweighted Mixed-Norm Estimate for Spatio-Temporal MEG/EEG Source Reconstruction. IEEE Trans. Medical Imaging Daniel Strohmeier, Yousra Bekhti, Jens Haueisen, Alexandre Gramfort
2015	J	`jnl`	Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals. NeuroImage Denis A. Engemann, Alexandre Gramfort
2015	B	`conf`	Calibration of One-Class SVM for MV set estimation. DSAA Albert Thomas, Vincent Feuillard, Alexandre Gramfort
2015	J	`jnl`	Data-driven HRF estimation for encoding and decoding models. NeuroImage Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Bertrand Thirion, Alexandre Gramfort
2015	—	`conf`	FAμST: Speeding up linear transforms for tractable inverse problems. EUSIPCO Luc Le Magoarou, Rémi Gribonval, Alexandre Gramfort
2015	—	`conf`	Fast Optimal Transport Averaging of Neuroimaging Data. IPMI Alexandre Gramfort, Gabriel Peyré, Marco Cuturi
2015	J	`jnl`	Fast Optimal Transport Averaging of Neuroimaging Data. CoRR Alexandre Gramfort, Gabriel Peyré, Marco Cuturi
2015	—	`conf`	GAP Safe screening rules for sparse multi-task and multi-class models. NIPS Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
2015	J	`jnl`	GAP Safe screening rules for sparse multi-task and multi-class models. CoRR Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
2015	—	`conf`	Inverse problems with time-frequency dictionaries and non-white Gaussian noise. EUSIPCO Matthieu Kowalski, Alexandre Gramfort
2015	—	`conf`	MEG/EEG Source Imaging with a Non-Convex Penalty in the Time-Frequency Domain. PRNI Daniel Strohmeier, Alexandre Gramfort, Jens Haueisen
2015	—	`conf`	Mind the Noise Covariance When Localizing Brain Sources with M/EEG. PRNI Denis A. Engemann, Daniel Strohmeier, Eric Larson, Alexandre Gramfort
2015	A*	`conf`	Mind the duality gap: safer rules for the Lasso. ICML Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
2015	J	`jnl`	Mind the duality gap: safer rules for the Lasso. CoRR Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
2014	—	`conf`	Benchmarking solvers for TV-ℓ1 least-squares and logistic regression in brain imaging. PRNI Elvis Dopgima Dohmatob, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux
2014	J	`jnl`	Blind Denoising with Random Greedy Pursuits. IEEE Signal Process. Lett. Manuel Moussallam, Alexandre Gramfort, Laurent Daudet, Gaël Richard
2014	J	`jnl`	Data-driven HRF estimation for encoding and decoding models. CoRR Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Alexandre Gramfort, Bertrand Thirion
2014	—	`conf`	Decoding perceptual thresholds from MEG/EEG. PRNI Yousra Bekhti, Nicolas Zilber, Fabian Pedregosa, Philippe Ciuciu, Virginie van Wassenhove, Alexandre Gramfort
2014	J	`jnl`	Denoising and fast diffusion imaging with physically constrained sparse dictionary learning. Medical Image Anal. Alexandre Gramfort, Cyril Poupon, Maxime Descoteaux
2014	J	`jnl`	Encoding of event timing in the phase of neural oscillations. NeuroImage Anne Kösem, Alexandre Gramfort, Virginie van Wassenhove
2014	—	`conf`	Improved MEG/EEG source localization with reweighted mixed-norms. PRNI Daniel Strohmeier, Jens Haueisen, Alexandre Gramfort
2014	J	`jnl`	MNE software for processing MEG and EEG data. NeuroImage Alexandre Gramfort, Martin Luessi, Eric Larson, Denis A. Engemann, Daniel Strohmeier, Christian Brodbeck, Lauri Parkkonen, Matti S. Hämäläinen
2014	J	`jnl`	Machine Learning for Neuroimaging with Scikit-Learn. CoRR Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux
2014	J	`jnl`	Machine learning for neuroimaging with scikit-learn. Frontiers Neuroinformatics Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux
2014	J	`jnl`	On the Consistency of Ordinal Regression Methods. CoRR Fabian Pedregosa, Francis R. Bach, Alexandre Gramfort
2014	J	`jnl`	Supramodal processing optimizes visual perceptual learning and plasticity. NeuroImage Nicolas Zilber, Philippe Ciuciu, Alexandre Gramfort, Leila Azizi, Virginie van Wassenhove
2013	J	`jnl`	API design for machine learning software: experiences from the scikit-learn project. CoRR 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
2013	J	`jnl`	Blind Denoising with Random Greedy Pursuits. CoRR Manuel Moussallam, Alexandre Gramfort, Laurent Daudet, Gaël Richard
2013	—	`conf`	HRF Estimation Improves Sensitivity of fMRI Encoding and Decoding Models. PRNI Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion, Alexandre Gramfort
2013	J	`jnl`	HRF estimation improves sensitivity of fMRI encoding and decoding models CoRR Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion, Alexandre Gramfort
2013	—	`conf`	Identifying Predictive Regions from fMRI with TV-L1 Prior. PRNI Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux
2013	A*	`conf`	Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals ICLR (Poster) Sebastian Hitziger, Maureen Clerc, Alexandre Gramfort, Sandrine Saillet, Christian G. Bénar, Théodore Papadopoulo
2013	—	`conf`	Learning from M/EEG Data with Variable Brain Activation Delays. IPMI Wojciech Zaremba, M. Pawan Kumar, Alexandre Gramfort, Matthew B. Blaschko
2013	—	`conf`	Non-negative Tensor Factorization for single-channel EEG artifact rejection. MLSP Cécilia Damon, Antoine Liutkus, Alexandre Gramfort, Slim Essid
2013	Misc	`conf`	Non-negative matrix factorization for single-channel EEG artifact rejection. ICASSP Cécilia Damon, Antoine Liutkus, Alexandre Gramfort, Slim Essid
2013	—	`conf`	Second Order Scattering Descriptors Predict fMRI Activity Due to Visual Textures. PRNI Michael Eickenberg, Mehdi Senoussi, Fabian Pedregosa, Alexandre Gramfort, Bertrand Thirion
2013	J	`jnl`	Second order scattering descriptors predict fMRI activity due to visual textures. CoRR Michael Eickenberg, Fabian Pedregosa, Senoussi Mehdi, Alexandre Gramfort, Bertrand Thirion
2013	J	`jnl`	Single-trial decoding of auditory novelty responses facilitates the detection of residual consciousness. NeuroImage Jean-Remi King, Frédéric Faugeras, Alexandre Gramfort, Aaron Schurger, Imen El Karoui, Jacobo D. Sitt, Benjamin Rohaut, Catherine Wacongne, Etienne Labyt, Tristán Bekinschtein, Laurent Cohen, Lionel Naccache, Stanislas Dehaene
2013	J	`jnl`	Time-frequency mixed-norm estimates: Sparse M/EEG imaging with non-stationary source activations. NeuroImage Alexandre Gramfort, Daniel Strohmeier, Jens Haueisen, Matti S. Hämäläinen, Matthieu Kowalski
2012	J	`jnl`	A supervised clustering approach for fMRI-based inference of brain states. Pattern Recognit. Vincent Michel, Alexandre Gramfort, Gaël Varoquaux, Evelyn Eger, Christine Keribin, Bertrand Thirion
2012	—	`conf`	Decoding Visual Percepts Induced by Word Reading with fMRI. PRNI Alexandre Gramfort, Christophe Pallier, Gaël Varoquaux, Bertrand Thirion
2012	—	`conf`	Improved Brain Pattern Recovery through Ranking Approaches. PRNI Fabian Pedregosa, Elodie Cauvet, Gaël Varoquaux, Christophe Pallier, Bertrand Thirion, Alexandre Gramfort
2012	J	`jnl`	Improved brain pattern recovery through ranking approaches CoRR Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion, Christophe Pallier, Elodie Cauvet
2012	—	`conf`	Learning to Rank from Medical Imaging Data. MLMI Fabian Pedregosa, Elodie Cauvet, Gaël Varoquaux, Christophe Pallier, Bertrand Thirion, Alexandre Gramfort
2012	J	`jnl`	Learning to rank from medical imaging data CoRR Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux, Elodie Cauvet, Christophe Pallier, Bertrand Thirion
2012	—	`conf`	Multilayer Scattering Image Analysis Fits fMRI Activity in Visual Areas. PRNI Michael Eickenberg, Alexandre Gramfort, Bertrand Thirion
2012	J	`jnl`	Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity. SIAM J. Imaging Sci. Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Evelyn Eger, Francis R. Bach, Bertrand Thirion
2012	J	`jnl`	Scikit-learn: Machine Learning in Python CoRR 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
2012	A*	`conf`	Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clustering. ICML Gaël Varoquaux, Alexandre Gramfort, Bertrand Thirion
2012	—	`conf`	Sparse DSI: Learning DSI Structure for Denoising and Fast Imaging. MICCAI (2) Alexandre Gramfort, Cyril Poupon, Maxime Descoteaux
2011	—	`conf`	A Comparative Study of Algorithms for Intra- and Inter-subjects fMRI Decoding. MLINI Vincent Michel, Alexandre Gramfort, Evelyn Eger, Gaël Varoquaux, Bertrand Thirion
2011	J	`jnl`	A supervised clustering approach for fMRI-based inference of brain states CoRR Vincent Michel, Alexandre Gramfort, Gaël Varoquaux, Evelyn Eger, Christine Keribin, Bertrand Thirion
2011	—	`conf`	Beyond Brain Reading: Randomized Sparsity and Clustering to Simultaneously Predict and Identify. MLINI Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion
2011	J	`jnl`	Forward Field Computation with OpenMEEG. Comput. Intell. Neurosci. Alexandre Gramfort, Théodore Papadopoulo, Emmanuel Olivi, Maureen Clerc
2011	—	`conf`	Functional Brain Imaging with M/EEG Using Structured Sparsity in Time-Frequency Dictionaries. IPMI Alexandre Gramfort, Daniel Strohmeier, Jens Haueisen, Matti S. Hämäläinen, Matthieu Kowalski
2011	—	`conf`	Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity. PRNI Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Francis R. Bach, Bertrand Thirion
2011	—	`conf`	Multi-subject Dictionary Learning to Segment an Atlas of Brain Spontaneous Activity. IPMI Gaël Varoquaux, Alexandre Gramfort, Fabian Pedregosa, Vincent Michel, Bertrand Thirion
2011	J	`jnl`	Phase delays within visual cortex shape the response to steady-state visual stimulation. NeuroImage Benoit Cottereau, Jean Lorenceau, Alexandre Gramfort, Maureen Clerc, Bertrand Thirion, Sylvain Baillet
2011	J	`jnl`	Scikit-learn: Machine Learning in Python. J. Mach. Learn. Res. 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
2011	J	`jnl`	Total Variation Regularization for fMRI-Based Prediction of Behavior. IEEE Trans. Medical Imaging Vincent Michel, Alexandre Gramfort, Gaël Varoquaux, Evelyn Eger, Bertrand Thirion
2011	J	`jnl`	Total variation regularization for fMRI-based prediction of behaviour CoRR Vincent Michel, Alexandre Gramfort, Gaël Varoquaux, Evelyn Eger, Bertrand Thirion
2011	J	`jnl`	Tracking cortical activity from M/EEG using graph cuts with spatiotemporal constraints. NeuroImage Alexandre Gramfort, Théodore Papadopoulo, Sylvain Baillet, Maureen Clerc
2010	J	`jnl`	A priori par normes mixtes pour les problèmes inverses. Application à la localisation de sources en M/EEG. Traitement du Signal Matthieu Kowalski, Alexandre Gramfort
2010	—	`conf`	Brain covariance selection: better individual functional connectivity models using population prior. NIPS Gaël Varoquaux, Alexandre Gramfort, Jean-Baptiste Poline, Bertrand Thirion
2010	J	`jnl`	Graph-Based Variability Estimation in Single-Trial Event-Related Neural Responses. IEEE Trans. Biomed. Eng. Alexandre Gramfort, Renaud Keriven, Maureen Clerc
2009	—	`conf`	Improving M/EEG Source Localization with an Inter-Condition Sparse Prior. ISBI Alexandre Gramfort, Matthieu Kowalski
2009	—	`—`	Mapping, timing and tracking cortical activations with MEG and EEG: Methods and application to human vision. (Localisation et suivi d'activité fonctionnelle cérébrale en électro et magnétoencéphalographie: Méthodes et applications au système visuel humain). Alexandre Gramfort