Alexandre Gramfort

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 155

Top Venues

Télécom ParisTech, France (PHD)

Education History

Télécom ParisTech, France

PHD

Publications

Théo Gnassounou, Antoine Collas, Rémi Flamary, Karim Lounici, Alexandre Gramfort
Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment. CoRR (2024)
Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis A. Engemann, Alexandre Gramfort
Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets. CoRR (2024)
Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis A. Engemann
Geodesic Optimization for Predictive Shift Adaptation on EEG data. CoRR (2024)
Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Oleksii Kachaiev, Ambroise Odonnat, Alexandre Gramfort, Thomas Moreau, Rémi Flamary
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation. CoRR (2024)
Julia Linhart, Gabriel Victorino Cardoso, Alexandre Gramfort, Sylvain Le Corff, Pedro L. C. Rodrigues
Diffusion posterior sampling for simulation-based inference in tall data settings. CoRR (2024)
Britta U. Westner, Daniel R. McCloy, Eric Larson, Alexandre Gramfort, Daniel S. Katz, Arfon M. Smith, invited co-signees
Cycling on the Freeway: The Perilous State of Open Source Neuroscience Software. CoRR (2024)
Nicholas Tolley, Pedro L. C. Rodrigues, Alexandre Gramfort, Stephanie R. Jones
Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference. PLoS Comput. Biol. 20 (2) (2024)
Quentin Klopfenstein, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon, Samuel Vaiter
Local linear convergence of proximal coordinate descent algorithm. Optim. Lett. 18 (1) (2024)
Antoine Collas, Rémi Flamary, Alexandre Gramfort
Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications. CoRR (2024)
Omar Chehab, Alexandre Gramfort, Aapo Hyvärinen
Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation. CoRR (2023)
Guillaume Staerman, Cédric Allain, Alexandre Gramfort, Thomas Moreau
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels. ICML (2023)
Bruno Aristimunha, Raphael Y. de Camargo, Walter Hugo Lopez Pinaya, Sylvain Chevallier, Alexandre Gramfort, Cédric Rommel
Evaluating the structure of cognitive tasks with transfer learning. CoRR (2023)
Julia Linhart, Alexandre Gramfort, Pedro Rodrigues
L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference. NeurIPS (2023)
Julia Linhart, Alexandre Gramfort, Pedro L. C. Rodrigues
L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference. CoRR (2023)
Théo Gnassounou, Rémi Flamary, Alexandre Gramfort
Convolutional Monge Mapping Normalization for learning on biosignals. CoRR (2023)
Ambroise Heurtebise, Pierre Ablin, Alexandre Gramfort
Multiview Independent Component Analysis with Delays. MLSP (2023)
Ambroise Heurtebise, Pierre Ablin, Alexandre Gramfort
MultiView Independent Component Analysis with Delays. CoRR (2023)
Lindsey Power, Cédric Allain, Thomas Moreau, Alexandre Gramfort, Timothy Bardouille
Using convolutional dictionary learning to detect task-related neuromagnetic transients and ageing trends in a large open-access dataset. NeuroImage 267 (2023)
Théo Gnassounou, Rémi Flamary, Alexandre Gramfort
Convolution Monge Mapping Normalization for learning on sleep data. NeurIPS (2023)
Britta U. Westner, Sarang S. Dalal, Alexandre Gramfort, Vladimir Litvak, John C. Mosher, Robert Oostenveld, Jan-Mathijs Schoffelen
A unified view on beamformers for M/EEG source reconstruction. NeuroImage 246 (2022)
Cédric Rommel, Thomas Moreau, Alexandre Gramfort
Deep invariant networks with differentiable augmentation layers. NeurIPS (2022)
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
Benchopt: Reproducible, efficient and collaborative optimization benchmarks. CoRR (2022)
Denis A. Engemann, Apolline Mellot, Richard Höchenberger, Hubert J. Banville, David Sabbagh, Lukas Gemein, Tonio Ball, Alexandre Gramfort
A reusable benchmark of brain-age prediction from M/EEG resting-state signals. NeuroImage 262 (2022)
Omar Chehab, Alexandre Gramfort, Aapo Hyvärinen
The Optimal Noise in Noise-Contrastive Learning Is Not What You Think. CoRR (2022)
Guillaume Staerman, Cédric Allain, Alexandre Gramfort, Thomas Moreau
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels. CoRR (2022)
Cédric Allain, Alexandre Gramfort, Thomas Moreau
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals. ICLR (2022)
Julia Linhart, Alexandre Gramfort, Pedro L. C. Rodrigues
Validation Diagnostics for SBI algorithms based on Normalizing Flows. CoRR (2022)
Cédric Rommel, Thomas Moreau, Joseph Paillard, Alexandre Gramfort
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals. ICLR (2022)
Juliette Millet, Charlotte Caucheteux, Pierre Orhan, Yves Boubenec, Alexandre Gramfort, Ewan Dunbar, Christophe Pallier, Jean-Remi King
Toward a realistic model of speech processing in the brain with self-supervised learning. CoRR (2022)
Juliette Millet, Charlotte Caucheteux, Pierre Orhan, Yves Boubenec, Alexandre Gramfort, Ewan Dunbar, Christophe Pallier, Jean-Remi King
Toward a realistic model of speech processing in the brain with self-supervised learning. NeurIPS (2022)
Thomas Moreau, Alexandre Gramfort
DiCoDiLe: Distributed Convolutional Dictionary Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44 (5) (2022)
Cédric Rommel, Thomas Moreau, Alexandre Gramfort
Deep invariant networks with differentiable augmentation layers. CoRR (2022)
Hubert J. Banville, Sean U. N. Wood, Chris Aimone, Denis-Alexander Engemann, Alexandre Gramfort
Robust learning from corrupted EEG with dynamic spatial filtering. NeuroImage 251 (2022)
Cédric Rommel, Joseph Paillard, Thomas Moreau, Alexandre Gramfort
Data augmentation for learning predictive models on EEG: a systematic comparison. CoRR (2022)
Alexander Rockhill, Eric Larson, Brittany Stedelin, Alessandra Mantovani, Ahmed M. Raslan, Alexandre Gramfort, Nicole C. Swann
Intracranial Electrode Location and Analysis in MNE-Python. J. Open Source Softw. 7 (69) (2022)
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Averaging Spatio-temporal Signals using Optimal Transport and Soft Alignments. CoRR (2022)
Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning. J. Mach. Learn. Res. 23 (2022)
Kenan Sehic, Alexandre Gramfort, Joseph Salmon, Luigi Nardi
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso. AutoML (2022)
Omar Chehab, Alexandre Gramfort, Aapo Hyvärinen
The optimal noise in noise-contrastive learning is not what you think. UAI (2022)
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
Benchopt: Reproducible, efficient and collaborative optimization benchmarks. NeurIPS (2022)
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 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets. CoRR (2022)
Griffin M. Weber, Chuan Hong, Zongqi Xia, Nathan P. Palmer, Paul Avillach, Sehi L'Yi, Mark S. Keller, Shawn N. Murphy, Alba Gutiérrez-Sacristán, Clara-Lea Bonzel, Arnaud Serret-Larmande, Antoine Neuraz, Gilbert S. Omenn, Shyam Visweswaran, Jeffrey G. Klann, Andrew M. South, Ne-Hooi Will Loh, Mario Cannataro, Brett K. Beaulieu-Jones, Riccardo Bellazzi, Giuseppe Agapito, Mario Alessiani, Bruce J. Aronow, Douglas S. Bell, Vincent Benoit, Florence T. Bourgeois, Luca Chiovato, Kelly Cho, Arianna Dagliati, Scott L. DuVall, Noelia García-Barrio, David A. Hanauer, Yuk-Lam Ho, John H. Holmes, Richard W. Issitt, Molei Liu, Yuan Luo, Kristine E. Lynch, Sarah Maidlow, Alberto Malovini, Kenneth D. Mandl, Chengsheng Mao, Michael E. Matheny, Jason H. Moore, Jeffrey S. Morris, Michele Morris, Danielle L. Mowery, Kee Yuan Ngiam, Lav P. Patel, Miguel Pedrera-Jiménez, Rachel B. Ramoni, Emily Schriver, Petra Schubert, Pablo Serrano-Balazote, Anastasia Spiridou, Amelia L. M. Tan, Byorn W. L. Tan, Valentina Tibollo, Carlo Torti, Enrico M. Trecarichi, Xuan Wang, James R. Aaron, Adem Albayrak, Giuseppe Albi, Anna Alloni, Danilo F. Amendola, François Angoulvant, Anthony L. L. J. Li, Fatima Ashraf, Andrew Atz, Paul Avillach, Paula S. Azevedo, James Balshi, Brett K. Beaulieu-Jones, Antonio Bellasi, Vincent Benoit, Michele Beraghi, José Luis Bernal-Sobrino, Mélodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Javier Blanco-Martínez, Martin Boeker, John Booth, Silvano Bosari, Robert L. Bradford, Gabriel A. Brat, Stéphane Bréant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Emily Bucholz, Anita Burgun, Tianxi Cai, Aldo Carmona, Charlotte Caucheteux, Julien Champ, Krista Y. Chen, Jin Chen, Lorenzo Chiudinelli, Kelly Cho, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sébastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermúdez, Jaime Cruz-Rojo, Mohamad Daniar, Christel Daniel, Priyam Das, Batsal Devkota, Audrey Dionne, Rui Duan, Julien Dubiel, Loic Esteve, Hossein Estiri, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Noelia García-Barrio, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Alba Gutiérrez-Sacristán, Larry Han, David A. Hanauer, Christian Haverkamp, Derek Y. Hazard, Bing He, Darren W. Henderson, Martin Hilka, Kenneth M. Huling, Meghan R. Hutch, Richard W. Issitt, Anne-Sophie Jannot, Vianney Jouhet, Ramakanth Kavuluru, Chris J. Kennedy, Kate F. Kernan, Daniel A. Key, Katie Kirchoff, Jeffrey G. Klann, Isaac S. Kohane, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Trang T. Le, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Qi Long, Sara Lozano-Zahonero, Sadiqa Mahmood, Sarah Maidlow, Adeline Makoudjou, Anupama Maram, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Bertrand Moal, Taha Mohseni Ahooyi, Jason H. Moore, Cinta Moraleda, Jeffrey S. Morris, Karyn L. Moshal, Sajad Mousavi, Douglas A. Murad, Shawn N. Murphy, Thomas Naughton, Carlos Tadeu Breda Neto, Jane Newburger, Kee Yuan Ngiam, Wanjiku F. M. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Gilbert S. Omenn, Nina Orlova, Brian Ostasiewski, Nathan P. Palmer, Nicolas Paris, Lav P. Patel, Miguel Pedrera-Jiménez, Ashley C. Pfaff, Emily R. Pfaff, Danielle Pillion, Sara Pizzimenti, Hans-Ulrich Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Rachel B. Ramoni, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Domínguez, Pablo Rojo, Paula Rubio-Mayo, Paolo Sacchi, Carlos Sáez, Elisa Salamanca, Malarkodi Jebathilagam Samayamuthu, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C. C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Jürgen Schüttler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Mohsin Shah, Zahra Shakeri Hossein Abad, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Andrew M. South, Francesca Sperotto, Zachary H. Strasser, Amelia L. M. Tan, Bryce W. Q. Tan, Suzana E. Tanni, Deanne M. Taylor, Ana I. Terriza-Torres, Patric Tippmann, Emma M. S. Toh, Yi-Ju Tseng, Andrew K. Vallejos, Gaël Varoquaux, Margaret E. Vella, Guillaume Verdy, Jill-Jênn Vie, Shyam Visweswaran, Michele Vitacca, Kavishwar B. Wagholikar, Lemuel R. Waitman, Demian Wassermann, Griffin M. Weber, Martin Wolkewitz, Scott Wong, Zongqi Xia, Xin Xiong, Ye Ye, Nadir Yehya, William Yuan, Alberto Zambelli, Harrison G. Zhang, Daniela Zöller, Valentina Zuccaro, Chiara Zucco, Isaac S. Kohane, Tianxi Cai, Gabriel A. Brat
International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality. npj Digit. Medicine 5 (2022)
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
Long-range and hierarchical language predictions in brains and algorithms. CoRR (2021)
Omar Chehab, Alexandre Defossez, Jean-Christophe Loiseau, Alexandre Gramfort, Jean-Remi King
Deep Recurrent Encoder: A scalable end-to-end network to model brain signals. CoRR (2021)
Pedro Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort
HNPE: Leveraging Global Parameters for Neural Posterior Estimation. NeurIPS (2021)
Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen
Shared Independent Component Analysis for Multi-Subject Neuroimaging. NeurIPS (2021)
Charlotte Caucheteux, Alexandre Gramfort, Jean-Rémi King
Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects. CoRR (2021)
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects. EMNLP (Findings) (2021)
Alexandre Gramfort, Hubert J. Banville, Omar Chehab, Aapo Hyvärinen, Denis A. Engemann
Learning with self-supervision on EEG data. BCI (2021)
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
POT: Python Optimal Transport. J. Mach. Learn. Res. 22 (2021)
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 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets. NeurIPS (Competition and Demos) (2021)
Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Implicit differentiation for fast hyperparameter selection in non-smooth convex learning. CoRR (2021)
Cédric Allain, Alexandre Gramfort, Thomas Moreau, A. Preprint
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals. CoRR (2021)
Hubert J. Banville, Sean U. N. Wood, Chris Aimone, Denis-Alexander Engemann, Alexandre Gramfort
Robust learning from corrupted EEG with dynamic spatial filtering. CoRR (2021)
Cédric Rommel, Thomas Moreau, Alexandre Gramfort
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals. CoRR (2021)
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
Disentangling syntax and semantics in the brain with deep networks. ICML (2021)
Maëliss Jallais, Pedro Rodrigues, Alexandre Gramfort, Demian Wassermann
Inverting brain grey matter models with likelihood-free inference: a tool for trustable cytoarchitecture measurements. CoRR (2021)
Maëliss Jallais, Pedro L. C. Rodrigues, Alexandre Gramfort, Demian Wassermann
Cytoarchitecture Measurements in Brain Gray Matter Using Likelihood-Free Inference. IPMI (2021)
Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen
Shared Independent Component Analysis for Multi-Subject Neuroimaging. CoRR (2021)
Marc-Andre Schulz, Bertrand Thirion, Alexandre Gramfort, Gaël Varoquaux, Danilo Bzdok
Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction. CoRR (2021)
Hugo Richard, Pierre Ablin, Aapo Hyvärinen, Alexandre Gramfort, Bertrand Thirion
Adaptive Multi-View ICA: Estimation of noise levels for optimal inference. CoRR (2021)
Pedro L. C. Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort
Leveraging Global Parameters for Flow-based Neural Posterior Estimation. CoRR (2021)
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
mvlearn: Multiview Machine Learning in Python. J. Mach. Learn. Res. 22 (2021)
Kenan Sehic, Alexandre Gramfort, Joseph Salmon, Luigi Nardi
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso. CoRR (2021)
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
Decomposing lexical and compositional syntax and semantics with deep language models. CoRR (2021)
Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Implicit differentiation of Lasso-type models for hyperparameter optimization. CoRR (2020)
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Debiased Sinkhorn barycenters. CoRR (2020)
Gabriel A. Brat, Griffin M. Weber, Nils Gehlenborg, Paul Avillach, Nathan P. Palmer, Luca Chiovato, James J. Cimino, Lemuel R. Waitman, Gilbert S. Omenn, Alberto Malovini, Jason H. Moore, Brett K. Beaulieu-Jones, Valentina Tibollo, Shawn N. Murphy, Sehi L'Yi, Mark S. Keller, Riccardo Bellazzi, David A. Hanauer, Arnaud Serret-Larmande, Alba Gutiérrez-Sacristán, John J. Holmes, Douglas S. Bell, Kenneth D. Mandl, Robert W. Follett, Jeffrey G. Klann, Douglas A. Murad, Luigia Scudeller, Mauro Bucalo, Katie Kirchoff, Jean B. Craig, Jihad Obeid, Vianney Jouhet, Romain Griffier, Sébastien Cossin, Bertrand Moal, Lav P. Patel, Antonio Bellasi, Hans-Ulrich Prokosch, Detlef Kraska, Piotr Sliz, Amelia L. M. Tan, Kee Yuan Ngiam, Alberto Zambelli, Danielle L. Mowery, Emily Schiver, Batsal Devkota, Robert L. Bradford, Mohamad Daniar, Christel Daniel, Vincent Benoit, Romain Bey, Nicolas Paris, Patricia Serre, Nina Orlova, Julien Dubiel, Martin Hilka, Anne-Sophie Jannot, Stéphane Bréant, Judith Leblanc, Nicolas Griffon, Anita Burgun, Mélodie Bernaux, Arnaud Sandrin, Elisa Salamanca, Sylvie Cormont, Thomas Ganslandt, Tobias Gradinger, Julien Champ, Martin Boeker, Patricia Martel, Loic Esteve, Alexandre Gramfort, Olivier Grisel, Damien Leprovost, Thomas Moreau, Gaël Varoquaux, Jill-Jênn Vie, Demian Wassermann, Arthur Mensch, Charlotte Caucheteux, Christian Haverkamp, Guillaume Lemaitre, Silvano Bosari, Ian D. Krantz, Andrew M. South, Tianxi Cai, Isaac S. Kohane
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium. npj Digit. Medicine 3 (2020)
Pedro L. C. Rodrigues, Alexandre Gramfort
Learning summary features of time series for likelihood free inference. CoRR (2020)
Hubert J. Banville, Omar Chehab, Aapo Hyvärinen, Denis-Alexander Engemann, Alexandre Gramfort
Uncovering the structure of clinical EEG signals with self-supervised learning. CoRR (2020)
Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort
Multi-subject MEG/EEG source imaging with sparse multi-task regression. NeuroImage 220 (2020)
Jérôme-Alexis Chevalier, Alexandre Gramfort, Joseph Salmon, Bertrand Thirion
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso. CoRR (2020)
Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin
Modeling Shared Responses in Neuroimaging Studies through MultiView ICA. CoRR (2020)
Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Implicit differentiation of Lasso-type models for hyperparameter optimization. ICML (2020)
Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin
Modeling Shared responses in Neuroimaging Studies through MultiView ICA. NeurIPS (2020)
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Debiased Sinkhorn barycenters. ICML (2020)
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Spatio-temporal alignments: Optimal transport through space and time. AISTATS (2020)
David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann
Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states. NeuroImage 222 (2020)
Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon
Support recovery and sup-norm convergence rates for sparse pivotal estimation. CoRR (2020)
Quentin Klopfenstein, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon, Samuel Vaiter
Model identification and local linear convergence of coordinate descent. CoRR (2020)
Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon
Support recovery and sup-norm convergence rates for sparse pivotal estimation. AISTATS (2020)
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
Comparison of beamformer implementations for MEG source localization. NeuroImage 216 (2020)
Jérôme-Alexis Chevalier, Joseph Salmon, Alexandre Gramfort, Bertrand Thirion
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso. NeurIPS (2020)
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
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. J. Open Source Softw. 4 (44) (2019)
Thomas Moreau, Alexandre Gramfort
Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals. CoRR (2019)
Mathurin Massias, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Dual Extrapolation for Sparse Generalized Linear Models. CoRR (2019)
Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
Beyond Pham's algorithm for joint diagonalization. ESANN (2019)
Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort
Group Level MEG/EEG Source Imaging via Optimal Transport: Minimum Wasserstein Estimates. IPMI (2019)
Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon
Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise. CoRR (2019)
David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann
Manifold-regression to predict from MEG/EEG brain signals without source modeling. NeurIPS (2019)
Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort
Learning step sizes for unfolded sparse coding. CoRR (2019)
Hubert J. Banville, Isabela Albuquerque, Aapo Hyvärinen, Graeme Moffat, Denis-Alexander Engemann, Alexandre Gramfort
Self-supervised representation learning from electroencephalography signals. CoRR (2019)
Pierre Ablin, Alexandre Gramfort, Jean-François Cardoso, Francis R. Bach
Stochastic algorithms with descent guarantees for ICA. AISTATS (2019)
Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort
Multi-subject MEG/EEG source imaging with sparse multi-task regression. CoRR (2019)
Pierre Ablin, Dylan Fagot, Herwig Wendt, Alexandre Gramfort, Cédric Févotte
A Quasi-Newton Algorithm on the Orthogonal Manifold for NMF with Transform Learning. ICASSP (2019)
Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort
Learning step sizes for unfolded sparse coding. NeurIPS (2019)
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Spatio-Temporal Alignments: Optimal transport through space and time. CoRR (2019)
Yannick Roy, Hubert J. Banville, Isabela Albuquerque, Alexandre Gramfort, Tiago H. Falk, Jocelyn Faubert
Deep learning-based electroencephalography analysis: a systematic review. CoRR (2019)
Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort
Group level MEG/EEG source imaging via optimal transport: minimum Wasserstein estimates. CoRR (2019)
Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso. NeurIPS (2019)

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Publication Activity (10 Years)

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Alexandre Gramfort