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Alexandre Gramfort

Inria, Université-Paris Saclay, Saclay, France

Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction


Oct 12, 2021
Marc-Andre Schulz, Bertrand Thirion, Alexandre Gramfort, Gaël Varoquaux, Danilo Bzdok

* Accepted at NIPS 2017 Workshop on Machine Learning for Health 

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Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects


Oct 12, 2021
Charlotte Caucheteux, Alexandre Gramfort, Jean-Rémi King

* Accepted to EMNLP 2021 (Findings) 

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CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals


Jun 25, 2021
Cédric Rommel, Thomas Moreau, Alexandre Gramfort


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Robust learning from corrupted EEG with dynamic spatial filtering


May 27, 2021
Hubert Banville, Sean U. N. Wood, Chris Aimone, Denis-Alexander Engemann, Alexandre Gramfort

* 42 pages, 9 figures 

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Implicit differentiation for fast hyperparameter selection in non-smooth convex learning


May 17, 2021
Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon


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Deep Recurrent Encoder: A scalable end-to-end network to model brain signals


Mar 29, 2021
Omar Chehab, Alexandre Defossez, Jean-Christophe Loiseau, Alexandre Gramfort, Jean-Remi King


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Decomposing lexical and compositional syntax and semantics with deep language models


Mar 02, 2021
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King


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Adaptive Multi-View ICA: Estimation of noise levels for optimal inference


Feb 22, 2021
Hugo Richard, Pierre Ablin, Aapo Hyvärinen, Alexandre Gramfort, Bertrand Thirion


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Leveraging Global Parameters for Flow-based Neural Posterior Estimation


Feb 12, 2021
Pedro L. C. Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort


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Learning summary features of time series for likelihood free inference


Dec 04, 2020
Pedro L. C. Rodrigues, Alexandre Gramfort


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Model identification and local linear convergence of coordinate descent


Oct 22, 2020
Quentin Klopfenstein, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon, Samuel Vaiter


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Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso


Sep 29, 2020
Jérôme-Alexis Chevalier, Alexandre Gramfort, Joseph Salmon, Bertrand Thirion

* 21 pages 

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Uncovering the structure of clinical EEG signals with self-supervised learning


Jul 31, 2020
Hubert Banville, Omar Chehab, Aapo Hyvärinen, Denis-Alexander Engemann, Alexandre Gramfort

* 32 pages, 9 figures 

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Modeling Shared Responses in Neuroimaging Studies through MultiView ICA


Jun 12, 2020
Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin


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Debiased Sinkhorn barycenters


Jun 03, 2020
Hicham Janati, Marco Cuturi, Alexandre Gramfort

* ICML 2020 

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Implicit differentiation of Lasso-type models for hyperparameter optimization


Feb 20, 2020
Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon


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Support recovery and sup-norm convergence rates for sparse pivotal estimation


Jan 15, 2020
Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon


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Self-supervised representation learning from electroencephalography signals


Nov 13, 2019
Hubert Banville, Isabela Albuquerque, Aapo Hyvärinen, Graeme Moffat, Denis-Alexander Engemann, Alexandre Gramfort


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Spatio-Temporal Alignments: Optimal transport through space and time


Nov 10, 2019
Hicham Janati, Marco Cuturi, Alexandre Gramfort


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Multi-subject MEG/EEG source imaging with sparse multi-task regression


Oct 14, 2019
Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort

* version 2. arXiv admin note: text overlap with arXiv:1902.04812 

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Dual Extrapolation for Sparse Generalized Linear Models


Jul 12, 2019
Mathurin Massias, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon


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Manifold-regression to predict from MEG/EEG brain signals without source modeling


Jun 07, 2019
David Sabbagh, Pierre Ablin, Gael Varoquaux, Alexandre Gramfort, Denis A. Engemann


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Learning step sizes for unfolded sparse coding


May 27, 2019
Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort

* 22 pages 

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