Publications (47)
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series
Stanislas Chambon, Mathieu Galtier, Pierrick Arnal +2
Machine Learning for Neuroimaging with Scikit-Learn
Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg +6
HRF estimation improves sensitivity of fMRI encoding and decoding models
Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion +1
Deep learning-based electroencephalography analysis: a systematic review
Yannick Roy, Hubert Banville, Isabela Albuquerque +3
Small-sample Brain Mapping: Sparse Recovery on Spatially Correlated Designs with Randomization and Clustering
Gael Varoquaux, Alexandre Gramfort, Bertrand Thirion
A hierarchical Bayesian perspective on majorization-minimization for non-convex sparse regression: application to M/EEG source imaging
Yousra Bekhti, Felix Lucka, Joseph Salmon +1
Fast Optimal Transport Averaging of Neuroimaging Data
Alexandre Gramfort, Gabriel Peyré, Marco Cuturi
Learning step sizes for unfolded sparse coding
Pierre Ablin, Thomas Moreau, Mathurin Massias +1
DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal
Stanislas Chambon, Valentin Thorey, Pierrick J. Arnal +2
Faster independent component analysis by preconditioning with Hessian approximations
Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
Anomaly Detection and Localisation using Mixed Graphical Models
Romain Laby, François Roueff, Alexandre Gramfort
GAP Safe screening rules for sparse multi-task and multi-class models
Eugene Ndiaye, Olivier Fercoq, Alexandre Gramfort +1
Learning to rank from medical imaging data
Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux +3
Improved brain pattern recovery through ranking approaches
Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux +3
Markov models for fMRI correlation structure: is brain functional connectivity small world, or decomposable into networks?
Gaël Varoquaux, Alexandre Gramfort, Jean Baptiste Poline +1
Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy
Laetitia Le, Camille Marini, Alexandre Gramfort +9
Data-driven HRF estimation for encoding and decoding models
Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu +2
Total variation regularization for fMRI-based prediction of behaviour
Vincent Michel, Alexandre Gramfort, Gaël Varoquaux +2
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals
Tom Dupré La Tour, Thomas Moreau, Mainak Jas +1
Gap Safe screening rules for sparsity enforcing penalties
Eugene Ndiaye, Olivier Fercoq, Alexandre Gramfort +1
Mind the duality gap: safer rules for the Lasso
Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
Multi-scale Mining of fMRI data with Hierarchical Structured Sparsity
Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel +4
A Quasi-Newton algorithm on the orthogonal manifold for NMF with transform learning
Pierre Ablin, Dylan Fagot, Herwig Wendt +2
GAP Safe Screening Rules for Sparse-Group-Lasso
Eugene Ndiaye, Olivier Fercoq, Alexandre Gramfort +1
Group level MEG/EEG source imaging via optimal transport: minimum Wasserstein estimates
Hicham Janati, Thomas Bazeille, Bertrand Thirion +2
Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals
Thomas Moreau, Alexandre Gramfort
Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression
Eugene Ndiaye, Olivier Fercoq, Alexandre Gramfort +2
A supervised clustering approach for fMRI-based inference of brain states
Vincent Michel, Alexandre Gramfort, Gaël Varoquaux +3
Brain covariance selection: better individual functional connectivity models using population prior
Gaël Varoquaux, Alexandre Gramfort, Jean Baptiste Poline +1
Faster ICA under orthogonal constraint
Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding
Mainak Jas, Tom Dupré La Tour, Umut ÅimÅekli +1
On the Consistency of Ordinal Regression Methods
Fabian Pedregosa, Francis Bach, Alexandre Gramfort
Stochastic algorithms with descent guarantees for ICA
Pierre Ablin, Alexandre Gramfort, Jean-François Cardoso +1
Autoreject: Automated artifact rejection for MEG and EEG data
Mainak Jas, Denis A. Engemann, Yousra Bekhti +2
Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals
Sebastian Hitziger, Maureen Clerc, Alexandre Gramfort +3
Celer: a Fast Solver for the Lasso with Dual Extrapolation
Mathurin Massias, Alexandre Gramfort, Joseph Salmon
A deep learning architecture to detect events in EEG signals during sleep
Stanislas Chambon, Valentin Thorey, Pierrick J. Arnal +2
Scikit-learn: Machine Learning in Python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort +16
From safe screening rules to working sets for faster Lasso-type solvers
Mathurin Massias, Alexandre Gramfort, Joseph Salmon
API design for machine learning software: experiences from the scikit-learn project
Lars Buitinck, Gilles Louppe, Mathieu Blondel +12
Second order scattering descriptors predict fMRI activity due to visual textures
Michael Eickenberg, Fabian Pedregosa, Senoussi Mehdi +2
Accelerating likelihood optimization for ICA on real signals
Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
The iterative reweighted Mixed-Norm Estimate for spatio-temporal MEG/EEG source reconstruction
Daniel Strohmeier, Yousra Bekhti, Jens Haueisen +1
Blind Denoising with Random Greedy Pursuits
Manuel Moussallam, Alexandre Gramfort, Laurent Daudet +1
Generalized Concomitant Multi-Task Lasso for sparse multimodal regression
Mathurin Massias, Olivier Fercoq, Alexandre Gramfort +1
Wasserstein regularization for sparse multi-task regression
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Calibration of One-Class SVM for MV set estimation
Albert Thomas, Vincent Feuillard, Alexandre Gramfort