According to our database
1,
Alexandre Gramfort
authored at least 240 papers
between 2009 and 2024.
Collaborative distances:
2024
Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference.
PLoS Comput. Biol., February, 2024
Local linear convergence of proximal coordinate descent algorithm.
Optim. Lett., January, 2024
emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography.
CoRR, 2024
Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment.
CoRR, 2024
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation.
CoRR, 2024
Geodesic Optimization for Predictive Shift Adaptation on EEG data.
CoRR, 2024
Diffusion posterior sampling for simulation-based inference in tall data settings.
CoRR, 2024
Cycling on the Freeway: The Perilous State of Open Source Neuroscience Software.
CoRR, 2024
Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications.
CoRR, 2024
Physics-Informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets.
Proceedings of the 32nd European Signal Processing Conference, 2024
2023
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Dataset, December, 2023
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Dataset, November, 2023
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Dataset, October, 2023
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Dataset, April, 2023
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Dataset, February, 2023
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Dataset, January, 2023
Using convolutional dictionary learning to detect task-related neuromagnetic transients and ageing trends in a large open-access dataset.
NeuroImage, 2023
Evaluating the structure of cognitive tasks with transfer learning.
CoRR, 2023
Convolutional Monge Mapping Normalization for learning on biosignals.
CoRR, 2023
Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation.
CoRR, 2023
L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Convolution Monge Mapping Normalization for learning on sleep data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Multiview Independent Component Analysis with Delays.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels.
Proceedings of the International Conference on Machine Learning, 2023
2022
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, December, 2022
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, October, 2022
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, October, 2022
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Dataset, July, 2022
pyRiemann/pyRiemann: v0.3.
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Dataset, July, 2022
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Dataset, June, 2022
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Dataset, June, 2022
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Dataset, June, 2022
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Dataset, May, 2022
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Dataset, May, 2022
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Dataset, April, 2022
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, March, 2022
Intracranial Electrode Location and Analysis in MNE-Python.
Dataset, February, 2022
DiCoDiLe: Distributed Convolutional Dictionary Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022
A unified view on beamformers for M/EEG source reconstruction.
NeuroImage, 2022
A reusable benchmark of brain-age prediction from M/EEG resting-state signals.
NeuroImage, 2022
Robust learning from corrupted EEG with dynamic spatial filtering.
NeuroImage, 2022
Intracranial Electrode Location and Analysis in MNE-Python.
J. Open Source Softw., 2022
Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning.
J. Mach. Learn. Res., 2022
Validation Diagnostics for SBI algorithms based on Normalizing Flows.
CoRR, 2022
Data augmentation for learning predictive models on EEG: a systematic comparison.
CoRR, 2022
Averaging Spatio-temporal Signals using Optimal Transport and Soft Alignments.
CoRR, 2022
The optimal noise in noise-contrastive learning is not what you think.
Proceedings of the Uncertainty in Artificial Intelligence, 2022
Deep invariant networks with differentiable augmentation layers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Toward a realistic model of speech processing in the brain with self-supervised learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Benchopt: Reproducible, efficient and collaborative optimization benchmarks.
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Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals.
Proceedings of the Tenth International Conference on Learning Representations, 2022
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals.
Proceedings of the Tenth International Conference on Learning Representations, 2022
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso.
Proceedings of the International Conference on Automated Machine Learning, 2022
2021
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, November, 2021
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Dataset, October, 2021
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, July, 2021
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, March, 2021
mvlearn: Multiview Machine Learning in Python.
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J. Mach. Learn. Res., 2021
POT: Python Optimal Transport.
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J. Mach. Learn. Res., 2021
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals.
CoRR, 2021
Long-range and hierarchical language predictions in brains and algorithms.
CoRR, 2021
Inverting brain grey matter models with likelihood-free inference: a tool for trustable cytoarchitecture measurements.
CoRR, 2021
Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction.
CoRR, 2021
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals.
CoRR, 2021
Deep Recurrent Encoder: A scalable end-to-end network to model brain signals.
CoRR, 2021
Decomposing lexical and compositional syntax and semantics with deep language models.
CoRR, 2021
Adaptive Multi-View ICA: Estimation of noise levels for optimal inference.
CoRR, 2021
Leveraging Global Parameters for Flow-based Neural Posterior Estimation.
CoRR, 2021
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets.
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Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021
HNPE: Leveraging Global Parameters for Neural Posterior Estimation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Shared Independent Component Analysis for Multi-Subject Neuroimaging.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Cytoarchitecture Measurements in Brain Gray Matter Using Likelihood-Free Inference.
Proceedings of the Information Processing in Medical Imaging, 2021
Disentangling syntax and semantics in the brain with deep networks.
Proceedings of the 38th International Conference on Machine Learning, 2021
Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021
Learning with self-supervision on EEG data.
Proceedings of the 9th International Winter Conference on Brain-Computer Interface, 2021
2020
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, December, 2020
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Dataset, November, 2020
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Dataset, October, 2020
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, October, 2020
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Dataset, September, 2020
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Dataset, June, 2020
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Dataset, June, 2020
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Dataset, April, 2020
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Dataset, April, 2020
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, April, 2020
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Dataset, March, 2020
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Dataset, February, 2020
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Dataset, January, 2020
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Dataset, January, 2020
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.
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,
,
npj Digit. Medicine, 2020
Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.
NeuroImage, 2020
Multi-subject MEG/EEG source imaging with sparse multi-task regression.
NeuroImage, 2020
Comparison of beamformer implementations for MEG source localization.
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,
,
NeuroImage, 2020
Learning summary features of time series for likelihood free inference.
CoRR, 2020
Model identification and local linear convergence of coordinate descent.
CoRR, 2020
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso.
CoRR, 2020
Uncovering the structure of clinical EEG signals with self-supervised learning.
CoRR, 2020
Modeling Shared responses in Neuroimaging Studies through MultiView ICA.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Debiased Sinkhorn barycenters.
Proceedings of the 37th International Conference on Machine Learning, 2020
Implicit differentiation of Lasso-type models for hyperparameter optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020
Support recovery and sup-norm convergence rates for sparse pivotal estimation.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Spatio-temporal alignments: Optimal transport through space and time.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
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Dataset, December, 2019
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Dataset, December, 2019
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Dataset, December, 2019
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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Dataset, December, 2019
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Dataset, November, 2019
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Dataset, November, 2019
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Dataset, October, 2019
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Dataset, September, 2019
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Dataset, September, 2019
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Dataset, September, 2019
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Dataset, September, 2019
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Dataset, August, 2019
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Dataset, August, 2019
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Dataset, May, 2019
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Dataset, May, 2019
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Dataset, April, 2019
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Dataset, February, 2019
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Dataset, January, 2019
MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.
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,
,
J. Open Source Softw., 2019
Dual Extrapolation for Sparse Generalized Linear Models.
CoRR, 2019
Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise.
CoRR, 2019
Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals.
CoRR, 2019
Deep learning-based electroencephalography analysis: a systematic review.
CoRR, 2019
Manifold-regression to predict from MEG/EEG brain signals without source modeling.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Learning step sizes for unfolded sparse coding.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Self-Supervised Representation Learning from Electroencephalography Signals.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019
Group Level MEG/EEG Source Imaging via Optimal Transport: Minimum Wasserstein Estimates.
Proceedings of the Information Processing in Medical Imaging, 2019
A Quasi-Newton Algorithm on the Orthogonal Manifold for NMF with Transform Learning.
Proceedings of the IEEE International Conference on Acoustics, 2019
Beyond Pham's algorithm for joint diagonalization.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019
Wasserstein regularization for sparse multi-task regression.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Stochastic algorithms with descent guarantees for ICA.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
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Dataset, December, 2018
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Dataset, November, 2018
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Dataset, November, 2018
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Dataset, October, 2018
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Dataset, September, 2018
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Dataset, August, 2018
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Dataset, July, 2018
nipy/nipype: Nipype 1.1.0.
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Dataset, July, 2018
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Dataset, May, 2018
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Dataset, May, 2018
nipy/nipype: Nipype 1.0.3.
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Dataset, April, 2018
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Dataset, March, 2018
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Dataset, February, 2018
nipy/nipype: Nipype - v1.0.0.
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Dataset, January, 2018
Faster Independent Component Analysis by Preconditioning With Hessian Approximations.
IEEE Trans. Signal Process., 2018
DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal.
CoRR, 2018
Domain adaptation with optimal transport improves EEG sleep stage classifiers.
Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
A Deep Learning Architecture to Detect Events in EEG Signals During Sleep.
Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018
Celer: a Fast Solver for the Lasso with Dual Extrapolation.
Proceedings of the 35th International Conference on Machine Learning, 2018
Driver Estimation in Non-Linear Autoregressive Models.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
An Ensemble Learning Approach to Detect Epileptic Seizures from Long Intracranial EEG Recordings.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
Faster ICA Under Orthogonal Constraint.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
Accelerating Likelihood Optimization for ICA on Real Signals.
Proceedings of the Latent Variable Analysis and Signal Separation, 2018
Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
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Dataset, November, 2017
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Dataset, November, 2017
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Dataset, November, 2017
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.1.
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Dataset, May, 2017
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.0.
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,
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Dataset, May, 2017
Non-linear auto-regressive models for cross-frequency coupling in neural time series.
PLoS Comput. Biol., 2017
Autoreject: Automated artifact rejection for MEG and EEG data.
NeuroImage, 2017
Seeing it all: Convolutional network layers map the function of the human visual system.
NeuroImage, 2017
On the Consistency of Ordinal Regression Methods.
J. Mach. Learn. Res., 2017
Gap Safe Screening Rules for Sparsity Enforcing Penalties.
J. Mach. Learn. Res., 2017
Convolutional Network Layers Map the Function of the Human Visual Cortex.
ERCIM News, 2017
From safe screening rules to working sets for faster Lasso-type solvers.
CoRR, 2017
Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy.
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,
,
,
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CoRR, 2017
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series.
CoRR, 2017
Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Parametric estimation of spectrum driven by an exogenous signal.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Caveats with Stochastic Gradient and Maximum Likelihood Based ICA for EEG.
Proceedings of the Latent Variable Analysis and Signal Separation, 2017
Hyperparameter estimation in maximum a posteriori regression using group sparsity with an application to brain imaging.
Proceedings of the 25th European Signal Processing Conference, 2017
Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.12.0-rc1.
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,
,
Dataset, April, 2016
The Iterative Reweighted Mixed-Norm Estimate for Spatio-Temporal MEG/EEG Source Reconstruction.
IEEE Trans. Medical Imaging, 2016
Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression.
CoRR, 2016
Automated rejection and repair of bad trials in MEG/EEG.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016
M/EEG source localization with multi-scale time-frequency dictionaries.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016
GAP Safe Screening Rules for Sparse-Group Lasso.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
2015
Data-driven HRF estimation for encoding and decoding models.
NeuroImage, 2015
Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.
NeuroImage, 2015
MEG/EEG Source Imaging with a Non-Convex Penalty in the Time-Frequency Domain.
Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015
Mind the Noise Covariance When Localizing Brain Sources with M/EEG.
Proceedings of the 2015 International Workshop on Pattern Recognition in NeuroImaging, 2015
GAP Safe screening rules for sparse multi-task and multi-class models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Fast Optimal Transport Averaging of Neuroimaging Data.
Proceedings of the Information Processing in Medical Imaging, 2015
Mind the duality gap: safer rules for the Lasso.
Proceedings of the 32nd International Conference on Machine Learning, 2015
FAμST: Speeding up linear transforms for tractable inverse problems.
Proceedings of the 23rd European Signal Processing Conference, 2015
Inverse problems with time-frequency dictionaries and non-white Gaussian noise.
Proceedings of the 23rd European Signal Processing Conference, 2015
Calibration of One-Class SVM for MV set estimation.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015
2014
Blind Denoising with Random Greedy Pursuits.
IEEE Signal Process. Lett., 2014
Supramodal processing optimizes visual perceptual learning and plasticity.
NeuroImage, 2014
Encoding of event timing in the phase of neural oscillations.
NeuroImage, 2014
MNE software for processing MEG and EEG data.
NeuroImage, 2014
Denoising and fast diffusion imaging with physically constrained sparse dictionary learning.
Medical Image Anal., 2014
Machine learning for neuroimaging with scikit-learn.
Frontiers Neuroinformatics, 2014
Improved MEG/EEG source localization with reweighted mixed-norms.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014
Benchmarking solvers for TV-ℓ1 least-squares and logistic regression in brain imaging.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014
Decoding perceptual thresholds from MEG/EEG.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014
2013
Single-trial decoding of auditory novelty responses facilitates the detection of residual consciousness.
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,
,
NeuroImage, 2013
Time-frequency mixed-norm estimates: Sparse M/EEG imaging with non-stationary source activations.
NeuroImage, 2013
Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals
Proceedings of the 1st International Conference on Learning Representations, 2013
API design for machine learning software: experiences from the scikit-learn project.
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,
,
CoRR, 2013
HRF Estimation Improves Sensitivity of fMRI Encoding and Decoding Models.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013
Identifying Predictive Regions from fMRI with TV-L1 Prior.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013
Second Order Scattering Descriptors Predict fMRI Activity Due to Visual Textures.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013
Non-negative Tensor Factorization for single-channel EEG artifact rejection.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013
Learning from M/EEG Data with Variable Brain Activation Delays.
Proceedings of the Information Processing in Medical Imaging, 2013
Non-negative matrix factorization for single-channel EEG artifact rejection.
Proceedings of the IEEE International Conference on Acoustics, 2013
2012
Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity.
SIAM J. Imaging Sci., 2012
A supervised clustering approach for fMRI-based inference of brain states.
Pattern Recognit., 2012
Improved Brain Pattern Recovery through Ranking Approaches.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012
Decoding Visual Percepts Induced by Word Reading with fMRI.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012
Multilayer Scattering Image Analysis Fits fMRI Activity in Visual Areas.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012
Learning to Rank from Medical Imaging Data.
Proceedings of the Machine Learning in Medical Imaging - Third International Workshop, 2012
Sparse DSI: Learning DSI Structure for Denoising and Fast Imaging.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012
Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clustering.
Proceedings of the 29th International Conference on Machine Learning, 2012
2011
Total Variation Regularization for fMRI-Based Prediction of Behavior.
IEEE Trans. Medical Imaging, 2011
Tracking cortical activity from M/EEG using graph cuts with spatiotemporal constraints.
NeuroImage, 2011
Phase delays within visual cortex shape the response to steady-state visual stimulation.
NeuroImage, 2011
Scikit-learn: Machine Learning in Python.
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,
,
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,
,
,
,
,
,
,
J. Mach. Learn. Res., 2011
Total variation regularization for fMRI-based prediction of behaviour
CoRR, 2011
Forward Field Computation with OpenMEEG.
Comput. Intell. Neurosci., 2011
Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity.
Proceedings of the 2011 International Workshop on Pattern Recognition in NeuroImaging, 2011
A Comparative Study of Algorithms for Intra- and Inter-subjects fMRI Decoding.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011
Beyond Brain Reading: Randomized Sparsity and Clustering to Simultaneously Predict and Identify.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011
Multi-subject Dictionary Learning to Segment an Atlas of Brain Spontaneous Activity.
Proceedings of the Information Processing in Medical Imaging, 2011
Functional Brain Imaging with M/EEG Using Structured Sparsity in Time-Frequency Dictionaries.
Proceedings of the Information Processing in Medical Imaging, 2011
2010
A priori par normes mixtes pour les problèmes inverses. Application à la localisation de sources en M/EEG.
Traitement du Signal, 2010
Graph-Based Variability Estimation in Single-Trial Event-Related Neural Responses.
IEEE Trans. Biomed. Eng., 2010
Brain covariance selection: better individual functional connectivity models using population prior.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
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).
PhD thesis, 2009
Improving M/EEG Source Localization with an Inter-Condition Sparse Prior.
Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28, 2009