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Alexandre Gramfort

Alexandre Gramfort

D-Index & Metrics

Computer Science

D-Index
56
Citations
99800
World Ranking
3924
National Ranking
1860

Overview

Alexandre Gramfort is affiliated with META in the United States. Their research spans multiple domains within neuroscience and computer science. The primary fields of study addressed in their publications include Neuroscience and Computer Science, with significant contributions also found in Cognitive Neuroscience, Artificial Intelligence, Signal Processing, Radiology, Nuclear Medicine and Imaging, and Computer Vision and Pattern Recognition.

The scientist's work focuses on key topics such as EEG and Brain-Computer Interfaces, Functional Brain Connectivity Studies, Neural dynamics and brain function, Blind Source Separation Techniques, Sparse and Compressive Sensing Techniques, Neurobiology of Language and Bilingualism, and Topic Modeling.

Alexandre Gramfort has published extensively in a variety of venues, among which the most frequent are arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), NeuroImage, Zenodo (CERN European Organization for Nuclear Research), and Imaging Neuroscience.

Some of their recent papers include the following:

  • Evidence of a predictive coding hierarchy in the human brain listening to speech, 2023, Nature Human Behaviour
  • Issues and recommendations from the OHBM COBIDAS MEEG committee for reproducible EEG and MEG research, 2020, Nature Neuroscience
  • Uncovering the structure of clinical EEG signals with self-supervised learning, 2020, arXiv (Cornell University)
  • Combining magnetoencephalography with magnetic resonance imaging enhances learning of surrogate-biomarkers, 2020, eLife
  • A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms, 2022, Scientific Data

The scientist has collaborated frequently with several coauthors, including Denis A. Engemann, Jean-Rémi King, Bertrand Thirion, Gaël Varoquaux, and Charlotte Caucheteux.

Best Publications

  • Scikit-learn: Machine Learning in Python

    Fabian Pedregosa;Gaël Varoquaux;Alexandre Gramfort;Vincent Michel

  • MEG and EEG data analysis with MNE-Python

    Alexandre Gramfort;Martin Luessi;Eric Larson;Denis A. Engemann

  • Machine learning for neuroimaging with scikit-learn.

    Alexandre Abraham;Alexandre Abraham;Fabian Pedregosa;Fabian Pedregosa;Michael Eickenberg;Michael Eickenberg;Philippe Gervais;Philippe Gervais

  • MNE software for processing MEG and EEG data

    Alexandre Gramfort;Martin Luessi;Eric Larson;Denis A. Engemann

  • API design for machine learning software: experiences from the scikit-learn project

    Lars Buitinck;Gilles Louppe;Mathieu Blondel;Fabian Pedregosa

  • OpenMEEG: opensource software for quasistatic bioelectromagnetics

    Alexandre Gramfort;Théodore Papadopoulo;Emmanuel Olivi;Maureen Clerc

  • Deep learning-based electroencephalography analysis: a systematic review.

    Yannick Roy;Hubert J. Banville;Isabela Albuquerque;Alexandre Gramfort

  • Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state.

    Jacobo Diego Sitt;Jacobo Diego Sitt;Jacobo Diego Sitt;Jean-Remi King;Jean-Remi King;Jean-Remi King;Imen El Karoui;Benjamin Rohaut

  • Scikit-learn: Machine Learning in Python

    Fabian Pedregosa;Gaël Varoquaux;Alexandre Gramfort;Vincent Michel

  • A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series

    Stanislas Chambon;Mathieu N. Galtier;Pierrick J. Arnal;Gilles Wainrib

  • Autoreject: Automated artifact rejection for MEG and EEG data.

    Mainak Jas;Denis A. Engemann;Yousra Bekhti;Federico Raimondo

  • Seeing it all: Convolutional network layers map the function of the human visual system

    Michael Eickenberg;Michael Eickenberg;Michael Eickenberg;Alexandre Gramfort;Gaël Varoquaux;Bertrand Thirion;Bertrand Thirion

  • Brain covariance selection: better individual functional connectivity models using population prior

    Gael Varoquaux;Alexandre Gramfort;Jean-baptiste Poline;Bertrand Thirion

  • Evidence of a predictive coding hierarchy in the human brain listening to speech

    Unknown

  • Time-frequency mixed-norm estimates: Sparse M/EEG imaging with non-stationary source activations

    Alexandre Gramfort;Daniel Strohmeier;Jens Haueisen;Matti S. Hämäläinen

  • Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods

    Alexandre Gramfort;Matthieu Kowalski;Matti Hämäläinen

  • Machine Learning for Neuroimaging with Scikit-Learn

    Alexandre Abraham;Fabian Pedregosa;Michael Eickenberg;Philippe Gervais

  • Multi-subject dictionary learning to segment an atlas of brain spontaneous activity

    Gael Varoquaux;Alexandre Gramfort;Fabian Pedregosa;Vincent Michel

  • Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.

    Denis A. Engemann;Alexandre Gramfort

  • Issues and recommendations from the OHBM COBIDAS MEEG committee for reproducible EEG and MEG research.

    Cyril Pernet;Marta I. Garrido;Alexandre Gramfort;Natasha Maurits

  • Single-trial decoding of auditory novelty responses facilitates the detection of residual consciousness.

    Jean-Remi King;Frédéric Faugeras;Alexandre Gramfort;Alexandre Gramfort;Alexandre Gramfort;Aaron Schurger;Aaron Schurger

  • Total Variation Regularization for fMRI-Based Prediction of Behavior

    V. Michel;A. Gramfort;G. Varoquaux;E. Eger

Frequent Co-Authors

Gaël Varoquaux
Gaël Varoquaux French Institute for Research in Computer Science and Automation - INRIA
Bertrand Thirion
Bertrand Thirion University of Paris-Saclay
Matti Hämäläinen
Matti Hämäläinen Harvard Medical School
Marco Cuturi
Marco Cuturi École Nationale de la Statistique et de l'Administration Économique
Jens Haueisen
Jens Haueisen Ilmenau University of Technology
Virginie van Wassenhove
Virginie van Wassenhove University of Paris-Saclay
Jean-Rémi King
Jean-Rémi King École Normale Supérieure
Cédric Lemogne
Cédric Lemogne Université Paris Cité
Aapo Hyvärinen
Aapo Hyvärinen University of Helsinki
Francis Bach
Francis Bach École Normale Supérieure

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