Posts by Collection

challenge

Biomag 2022 - Dementia screening challenge

Apolline Mellot, Benoit Malezieux, Cedric Allain - Winning solution, Birmingham, United Kingdom, 2022

The goal of this challenge was to classify individual Magneto-Encephalography (MEG) recordings into one of three classes: healthy, mild cognitive impairment (MCI), and dementia. MEG data from the train and test set were recorded at two different sites with the same 160-channel gradiometer MEG system but with different sampling rates (1000Hz and 2000Hz).

publications

A reusable benchmark of brain-age prediction from M/EEG resting-state signals

2022, NeuroImage

Denis A. Engemann, Apolline Mellot, Richard Höchenberger, Hubert Banville, David Sabbagh, Lukas Gemein, Tonio Ball, Alexandre Gramfort

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling

2023, Imaging Neuroscience MIT Press

Apolline Mellot, Antoine Collas, Pedro L. C. Rodrigues, Denis Engemann, Alexandre Gramfort

Novel SPD matrix representations considering cross-frequency coupling for EEG classification using Riemannian geometry

2023, 31st European Signal Processing Conference (EUSIPCO)

Maria Sayu Yamamoto, Apolline Mellot, Sylvain Chevallier, Fabien Lotte

Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets

2024, 32nd European Signal Processing Conference (EUSIPCO)

Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis Engemann, Alexandre Gramfort

Geodesic optimization for predictive shift adaptation on EEG data

2024, Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS)

Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis Engemann

Apolline Mellot

Posts by Collection

challenge

Biomag 2022 - Dementia screening challenge

publications

A reusable benchmark of brain-age prediction from M/EEG resting-state signals

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling

Novel SPD matrix representations considering cross-frequency coupling for EEG classification using Riemannian geometry

Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets

Geodesic optimization for predictive shift adaptation on EEG data

talks

Biomag 2022 - Dementia screening challenge

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling

Geodesic Optimization for Predictive Shift Adaptation on EEG data (GOPSA)