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Harmonizing and aligning M/EEG datasets with covariance


Harmonizing and aligning M/EEG datasets with covariance-based ...

This study demonstrates that the generalization of M/EEG-based regression models across datasets can be substantially enhanced by applying domain adaptation ...

Harmonizing and aligning M/EEG datasets with covariance-based ...

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling ... This article is a preprint ...

Harmonizing and aligning M/EEG datasets with covariance

Model- based dataset alignment methods can leverage the geometry of covariance matrices, leading to three steps: re- centering, re- scaling, and ...

Harmonizing and aligning M/EEG datasets with covariance-based ...

State-of-the-art predictive approaches on M/EEG signals classically represent the data by covariance matrices. Model-based dataset alignment ...

Harmonizing and aligning M/EEG datasets with ... - OpenAlex

Please enable it to continue. OpenAlex. back. Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling.

Harmonizing and aligning M/EEG datasets with covariance-based ...

State-of-the-art predictive approaches on magneto- and electroencephalography (M/EEG) signals classically represent the data by covariance matrices. Model-based ...

Harmonizing and aligning M/EEG datasets with covariance-based ...

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling. Machine Learning · Psychology · Computer ...

Imaging Neuroscience on X: "New paper in Imaging Neuroscience ...

by Apolline Mellot, Alexandre Gramfort, et al: Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance ...

arXiv:2402.03345v1 [eess.SP] 24 Jan 2024

two Stiefel matrices that are used to align the covariances of both source and target data. ... Harmonizing and aligning M/EEG datasets with ...

‪Apolline Mellot‬ - ‪Google Scholar‬

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling. A Mellot, A Collas, PLC Rodrigues, DA ...

Apolline Mellot - X.com

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive... Abstract. Neuroscience studies face ...

ComBat models for harmonization of resting-state EEG features in ...

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling. Imaging Neuroscience, 1 ...

publications - Denis A. Engemann

Engemann. Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling · Apr 27, 2023. Mellot, Apolline ...

Geodesic Optimization for Predictive Shift Adaptation on EEG data

[f] Mellot, A., Collas, A., Rodrigues, P. L., Engemann, D., & Gramfort, A. (2023). Harmonizing and aligning M/EEG datasets with covariance-based ...

Apolline Mellot (0000-0002-7001-9749) - ORCID

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling. 2023-04-27 | Preprint | Author.

Physics-informed and Unsupervised Riemannian Domain ...

205–. 219. [10] A. Mellot et al., “Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling,”.

Publications | Antoine Collas

Journal Articles · Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling · Parametric ...

Geodesic Optimization for Predictive Shift Adaptation on EEG data

Harmonizing and aligning M/EEG datasets with covariance-based techniques to enhance predictive regression modeling. Imaging Neuroscience, 1 ...

An extended clinical EEG dataset with 15,300 automatically labelled ...

(2022) published the NMT Scalp EEG dataset as another public EEG pathology dataset ... Harmonizing and aligning m/eeg datasets with covariance-based techniques to ...

8 publications - OUCI

State-of-the-art predictive approaches on M/EEG signals classically represent the data by covariance matrices. Model-based dataset alignment methods can ...