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Alexandre Barachant

Researcher at Facebook

Publications -  50
Citations -  2410

Alexandre Barachant is an academic researcher from Facebook. The author has contributed to research in topics: Riemannian geometry & Covariance matrix. The author has an hindex of 18, co-authored 50 publications receiving 1761 citations. Previous affiliations of Alexandre Barachant include University of Grenoble & Commissariat à l'énergie atomique et aux énergies alternatives.

Papers
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Journal ArticleDOI

Multiclass Brain–Computer Interface Classification by Riemannian Geometry

TL;DR: A new classification framework for brain-computer interface (BCI) based on motor imagery using spatial covariance matrices as EEG signal descriptors and relying on Riemannian geometry to directly classify these matrices using the topology of the manifold of symmetric and positive definite matrices.
Journal ArticleDOI

Classification of covariance matrices using a Riemannian-based kernel for BCI applications

TL;DR: A new kernel is derived by establishing a connection with the Riemannian geometry of symmetric positive definite matrices, effectively replacing the traditional spatial filtering approach for motor imagery EEG-based classification in brain-computer interface applications.
Journal ArticleDOI

Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review

TL;DR: A rationale for its robustness and transfer learning capabilities is provided and the link between a simple Riemannian classifier and a state-of-the-art spatial filtering approach is elucidated, enabling the conception of online decoding machines suiting real-world operation in adverse conditions.
Book ChapterDOI

Riemannian geometry applied to BCI classification

TL;DR: In this article, the authors proposed different algorithms to classify covariance matrices in their native space using a differential geometry framework, which is used for brain-computer interfaces based on motor imagery.