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MOABB: Trustworthy algorithm benchmarking for BCIs

MOABB: Trustworthy algorithm benchmarking for BCIs

V. Jayaram
A. Barachant
ArXiv (abs)PDFHTMLGithub (789★)

Papers citing "MOABB: Trustworthy algorithm benchmarking for BCIs"

5 / 55 papers shown
Title
Tangent space spatial filters for interpretable and efficient Riemannian classification
Tangent space spatial filters for interpretable and efficient Riemannian classification
Jiachen Xu
Moritz Grosse-Wentrup
V. Jayaram
46
16
0
23 Sep 2019
Building Brain Invaders: EEG data of an experimental validation
Building Brain Invaders: EEG data of an experimental validation
G. V. Veen
A. Barachant
Anton Andreev
G. Cattan
Pedro L. C. Rodrigues
M. Congedo
42
23
0
13 May 2019
Brain Invaders Adaptive versus Non-Adaptive P300 Brain-Computer Interface dataset
Brain Invaders Adaptive versus Non-Adaptive P300 Brain-Computer Interface dataset
Erwan Vaineau
A. Barachant
Anton Andreev
Pedro L. C. Rodrigues
G. Cattan
M. Congedo
29
14
0
19 Apr 2019
Dataset of an EEG-based BCI experiment in Virtual Reality and on a Personal Computer
Dataset of an EEG-based BCI experiment in Virtual Reality and on a Personal Computer
G. Cattan
Anton Andreev
Pedro L. C. Rodrigues
M. Congedo
26
3
0
27 Mar 2019
Deep learning-based electroencephalography analysis: a systematic review
Deep learning-based electroencephalography analysis: a systematic review
Yannick Roy
Hubert J. Banville
Isabela Albuquerque
Alexandre Gramfort
T. Falk
J. Faubert
144
977
0
16 Jan 2019