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MOABB bibliography
Sylvain Chevallier edited this page Dec 3, 2022
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To cite MOABB, you could use the following paper:
Vinay Jayaram and Alexandre Barachant. "MOABB: trustworthy algorithm benchmarking for BCIs." Journal of neural engineering 15.6 (2018): 066011. DOI
To explore academic works that cite/use MOABB you can check out the Connected Papers Link
- P. Guetschel, T. Papadopoulo, M. Tangermann. Embedding neurophysiological signals. Proc. of the IEEE MetroXRAINE conference, Oct 2022, Roma, Italy. HAL
- Zoumpourlis, G., & Patras, I. (2022). Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative Training. arXiv preprint arXiv:2211.11460.
- Matthijs Pals, Rafael J. Pérez Belizón, Nicolas Berberich, Stefan K. Ehrlich, John Nassour & Gordon Cheng. "Demonstrating the Viability of Mapping Deep Learning Based EEG Decoders to Spiking Networks on Low-powered Neuromorphic Chips", IEEE Engineering in Medicine & Biology Society (EMBC). DOI
- Jan Sosulski, Jan-Philip Kemmer & Michael Tangermann Improving Covariance Matrices Derived from Tiny Training Datasets for the Classification of Event-Related Potentials with Linear Discriminant Analysis. Neuroinformatics (2020). DOI
- Xu, Jiachen, Moritz Grosse-Wentrup, and Vinay Jayaram. "Tangent space spatial filters for interpretable and efficient Riemannian classification." Journal of neural engineering 17.2 (2020): 026043. DOI
- Rodrigues, Pedro, Marco Congedo, and Christian Jutten. "Dimensionality transcending: a method for merging BCI datasets with different dimensionalities." IEEE Transactions on Biomedical Engineering (2020). DOI
- Xu, Jiachen, Moritz Grosse-Wentrup, and Vinay Jayaram. "Interpretable Riemannian classification in brain-computer interfacing." (2019). DOI
- Xu, Jiachen, Vinay Jayaram, Bernhard Schölkopf, Moritz Grosse-Wentrup. "Feature extraction from the Hermitian manifold for Brain-Computer Interfaces." 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2019. DOI
- Congedo, Marco, Pedro Luiz Coelho Rodrigues, and Christian Jutten. "The Riemannian minimum distance to means field classifier." 8th Graz Brain-Computer Interface Conference 2019. 2019. DOI
- Rodrigues, Pedro Luiz Coelho, Christian Jutten, and Marco Congedo. "Riemannian procrustes analysis: Transfer learning for brain–computer interfaces." IEEE Transactions on Biomedical Engineering 66.8 (2018): 2390-2401. DOI
- Vinay Jayaram and Alexandre Barachant. "MOABB: trustworthy algorithm benchmarking for BCIs." Journal of neural engineering 15.6 (2018): 066011. DOI