2 citations · 2 across the 2 of their papers we have counts for
3 papers
What masking geometry works best for EEG foundation models?
Pierre Guetschel, Bruno Aristimunha, Yassine El Ouahidi +3
EEG foundation models hold promise for scalable brain-signal decoding across clinical and cognitive neuroscience applications, yet their pre-training pipelines remain poorly unders…
Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding
Yassine El Ouahidi, Giulia Lioi, Nicolas Farrugia +2
In the context of Brain-Computer Interfaces, we propose an adaptive method that reaches offline performance level while being usable online without requiring supervision. Interesti…
A Strong and Simple Deep Learning Baseline for BCI MI Decoding
Yassine El Ouahidi, Vincent Gripon, Bastien Pasdeloup +3
We propose EEG-SimpleConv, a straightforward 1D convolutional neural network for Motor Imagery decoding in BCI. Our main motivation is to propose a simple and performing baseline t…