3 citations · 5 across the 4 of their papers we have counts for
4 papers
REVE: A Foundation Model for EEG -- Adapting to Any Setup with Large-Scale Pretraining on 25,000 Subjects
Yassine El Ouahidi, Jonathan Lys, Philipp Thölke +5
Foundation models have transformed AI by reducing reliance on task-specific data through large-scale pretraining. While successful in language and vision, their adoption in EEG has…
AutoMashup: Automatic Music Mashups Creation
Marine Delabaere, Léa Miqueu, Michael Moreno +8
We introduce AutoMashup, a system for automatic mashup creation based on source separation, music analysis, and compatibility estimation. We propose using COCOLA to assess compatib…
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…