3 papers
cs.LG2026
SpecMoE: Spectral Mixture-of-Experts Foundation Model for Cross-Species EEG Decoding
Davy Darankoum, Chloé Habermacher, Julien Volle +1
Decoding the orchestration of neural activity in electroencephalography (EEG) signals is a central challenge in bridging neuroscience with artificial intelligence. Foundation model…
cs.LG2025
From Epilepsy Seizures Classification to Detection: A Deep Learning-based Approach for Raw EEG Signals
Davy Darankoum, Manon Villalba, Clelia Allioux +8
Epilepsy represents the most prevalent neurological disease in the world. One-third of people suffering from mesial temporal lobe epilepsy (MTLE) exhibit drug resistance, urging th…
cs.LG2025
CoSupFormer : A Contrastive Supervised learning approach for EEG signal Classification
D. Darankoum, C. Habermacher, J. Volle +1
Electroencephalography signals (EEGs) contain rich multi-scale information crucial for understanding brain states, with potential applications in diagnosing and advancing the drug…