2 papers
eess.SP2024
Automatic Classification of Sleep Stages from EEG Signals Using Riemannian Metrics and Transformer Networks
Mathieu Seraphim, Alexis Lechervy, Florian Yger +2
Purpose: In sleep medicine, assessing the evolution of a subject's sleep often involves the costly manual scoring of electroencephalographic (EEG) signals. In recent years, a numbe…
cs.LG2024
Structure-Preserving Transformers for Sequences of SPD Matrices
Mathieu Seraphim, Alexis Lechervy, Florian Yger +2
In recent years, Transformer-based auto-attention mechanisms have been successfully applied to the analysis of a variety of context-reliant data types, from texts to images and bey…