2025
Subject Representation Learning from EEG using Graph Convolutional Variational Autoencoders
ICASSP 2025accepted
We propose GC-VASE, a graph convolutional-based variational autoencoder that leverages contrastive learning for subject representation learning from EEG data. Our method successfully learns robust subject-specific latent representations using the split-latent space architecture tailored for subject…