generative model

REST-GAN: A Deep Generative Model for Resting-State EEG Synthesis and Transferable Representation Learning

Researchers introduce REST-GAN, a generative adversarial network for resting-state EEG that both synthesizes realistic neural signals and learns transferable representations. The model achieves high precision and recall in band-power features and shows competitive performance in demographic classification tasks, requiring substantially less training data and computational resources than existing methods.