IEEE

Convolutional Variational Autoencoder for Anomaly Detection in On-Load Tap Changers

Abstract: Transformer outages significantly impact the reliability and cost efficiency of power systems. Studies indicate that approximately 30% of transformer failures stem from issues with on-load ...
IEEE

Subject Representation Learning from EEG using Graph Convolutional Variational Autoencoders

Abstract: 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 ...