ResVGAE: Going Deeper with Residual Modules for Link Prediction

Indrit Nallbani, Reyhan Kevser Keser, Aydin Ayanzadeh +2

Graph autoencoders are efficient at embedding graph-based data sets. Most graph autoencoder architectures have shallow depths which limits their ability to capture meaningful relat…