A Hybrid Supervised and Self-Supervised Graph Neural Network for
Edge-Centric Applications
A Hybrid Supervised and Self-Supervised Graph Neural Network for
Edge-Centric Applications
This paper presents a novel graph-based deep learning model for tasks involving relations between two nodes (edge-centric tasks), where the focus lies on predicting relationships and interactions between pairs of nodes rather than node properties themselves. This model combines supervised and self-supervised learning, taking into account for the loss function …