A Survey on GNN-based Link Prediction: Techniques, Applications, and Challenges

Explain Like I'm Normal

Researchers published a comprehensive taxonomy of Graph Neural Network (GNN) architectures specifically for link prediction, covering GCNs, GATs, and the newer Graph Transformers. This survey serves as a technical manual for anyone trying to predict relationships or missing data points within complex, interconnected datasets. It bridges the gap between raw graph theory and practical machine learning implementation.