Graph Neural Networks have proven to be a powerful tool for harnessing graph data, which is widely used for representing rich relational information in multiple areas. However, the performance of graph neural networks largely depends on the amount of labeled data, which is subject to an expensive and time-consuming annotation process. This creates data without labels, or a label scarcity.…