Many datasets in various machine learning (ML) applications have structural relationships between their entities, which can be represented as graphs. Such application includes social and communication networks analysis, traffic prediction, and fraud detection. Graph representation Learning aims to build and train models for graph datasets to be used for a variety of ML tasks.