  One of the hot topics in machine learning is the field of GNN. The complexity
of graph data has imposed significant challenges on existing machine learning
algorithms. Recently, many studies on extending deep learning approaches for
graph data have emerged. This paper represents a survey, providing a
comprehensive overview of Graph Neural Networks (GNNs). We discuss the
applications of graph neural networks across various domains. Finally, we
present an advanced field in GNNs: graph generation.
