Machine Learning, Artificial Intelligence, Graph Neural Networks, Deep Learning, Data Science.
Graphs are applicable to many real-world datasets such as social networks, citation networks, chemical graphs, etc. The growing interest in graph-structured data increases the number of researches in graph neural networks. Variational autoencoders (VAEs) embodied the success of variational Bayesian