Overview of Research Papers and Resources for Graph Neural Networks and Graph Machine Learning

• Zhou, Jie, et al. "Graph neural networks: A review of methods and applications." AI open 1 (2020): 57-81.
• Wu, Zonghan, et al. "A comprehensive survey on graph neural networks." IEEE transactions on neural networks and learning systems 32.1 (2020): 4-24.
• Jiang, Weiwei, and Jiayun Luo. "Graph neural network for traffic forecasting: A survey." Expert Systems with Applications (2022): 117921. Wu, Lingfei, et al. "Graph neural networks: foundation, frontiers and applications." Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2022.

• Stamile, Claudio, Aldo Marzullo, and Enrico Deusebio. Graph Machine Learning: Take graph data to the next level by applying machine learning techniques and algorithms. Packt Publishing Ltd, 2021.
• Hamilton, William L. Graph Representation Learning. San Rafael Morgan Et Claypool, 2020.

• Leskovec, Jure. “CS224W Machine Learning with Graphs | Home.” Web.stanford.edu, 2022, web.stanford.edu/class/cs224w/.