Graph Neural Networks: Foundation, Frontiers and Applications
Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo
Abstract
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the recent years. Graph neural networks, also known as deep learning on graphs, graph representation learning, or geometric deep learning, have become one of the fastest-growing research topics in machine learning, especially deep learning. However, as the field rapidly grows, it has been extremely challenging to gain a global perspective of the developments of GNNs. Therefore, we feel the urgency to bridge the above gap and have a comprehensive tutorial on this fast-growing yet challenging topic.
Topics & Concepts
Deep learningComputer scienceArtificial intelligenceGraphArtificial neural networkDeep neural networksData scienceMachine learningTheoretical computer scienceAdvanced Graph Neural NetworksGraph Theory and Algorithms