1 INTRODUCTION  
2 NOTATIONS AND PRELIMINARIES  
3 GRAPH RECURRENT NEURAL NETWORKS  
3.1 Node-level RNNs  
3.2 Graph-level RNNs  
4 GRAPH CONVOLUTIONAL NETWORKS  
4.1 Convolution Operations  
4.2 Readout Operations  
4.3 Improvements and Discussions  
5 GRAPH AUTOENCODERS  
5.1 Autoencoders  
5.2 Variational Autoencoders  
5.3 Improvements and Discussions  
6 GRAPH REINFORCEMENT LEARNING  
7 GRAPH ADVERSARIAL METHODS  
7.1 Adversarial Training  
7.2 Adversarial Attacks  
8 DISCUSSIONS AND CONCLUSION