I. INTRODUCTION

II. DYNAMIC NETWORKS  
A. Dynamic Network Representations  
B. Link Duration Spectrum  
C. Node Dynamics  
D. The Dynamic Network Cube  
E. Dynamic Network Models  
F. Discussion and Summary

III. DYNAMIC GRAPH NEURAL NETWORKS  
A. Pseudo-Dynamic Models  
B. Edge-Weighted Models  
C. Discrete Dynamic Graph Neural Networks  
D. Continuous Dynamic Graph Neural Networks  
E. Discussion and Summary

IV. DEEP LEARNING FOR PREDICTION OF NETWORK TOPOLOGY  
A. Decoders  
B. Loss Functions  
C. Evaluation Metrics  
D. Discussion and Summary

V. CHALLENGES AND FUTURE WORK