I want to study NN for time-varying directed graphs. However, as this field has developed relatively recently, it is difficult to find new ways. So the question is, is there any NN that can handle such data?


I'm seeing recent trend of combining RNN/CNN with GNN(graph neural networks) so that both time dependency and topology are captured. I would suggest you to start by looking at DCRNN (Yaguang Li et al.), it's a strong baseline that everyone uses nowadays. Other good resources:

  • Graph wavenet for deep spatial-temporal graph modeling (Zonghan Wu et al.)
  • Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting (Bing Yu et al.)
  • STANN: A Spatio–Temporal Attentive Neural Network for Traffic Prediction (Zhixiang He et al.)

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