Graph neural networks 

GNNs were introduced in 2005 and have received a lot of attention during the last 5 years or so. The key concept behind them is to try to generalize the ideas behind CNNs and RNNs to apply them to any type of dataset, including graphs. This section is only a short introduction to GNNs, since we would require an entire book to fully explore the topic. As usual, more references are given in the Further reading section if you would like to gain a deeper understanding of this topic.