Post #81

Random Features Strengthen Graph Neural Networks Continuation of the previous post, a recent submission to ICML 20 by Sato et al. This is quite cool as it shows you can add a random number to your node embedding and it would become a more powerful GNN. They improved bounds on Minimum Dominating Set and Maximum Matching problems and showed that it can recognize graphs that other GNNs cannot.