Reviews: Scalable Deep Generative Relational Model with High-Order Node Dependence

First of all, I don't think it's a good way to represent each node with a dirichlet distribution leading to a positive node embedding. It's quite different from traditional real-valued embedding methods and I assume positive embedding representations will directly reduce semantic information compared to real-valued. So if there are any other positive embedding methods, please refer them to illustrate the relation to the proposed method. As mentioned in the article, the proposed SDREM propagating information through neighbors works in a similar spirit to the spatial graph convolutional network (GCN) in a frequentist setting. But as far as I am concerned, GCNs that have already been applied, will not only consider neighboring information in graphs, but also propagate each node embedding to a deeper representation through a fully connected network.