Graph Representation Learning
2 benchmarks982 papers
The goal of Graph Representation Learning is to construct a set of features (‘embeddings’) representing the structure of the graph and the data thereon. We can distinguish among Node-wise embeddings, representing each node of the graph, Edge-wise embeddings, representing each edge in the graph, and Graph-wise embeddings representing the graph as a whole.
<span class="description-source">Source: SIGN: Scalable Inception Graph Neural Networks </span>