Browsing Faculty of Science by Subject "Graph neural networks"

Now showing items 1-2 of 2

    • Scalable subgraph representation learning through simplification 

      Louis, Paul (2023-06-01)
      Link prediction on graphs is a fundamental problem. Subgraph representation learning approaches (SGRLs), by transforming link prediction to graph classification on the subgraphs around the links, have achieved state-of-the-art ...

    • Subgraph classification through neighborhood pooling 

      Jacob, Shweta Ann (2023-06-01)
      Subgraph classification is an emerging field in graph representation learning where the task is to classify a group of nodes (i.e., a subgraph) within a graph. Graph neural networks (GNNs) are the de facto solution for ...