Graph level anomaly detection (GLAD) aims to spot anomalous graphs that structure pattern and feature information are different from most normal graphs in a graph set, which is rarely studied by other ...

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...

Graph classification seeks to assign labels to entire graphs by extracting and learning from their structural patterns. Early approaches relied on graph kernels, which measure similarity by counting ...

Graphs are everywhere. Whenever a delivery company models a road network, a power grid operator tracks the flow of ...