Graph data have extensive applications in various domains, including social networks, biological reaction networks, and molecular structures. Graph classification aims to predict the properties of ...

PyGSP: Graph Signal Processing in Python The PyGSP is a Python package to ease Signal Processing on Graphs. The documentation is available on Read the Docs and development takes place on GitHub. A ...

Graph anomaly detection is attracting remarkable multidisciplinary research interests ranging from finance, healthcare, and social network analysis. Recent advances on graph neural networks have ...

Includes the basic convolutional graph neural networks (selection -zero-padding and graph coarsening-, spectral, aggregation), and some non-convolutional graph neural networks as well (node-variant, ...