Tag: graph neural networks
All the talks with the tag "graph neural networks".
Graph Neural Networks - Privacy and Applications
Rucha Bhalchandra JoshiPublished: at 02:00 PMThis work discusses the complex relationships within graph-structured data and the use of graph neural networks (GNNs) for tasks such as node classification and link prediction. It also addresses privacy concerns in GNNs and presents a privacy-preserving approach that safeguards local graph structures while enabling meaningful analysis and insights.
Characterizing Graph Datasets for Node Classification - Homophily-Heterophily Dichotomy and Beyond
Sikta MohantyPublished: at 02:00 PMThis work explores the concept of homophily in graph datasets and proposes a measure called adjusted homophily. It also introduces a new characteristic called label informativeness (LI) to distinguish different types of heterophily. The study shows that LI better correlates with graph neural network performance compared to traditional homophily measures.