Abstract: Graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks. However, existing graph CNNs generally use a fixed ...

As more businesses incorporate AI agents into their operations, visibility and auditability around their usage is critical to building acceptance and trust. It’s increasingly apparent that the next ...

Developers no longer work in the background. They are at the centre of progress, shaping how GenAI evolves and how it ...

Abstract: We propose a Multi-graph Attention spatial-temporal graph convolutional network (MGA-STGCN) for AHP risk forecasting. To describe the temporal and spatial features of the area, we use ...

Neo4j, a leading graph intelligence platform, is releasing Neo4j Fleet Manager—a unified control plane for managing and monitoring graph databases across any environment including cloud, hybrid, and ...