IEEE

HGNN-GAMS: Heterogeneous Graph Neural Networks for Graph Attribute Mining and Semantic Fusion

Abstract: Heterogeneous Graph Neural Networks (HGNNs) have attracted significant research attention in recent years due to their ability to capture complex interactions among various node types in ...
GitHub

tutorial-connect-virtual-networks.md

You can connect virtual networks to each other with virtual network peering. These virtual networks can be in the same region or different regions (also known as global virtual network peering). Once ...
HackerNoon

The Race to Build AI’s Context Layer Is Really About Meaning

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
IEEE

Rotation- and Permutation-Equivariant Quantum Graph Neural Network for 3D Graph Data

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...