Graph neural networks have emerged as a leading paradigm for inferring node labels in complex relational data. By extending convolutional and attention operations to arbitrary graph structures, these ...

FastNoise2 is built around a node graph architecture. Rather than calling standalone functions to generate noise, you build a tree of interconnected nodes, then evaluate the root node to get the final ...

The Graph’s creator team, Edge & Node, has formally joined the LF Decentralized Trust, a collaborative project under the Linux Foundation centered on the open development of standards and ...

Abstract: Class imbalance with node quantity or node topology challenges graph node classification in real-world, such as fake user identification and fraud finance detection in social networks.

Abstract: Graph Edit Distance (GED) is a classical graph similarity metric. Since exact GED computation is NP-hard, existing GNN-based methods try to approximate GED in polynomial time. However, they ...