Graphene could transform everything from electric cars to smartphones, but only if we can guarantee its quality. The ...

Abstract: Empowered by their remarkable advantages, graph neural networks (GNN) serve as potent tools for embedding graph-structured data and finding applications across various domains. Particularly, ...

Author Shawn Peters blends clarity and rigor to make data structures and algorithms accessible to all learners. COLORADO, CO, UNITED STATES, January 2, 2026 /EINPresswire.com/ — Vibrant Publishers ...

The primary purpose of this study is to present mathematical modeling methods inspired by graph theory operations and logic as a tool to structurally analyze the socio-economic composition of a city ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Jul 03, 2025, 10:43am EDT Business 3d tablet virtual growth ...

What if you could transform vast amounts of unstructured text into a living, breathing map of knowledge—one that not only organizes information but reveals hidden connections you never knew existed?

Graph generation is a complex problem that involves constructing structured, non-Euclidean representations while maintaining meaningful relationships between entities. Most current methods fail to ...

High sparse Knowledge Graph is a key challenge to solve the Knowledge Graph Completion task. Due to the sparsity of the KGs, there are not enough first-order neighbors to learn the features of ...