Graph theory analysis, a mathematical approach, has been applied in brain connectivity studies to explore the organization of network patterns. The computation of graph theory metrics enables the ...

Synopsys is set for a faster rebound due to China sales resuming, an $8B backlog, and strong AI-driven tool demand. Click ...

In recent years, with the public availability of AI tools, more people have become aware of how closely the inner workings of ...

This review examines AI and ML's role in transforming thermoelectric materials design, focusing on defect engineering and ...

Learn how Pigment’s AI-driven platform transforms planning, forecasting, budgeting, and decision-making with cutting-edge ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

Edges and nodes form the core elements of heterogeneous graphs (HGs). However, existing heterogeneous graph neural networks (HGNNS) largely rely on meta-paths to capture semantic information of nodes, ...

xAI’s graph showed two variants of Grok 3, Grok 3 Reasoning Beta and Grok 3 mini Reasoning, beating OpenAI’s best-performing available model, o3-mini-high, on AIME 2025.

Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

In conclusion, researchers have proposed LGGM, a new class of graph generative model that is trained on over 5,000 graphs sourced from 13 distinct domains from the well-known Network Repository. LGGM ...