Networking technology took center stage at Nvidia’s GTC DC developers show in Washington, D.C. as a range of networking products were introduced for high-performance AI inference processing and more.

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Abstract: As we know, power flow calculation is fundamental to power systems. Currently, the mainstream power flow algorithms utilize programming for power flow calculations. However, when faced with ...

LangGraph is a powerful framework by LangChain designed for creating stateful, multi-actor applications with LLMs. It provides the structure and tools needed to build sophisticated AI agents through a ...

The global energy sector is undergoing a transformation, with the electric grid expanding to accommodate an increasing number of assets, including solar arrays, wind farms, batteries, electric ...

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...

1 Business College, California State University, Long Beach, CA, United States 2 School of Business and Management, Shanghai International Studies University, Shanghai, China In common graph neural ...

What if you could transform raw data into a sleek, interactive dashboard in just 10 minutes? It might sound ambitious, but with the right tools and guidance, it’s entirely possible. Imagine walking ...