Coastal landscapes are constantly being reshaped by natural forces, and as climate change causes more frequent storms and sea ...

Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of ...

Abstract: Federated Graph Learning (FGL) combines the powerful graph data modeling capabilities of Graph Neural Networks (GNNs) with the distributed processing requirements of intelligent ...

AI hallucinations about a brand come in many types: A generative AI system might show a person who isn’t the actual founder, display the wrong address for the headquarters, or describe an old product ...

Abstract: This paper investigates a GraphRAG framework that integrates knowledge graphs into the Retrieval-Augmented Generation (RAG) architecture to enhance networking applications. While RAG has ...

Credit: Image generated by VentureBeat with FLUX-pro-1.1 Without data, enterprise AI isn't going to be successful. Getting all the data in one place and having the right type of data tools, including ...

A TechRadar article noted that nearly 90% of enterprise information (documents, emails, videos) lies dormant in unstructured systems. This "dark data" isn't just neglected; it's a liability. GenAI ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...