As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Abstract: Complex networks with their nontrivial topological features and rich patterns of interactions are commonly used to model real-world systems, including social networks, biological systems, ...
The race to release world models is on as AI image and video generation company Runway joins an increasing number of startups and Big Tech companies by launching its first one. Dubbed GWM-1, the model ...
We further applied exponential random graph models (ERGMs) to assess how channel type, frame, and their interaction influence the formation of ties. Results: The Pro-Ana Advocacy frames were primarily ...
Microsoft Corp. today is expanding its Fabric data platform with the addition of native graph database and geospatial mapping capabilities, saying the enhancements enhance Fabric’s capacity to power ...
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 ...
1 School of Big Data and Statistics, Guizhou University of Finance and Economics, Guiyang, China 2 Audit Office, Guizhou University of Finance and Economics, Guiyang, China The performance of Dynamic ...
Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision ...
Abstract: We study human mobility networks through timeseries of contacts between individuals. Our proposed Random Walkers Induced temporal Graph (RWIG) model generates temporal graph sequences based ...
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