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, ...

Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...

Abstract: Graph neural network is a new neural network model in recent years, whose advantage lies in processing graph structure data. In the era of big data, people can collect a large amount of ...

Creating simple data classes in Java traditionally required substantial boilerplate code. Consider how we would represent Java’s mascots, Duke and Juggy: public class JavaMascot { private final String ...

Graphs and data visualizations are all around us—charting our steps, our election results, our favorite sports teams’ stats, and trends across our world. But too often, people glance at a graph ...

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 ...

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 ...

Neo4j Inc. today announced a new serverless offering that dramatically simplifies the deployment of its graph database offering, making it easier to use with artificial intelligence applications. Most ...

Spatial-temporal data handling involves the analysis of information gathered over time and space, often through sensors. Such data is crucial in pattern discovery and prediction. However, missing ...

The Graph, the decentralized indexing system that works much like Google for blockchains, has introduced a data standard for Web3. Called GRC-20, the standard would define how information is ...