Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Whether you’re genuinely interested in getting insights and solving problems using data, or just attracted by what has been called “the most promising career” by LinkedIn and the “best job in America” ...

These past few months have not been kind to any of us. The ripples caused by the COVID-19 crisis are felt far and wide, and the world's economies have taken a staggering blow. As with most things in ...

Graph technology has become a requirement for the modern enterprise. Companies in virtually every industry, from healthcare to energy to financial services, are applying the power of graph analytics ...

All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links. Learn more. Graph ...

The problem: The app must store a collection of people and who they know. Sometimes it must find out everyone who knows someone who knows Bob. Sometimes it must look further for everyone who is three ...

Franz’s AllegroGraph 7.2 Powers Enterprise Data Fabrics With Graph Neural Networks, Virtual Graphs and Streaming Graph Pipelines Organizations Gain ‘Next Level AI’ by Merging Knowledge Graphs with ...

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...

What Is a Graph Database? Your email has been sent Explore the concept of graph databases, their use cases, benefits, drawbacks, and popular tools. A graph database is a dynamic database management ...