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 ...

Imagine 100 dots scattered in front of you. In a haphazard variation on connect-the-dots, start drawing lines between the points. How many lines can you draw without producing a triangle? A square? An ...

Six years ago, Afonso Bandeira and Shuyang Ling were attempting to come up with a better way to discern clusters in enormous data sets when they stumbled into a surreal world. Ling realized that the ...

Creating a graph doesn’t need to be difficult once you have the right tools at your disposal. Now, instead of having to draw a graph on a piece of paper, or use advanced applications to get the job ...

Graph databases represent one of the fastest-growing areas in the database market. MarketsandMarkets’ report on graph databases predicts that graph databases will grow from $1.9 billion in 2021 to ...