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 ...

Part I of our series on graph analytics introduced us to graph analytics, and its brethren graph databases. We talked about the use of graph analytics to understand and visualize relationships between ...

Modern network-on-chip could include different types of nodes. Generally nodes that are of-chip external interconnections controllers – external nodes, are used in the system for I/O. Internal nodes ...

R gives the capability of creating many graphical displays. These displays are used to view data in an easier and more concise way. In other words, graphs can help us make better sense of what happens ...

For any integer 𝑘 ≥ 2, a graph 𝐺 is called 𝑘-leaf-connected if |V(G)|≥k+1 and given any subset 𝑆 ⊆ 𝑉(𝐺) with |S|=k,G always has a spanning tree 𝑇 such that 𝑆 is precisely the set of leaves of ...

In just three pages, a Russian mathematician has presented a better way to color certain types of networks than many experts thought possible. A paper posted online last month has disproved a ...