Graph algorithms constitute a fundamental area of computational research that focuses on the analysis and manipulation of graph structures, which represent systems of interconnected entities. In ...

Graph labeling is a central topic in combinatorial optimisation that involves assigning numerical or categorical labels to vertices or edges of a graph subject to specific constraints. This framework ...

In algorithms, as in life, negativity can be a drag. Consider the problem of finding the shortest path between two points on a graph — a network of nodes connected by links, or edges. Often, these ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this episode, Thomas Betts chats with ...

This is what a machine learning algorithm looks like, according to Nigel Toon, CEO of Bristol start-up Graphcore. The false colour image has been created by the firm’s graph compiler software, which ...

Nvidia has expanded its support of NetworkX graph analytic algorithms in RAPIDS, its open source library for accelerated computing. The expansion means data scientists can run 40-plus NetworkX ...

Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory. This past October, as Jacob Holm and Eva Rotenberg were thumbing through a ...

Neo4j is both the original graph database and the continued leader in the graph database market. Designed to store entities and relationships, and optimized to perform graph operations such as ...

The last two years have delivered a new wave of deep learning architectures designed specifically for tackling both training and inference sides of neural networks. We have covered many of them ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...