Graphs are everywhere. In discrete mathematics, they are structures that show the connections between points, much like a public transportation network. Mathematicians have long sought to develop ...

Machine learning models are often drowning in data, but the problem is not always the sheer volume of samples. Increasingly, ...

Clustering algorithms are the workhorses of modern data science, quietly sorting everything from medical images to customer records into meaningful groups without any labels to guide them. Yet for all ...

This book offers a refreshing approach to complex concepts by blending humor, imaginative examples, and practical Python implementations to reveal the power and versatility of graph based ...

Uncover the latest and most impactful research in Graph Theory in Probability. Explore pioneering discoveries, insightful ideas and new methods from leading researchers in the field. Mounting ...

A professor has helped create a powerful new algorithm that uncovers hidden patterns in complex networks, with potential uses in fraud detection, biology and knowledge discovery. University of ...

StellarGraph has launched a series of new algorithms for network graph analysis to help discover patterns in data, work with larger data sets and speed up performance while reducing memory usage.

A quantum photonic device can perform some real-world tasks more efficiently than classical computers. Quantum computers can outperform their classical counterparts when solving certain computational ...

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 ...

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 ...