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 ...

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, ...

Graph colouring, the assignment of colours to the vertices of a graph so that no two adjacent vertices share the same colour, represents a canonical NP-hard combinatorial optimisation problem with ...

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...

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 ...

Algorithms are the foundation of modern computing. They help computers solve problems, process data, and make decisions efficiently. Understanding the different types of algorithms is an important ...

This is a sequence of lessons which covers the definitions in graph theory and the planarity algorithm. It includes a definitions crossword and smart notebook files for both sets of lessons. A bundle ...

A new graph-based machine learning method called GraphiRNA models the relationships among microRNAs, including negative ...