Topological Methods in Data Analysis and Visualization V

This collection of peer-reviewed workshop papers provides comprehensive coverage of cutting-edge research into topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The book also addresses core research challenges such as the representation of large and complex datasets, and integrating numerical methods with robust combinatorial algorithms.

In keeping with the focus of the TopoInVis 2017 Workshop, the contributions reflect the latest advances in finding experimental solutions to open problems in the sector. They provide an essential snapshot of state-of-the-art research, helping researchers to keep abreast of the latest developments and providing a basis for future work. Gathering papers by some of the world's leading experts on topological techniques, thebook represents a valuable contribution to a field of growing importance, with applications in disciplines ranging from engineering to medicine.

Covers the full range of cutting-edge research in the sector Features work by the most prominent and respected researchers Addresses key issues such as representing big data Contains papers on the latest developments including fast homology computation

Inhalt
Persistence.- Scalar Topology.- Time-Varying Topology.- Multivariate Topology.- Other Forms of Topology.