Get Free Shipping on orders over $0
Mathematics and Visualization : Theory, Algorithms, and Applications - Peer-Timo Bremer

Mathematics and Visualization

Theory, Algorithms, and Applications

By: Peer-Timo Bremer (Editor), Ingrid Hotz (Editor), Valerio Pascucci (Editor)

Hardcover | 7 May 2014

At a Glance

Hardcover


$249.00

or 4 interest-free payments of $62.25 with

 or 

Ships in 5 to 7 business days

This collection of peer-reviewed conference papers provides comprehensive coverage of cutting-edge research in 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 volume also features material on core research challenges such as the representation of large and complex datasets and integrating numerical methods with robust combinatorial algorithms.

Reflecting the focus of the TopoInVis 2013 conference, the contributions evince the progress currently being made on finding experimental solutions to open problems in the sector. They provide an inclusive snapshot of state-of-the-art research that enables researchers to keep abreast of the latest developments and provides a foundation for future progress. With papers by some of the world's leading experts in topological techniques, this volume is a major contribution to the literature in a field of growing importance with applications in disciplines that range from engineering to medicine.

Other Editions and Formats

Paperback

Published: 23rd August 2016

More in Pattern Recognition

Accelerating Deep Neural Networks - Ryoma Sato
Bandit Convex Optimisation - Tor  Lattimore

RRP $99.95

$89.75

10%
OFF
Introduction to Online Control - Elad  Hazan

RRP $95.95

$86.75

10%
OFF
Mathematics for Machine Learning - Marc Peter Deisenroth

RRP $79.95

$62.99

21%
OFF
Exploring GeoAI : Tools and Workflows - Ismael Chivite
Exploring GeoAI : Tools and Workflows - Ismael Chivite
Ram-Based Neural Networks : Progress in Neural Processing, 9 - James Austin