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Springer Topological Methods in Data Analysis and Visualization V

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Description

This peer-reviewed collection explores cutting-edge research in topological approaches to analysing and visualising complex data. The book covers fast homology computation methods, comparative simplification techniques, and practical applications across materials and medical science. It addresses core research challenges including representation of large and complex datasets whilst integrating numerical methods with robust combinatorial algorithms. Designed for researchers and practitioners working with data analysis and visualisation, this Mathematics and Visualization volume from Springer presents the latest algorithmic advances and theoretical insights from the TopoInVis workshop series, offering solutions to the most pressing problems in topological data analysis today.

Key Features

Features peer-reviewed workshop papers covering fast homology computation and comparative simplification techniques for advanced data analysis.

Addresses representation and analysis of large and complex datasets through topological methods and visualization approaches.

Integrates numerical methods with combinatorial algorithms to solve practical research challenges in data science.

Includes applications in materials science and medical science, demonstrating real-world uses of topological data analysis.

Published by Springer as part of the Mathematics and Visualization series, ensuring academic rigour and peer-review standards.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
12 December 2021
Listed Since
14 November 2021

Barcode

No barcode data available

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