Topological methods in data analysis and visualization : theory, algorithms, and applications
著者
書誌事項
Topological methods in data analysis and visualization : theory, algorithms, and applications
（Mathematics and visualization）
Springer, c2020
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注記
Other editors: Issei Fujishiro, Filip Sadlo, Shigeo Takahashi
Includes bibliographical references and index
内容説明・目次
内容説明
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, the book represents a valuable contribution to a field of growing importance, with applications in disciplines ranging from engineering to medicine.
目次
Persistence.- Scalar Topology.- Time-Varying Topology.- Multivariate Topology.- Other Forms of Topology.
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