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Topological methods in data analysis and visualization V: theory, algorithms, and applications
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 simplif...
Autores principales: | , , , |
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Lenguaje: | eng |
Publicado: |
Springer
2020
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-3-030-43036-8 http://cds.cern.ch/record/2749349 |
_version_ | 1780969038566916096 |
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author | Carr, Hamish Fujishiro, Issei Sadlo, Filip Takahashi, Shigeo |
author_facet | Carr, Hamish Fujishiro, Issei Sadlo, Filip Takahashi, Shigeo |
author_sort | Carr, Hamish |
collection | CERN |
description | 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. |
id | cern-2749349 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2020 |
publisher | Springer |
record_format | invenio |
spelling | cern-27493492021-04-21T16:44:02Zdoi:10.1007/978-3-030-43036-8http://cds.cern.ch/record/2749349engCarr, HamishFujishiro, IsseiSadlo, FilipTakahashi, ShigeoTopological methods in data analysis and visualization V: theory, algorithms, and applicationsMathematical Physics and MathematicsThis 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.Springeroai:cds.cern.ch:27493492020 |
spellingShingle | Mathematical Physics and Mathematics Carr, Hamish Fujishiro, Issei Sadlo, Filip Takahashi, Shigeo Topological methods in data analysis and visualization V: theory, algorithms, and applications |
title | Topological methods in data analysis and visualization V: theory, algorithms, and applications |
title_full | Topological methods in data analysis and visualization V: theory, algorithms, and applications |
title_fullStr | Topological methods in data analysis and visualization V: theory, algorithms, and applications |
title_full_unstemmed | Topological methods in data analysis and visualization V: theory, algorithms, and applications |
title_short | Topological methods in data analysis and visualization V: theory, algorithms, and applications |
title_sort | topological methods in data analysis and visualization v: theory, algorithms, and applications |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-3-030-43036-8 http://cds.cern.ch/record/2749349 |
work_keys_str_mv | AT carrhamish topologicalmethodsindataanalysisandvisualizationvtheoryalgorithmsandapplications AT fujishiroissei topologicalmethodsindataanalysisandvisualizationvtheoryalgorithmsandapplications AT sadlofilip topologicalmethodsindataanalysisandvisualizationvtheoryalgorithmsandapplications AT takahashishigeo topologicalmethodsindataanalysisandvisualizationvtheoryalgorithmsandapplications |