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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.17045 |
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| _version_ | 1866916299259510784 |
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| author | Glass, Cheyne Vidaurre, Elizabeth |
| author_facet | Glass, Cheyne Vidaurre, Elizabeth |
| contents | Topological Data Analysis has grown in popularity in recent years as a way to apply tools from algebraic topology to large data sets. One of the main tools in topological data analysis is persistent homology. This paper uses undergraduate linear algebra to provide explicit methods for, and examples of, computing persistent (co)homology. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_17045 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Topological Data Analysis via Undergraduate Linear Algebra Glass, Cheyne Vidaurre, Elizabeth Algebraic Topology Statistics Theory 62R40 Topological Data Analysis has grown in popularity in recent years as a way to apply tools from algebraic topology to large data sets. One of the main tools in topological data analysis is persistent homology. This paper uses undergraduate linear algebra to provide explicit methods for, and examples of, computing persistent (co)homology. |
| title | Topological Data Analysis via Undergraduate Linear Algebra |
| topic | Algebraic Topology Statistics Theory 62R40 |
| url | https://arxiv.org/abs/2406.17045 |