Exploring Singularities in point clouds with the graph Laplacian: An explicit approach
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2022
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| _version_ | 1866917286924779520 |
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| author | Andersson, Martin Avelin, Benny |
| author_facet | Andersson, Martin Avelin, Benny |
| contents | We develop theory and methods that use the graph Laplacian to analyze the geometry of the underlying manifold of datasets. Our theory provides theoretical guarantees and explicit bounds on the functional forms of the graph Laplacian when it acts on functions defined close to singularities of the underlying manifold. We use these explicit bounds to develop tests for singularities and propose methods that can be used to estimate geometric properties of singularities in the datasets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2301_00201 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Exploring Singularities in point clouds with the graph Laplacian: An explicit approach Andersson, Martin Avelin, Benny Machine Learning Differential Geometry 58K99 (Primary), 68R99, 60B99, 62G10 (Secondary) We develop theory and methods that use the graph Laplacian to analyze the geometry of the underlying manifold of datasets. Our theory provides theoretical guarantees and explicit bounds on the functional forms of the graph Laplacian when it acts on functions defined close to singularities of the underlying manifold. We use these explicit bounds to develop tests for singularities and propose methods that can be used to estimate geometric properties of singularities in the datasets. |
| title | Exploring Singularities in point clouds with the graph Laplacian: An explicit approach |
| topic | Machine Learning Differential Geometry 58K99 (Primary), 68R99, 60B99, 62G10 (Secondary) |
| url | https://arxiv.org/abs/2301.00201 |