Neural embedding: learning the embedding of the manifold of physics data
Abstract In this paper, we present a method of embedding physics data manifolds with metric structure into lower dimensional spaces with simpler metrics, such as Euclidean and Hyperbolic spaces. We then demonstrate that it can be a powerful step in the data analysis pipeline for many applications. U...
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| Autores principales: | , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
SpringerOpen
2023-07-01
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| Colección: | Journal of High Energy Physics |
| Materias: | |
| Acceso en línea: | https://doi.org/10.1007/JHEP07(2023)108 |
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