torchsom: The Reference PyTorch Library for Self-Organizing Maps
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866909841227776000 |
|---|---|
| author | Berthier, Louis Shokry, Ahmed Moreaud, Maxime Ramelet, Guillaume Moulines, Eric |
| author_facet | Berthier, Louis Shokry, Ahmed Moreaud, Maxime Ramelet, Guillaume Moulines, Eric |
| contents | This paper introduces torchsom, an open-source Python library that provides a reference implementation of the Self-Organizing Map (SOM) in PyTorch. This package offers three main features: (i) dimensionality reduction, (ii) clustering, and (iii) friendly data visualization. It relies on a PyTorch backend, enabling (i) fast and efficient training of SOMs through GPU acceleration, and (ii) easy and scalable integrations with PyTorch ecosystem. Moreover, torchsom follows the scikit-learn API for ease of use and extensibility. The library is released under the Apache 2.0 license with 90% test coverage, and its source code and documentation are available at https://github.com/michelin/TorchSOM. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_11147 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | torchsom: The Reference PyTorch Library for Self-Organizing Maps Berthier, Louis Shokry, Ahmed Moreaud, Maxime Ramelet, Guillaume Moulines, Eric Machine Learning 68T07, 68T05, 68-04 I.2.6; I.5.1; I.5.3 This paper introduces torchsom, an open-source Python library that provides a reference implementation of the Self-Organizing Map (SOM) in PyTorch. This package offers three main features: (i) dimensionality reduction, (ii) clustering, and (iii) friendly data visualization. It relies on a PyTorch backend, enabling (i) fast and efficient training of SOMs through GPU acceleration, and (ii) easy and scalable integrations with PyTorch ecosystem. Moreover, torchsom follows the scikit-learn API for ease of use and extensibility. The library is released under the Apache 2.0 license with 90% test coverage, and its source code and documentation are available at https://github.com/michelin/TorchSOM. |
| title | torchsom: The Reference PyTorch Library for Self-Organizing Maps |
| topic | Machine Learning 68T07, 68T05, 68-04 I.2.6; I.5.1; I.5.3 |
| url | https://arxiv.org/abs/2510.11147 |