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| 1. Verfasser: | |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2412.09469 |
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| _version_ | 1866909425514577920 |
|---|---|
| author | Cornish, Rob |
| author_facet | Cornish, Rob |
| contents | Cornish (2024) recently gave a general theory of neural network symmetrisation in the abstract context of Markov categories. We give a high-level overview of these results, and their concrete implications for the symmetrisation of deterministic functions and of Markov kernels. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_09469 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Neural Network Symmetrisation in Concrete Settings Cornish, Rob Machine Learning Cornish (2024) recently gave a general theory of neural network symmetrisation in the abstract context of Markov categories. We give a high-level overview of these results, and their concrete implications for the symmetrisation of deterministic functions and of Markov kernels. |
| title | Neural Network Symmetrisation in Concrete Settings |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2412.09469 |