Partial Markov Categories
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866917283406807040 |
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| author | Di Lavore, Elena Román, Mario Sobociński, Paweł |
| author_facet | Di Lavore, Elena Román, Mario Sobociński, Paweł |
| contents | We introduce partial Markov categories as a synthetic framework for synthetic probabilistic inference, blending the work of Cho and Jacobs, Fritz, and Golubtsov on Markov categories with the work of Cockett and Lack on cartesian restriction categories. We describe observations, Bayes' theorem, normalisation, and both Pearl's and Jeffrey's updates in purely categorical terms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_03477 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Partial Markov Categories Di Lavore, Elena Román, Mario Sobociński, Paweł Category Theory Logic in Computer Science 18M30 We introduce partial Markov categories as a synthetic framework for synthetic probabilistic inference, blending the work of Cho and Jacobs, Fritz, and Golubtsov on Markov categories with the work of Cockett and Lack on cartesian restriction categories. We describe observations, Bayes' theorem, normalisation, and both Pearl's and Jeffrey's updates in purely categorical terms. |
| title | Partial Markov Categories |
| topic | Category Theory Logic in Computer Science 18M30 |
| url | https://arxiv.org/abs/2502.03477 |