Probabilistic morphisms and Bayesian supervised learning
Fuente:
arXiv
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866911040398163968 |
|---|---|
| author | Lê, Hông Vân |
| author_facet | Lê, Hông Vân |
| contents | In this paper, we develop category theory of Markov kernels to study categorical aspects of Bayesian inversions. As a result, we present a unified model for Bayesian supervised learning, encompassing Bayesian density estimation. We illustrate this model with Gaussian process regressions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_15408 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Probabilistic morphisms and Bayesian supervised learning Lê, Hông Vân Statistics Theory Category Theory 62C10, 62G05, 62G08, 18B40 In this paper, we develop category theory of Markov kernels to study categorical aspects of Bayesian inversions. As a result, we present a unified model for Bayesian supervised learning, encompassing Bayesian density estimation. We illustrate this model with Gaussian process regressions. |
| title | Probabilistic morphisms and Bayesian supervised learning |
| topic | Statistics Theory Category Theory 62C10, 62G05, 62G08, 18B40 |
| url | https://arxiv.org/abs/2502.15408 |