Compositionality in algorithms for smoothing
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| Acceso en línea: | |
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| _version_ | 1866918406764101632 |
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| author | Schauer, Moritz van der Meulen, Frank Wang, Andi Q. |
| author_facet | Schauer, Moritz van der Meulen, Frank Wang, Andi Q. |
| contents | Backward Filtering Forward Guiding (BFFG) is a bidirectional algorithm proposed in Mider et al. [2021] and studied more in depth in a general setting in Van der Meulen and Schauer [2022]. In category theory, optics have been proposed for modelling systems with bidirectional data flow. We connect BFFG with optics by demonstrating that the forward and backwards map together define a functor from a category of Markov kernels into a category of optics, which is furthermore lax monoidal in the case when the guiding kernels coincide with the generative dynamics |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_13865 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Compositionality in algorithms for smoothing Schauer, Moritz van der Meulen, Frank Wang, Andi Q. Category Theory Methodology Primary: 62M05, 18M35, Secondary: 18M05 Backward Filtering Forward Guiding (BFFG) is a bidirectional algorithm proposed in Mider et al. [2021] and studied more in depth in a general setting in Van der Meulen and Schauer [2022]. In category theory, optics have been proposed for modelling systems with bidirectional data flow. We connect BFFG with optics by demonstrating that the forward and backwards map together define a functor from a category of Markov kernels into a category of optics, which is furthermore lax monoidal in the case when the guiding kernels coincide with the generative dynamics |
| title | Compositionality in algorithms for smoothing |
| topic | Category Theory Methodology Primary: 62M05, 18M35, Secondary: 18M05 |
| url | https://arxiv.org/abs/2303.13865 |