Saved in:
Bibliographic Details
Main Authors: Schauer, Moritz, van der Meulen, Frank, Wang, Andi Q.
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2303.13865
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866918406764101632
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