# A Channel-based Exact Inference Algorithm for Bayesian Networks

arXiv: https://arxiv.org/abs/1804.08032 · HTML: https://mlsanity.com/paper/1804.08032/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Apr 2018.

## Built on by (most cited first, 1 of 1)

- [BayesL: a Logical Framework for the Verification of Bayesian Networks](https://mlsanity.com/paper/2506.23773/) (2025)

## Abstract (arXiv)

This paper describes a new algorithm for exact Bayesian inference that is based on a recently proposed compositional semantics of Bayesian networks in terms of channels. The paper concentrates on the ideas behind this algorithm, involving a linearisation (`stretching') of the Bayesian network, followed by a combination of forward state transformation and backward predicate transformation, while evidence is accumulated along the way. The performance of a prototype implementation of the algorithm in Python is briefly compared to a standard implementation (pgmpy): first results show competitive performance.