# Markov Conditions and Factorization in Logical Credal Networks

arXiv: https://arxiv.org/abs/2302.14146 · HTML: https://mlsanity.com/paper/2302.14146/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 29 references that are in the map.
- First posted on arXiv 27 Feb 2023.

## Builds on (most cited first, 5 of 5)

- [Foundations of Structural Causal Models with Cycles and Latent Variables](https://mlsanity.com/paper/1611.06221/) (2016)
- [Directed Cyclic Graphical Representations of Feedback Models](https://mlsanity.com/paper/1302.4982/) (2013)
- [Join-Graph Propagation Algorithms](https://mlsanity.com/paper/1401.3489/) (2014)
- [Logical Credal Networks](https://mlsanity.com/paper/2109.12240/) (2021)
- [On the Foundations of Cycles in Bayesian Networks](https://mlsanity.com/paper/2301.08608/) (2023)

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

- [Logic, Optimization, and Artificial Intelligence](https://mlsanity.com/paper/2607.15532/) (2026)

## Abstract (arXiv)

We examine the recently proposed language of Logical Credal Networks, in particular investigating the consequences of various Markov conditions. We introduce the notion of structure for a Logical Credal Network and show that a structure without directed cycles leads to a well-known factorization result. For networks with directed cycles, we analyze the differences between Markov conditions, factorization results, and specification requirements.