# α Belief Propagation as Fully Factorized Approximation

arXiv: https://arxiv.org/abs/1908.08906 · HTML: https://mlsanity.com/paper/1908.08906/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Aug 2019.

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

- [Circular Belief Propagation for Approximate Probabilistic Inference](https://mlsanity.com/paper/2403.12106/) (2024)

## Abstract (arXiv)

Belief propagation (BP) can do exact inference in loop-free graphs, but its performance could be poor in graphs with loops, and the understanding of its solution is limited. This work gives an interpretable belief propagation rule that is actually minimization of a localized α-divergence. We term this algorithm as α belief propagation (α-BP). The performance of α-BP is tested in MAP (maximum a posterior) inference problems, where α-BP can outperform (loopy) BP by a significant margin even in fully-connected graphs.