English

Lifting Factor Graphs with Some Unknown Factors

Artificial Intelligence 2024-06-04 v1 Machine Learning

Abstract

Lifting exploits symmetries in probabilistic graphical models by using a representative for indistinguishable objects, allowing to carry out query answering more efficiently while maintaining exact answers. In this paper, we investigate how lifting enables us to perform probabilistic inference for factor graphs containing factors whose potentials are unknown. We introduce the Lifting Factor Graphs with Some Unknown Factors (LIFAGU) algorithm to identify symmetric subgraphs in a factor graph containing unknown factors, thereby enabling the transfer of known potentials to unknown potentials to ensure a well-defined semantics and allow for (lifted) probabilistic inference.

Keywords

Cite

@article{arxiv.2406.01275,
  title  = {Lifting Factor Graphs with Some Unknown Factors},
  author = {Malte Luttermann and Ralf Möller and Marcel Gehrke},
  journal= {arXiv preprint arXiv:2406.01275},
  year   = {2024}
}

Comments

Accepted to the Proceedings of the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU-23)

R2 v1 2026-06-28T16:51:02.814Z