Bayesian Networks and Proof-Nets: the proof-theory of Bayesian Inference
Abstract
We study the correspondence between Bayesian Networks and graphical representation of proofs in linear logic. The goal of this paper is threefold: to develop a proof-theoretical account of Bayesian inference (in the spirit of the Curry-Howard correspondence between proofs and programs), to provide compositional graphical methods, and to take into account computational efficiency. We exploit the fact that the decomposition of a graph is more flexible than that of a proof-tree, or of a type-derivation, even if compositionality becomes more challenging.
Fields of Study & Subjects
Bayesian Modeling and Causal Inference
Logic
programming
and type systems
Reasoning
and Knowledge
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 3 February 2026
- Document type
- Preprint