# Probabilistic Programming **Entity class:** Probabilistic And Inverse-Problem Layer concept **Probabilistic Programming** is a concept in the probabilistic and inverse-problem of the counterterrorism predictive-graph ontology. Within a predictive graph, Probabilistic Programming helps separate recorded evidence from the hidden state inferred from that evidence. ## Counterterrorism predictive-graph role The page records capability and analytic function. Any claim of a named operational deployment remains subject to the [[wiki/Counterterrorism Predictive Graph Evidence Ladder|evidence ladder]]. The analytic state should distinguish ground truth, observed evidence, inferred state, and predicted state. ## Relationships - **domain router:** [[wiki/Bayesian Inference|Bayesian Inference]]. - **ontology neighbors:** [[wiki/Posterior Odds|Posterior Odds]] and [[wiki/Monte Carlo Method|Monte Carlo Method]]. - **synthesis:** [[wiki/Counterterrorism Predictive Graph|Counterterrorism Predictive Graph]] and [[wiki/Predictive Intelligence Loop|Predictive Intelligence Loop]]. ## Sources - [NIST/SEMATECH — e-Handbook of Statistical Methods (accessed September 23, 2026)](https://www.itl.nist.gov/div898/handbook/) - [Oden Institute — Tan Bui-Thanh research profile (accessed September 23, 2026)](https://oden.utexas.edu/people/directory/Tan-Bui/) **As of:** 2026-09-23