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cs.PL2025
Quantitative Verification of Omega-regular Properties in Probabilistic Programming
Peixin Wang, Jianhao Bai, Min Zhang +1
Probabilistic programming provides a high-level framework for specifying statistical models as executable programs with built-in randomness and conditioning. Existing inference tec…
cs.PL2023★ 1 cited
Static Posterior Inference of Bayesian Probabilistic Programming via Polynomial Solving
Peixin Wang, Tengshun Yang, Hongfei Fu +2
In Bayesian probabilistic programming, a central problem is to estimate the normalised posterior distribution (NPD) of a probabilistic program with conditioning via score (a.k.a. o…