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cs.PL2023
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…
cs.PL2022
ProbTA: A sound and complete proof rule for probabilistic verification
Guanyan Li, Zhilei Han, Fei He
We propose a sound and complete proof rule ProbTA for quantitative analysis of violation probability of probabilistic programs. Our approach extends the technique of trace abstract…