3 citations · 4 across the 6 of their papers we have counts for
6 papers
Quantitative Verification of Constrained Occupation Time for Stochastic Discrete-time Systems
Bai Xue, Peixin Wang, C. -H. Luke Ong
This paper addresses the quantitative verification of constrained occupation time in stochastic discrete-time systems, focusing on the probability of visiting a target set at least…
Structural Abstraction and Refinement for Probabilistic Programs
Guanyan Li, Juanen Li, Zhilei Han +3
In this paper, we present structural abstraction refinement, a novel framework for verifying the threshold problem of probabilistic programs. Our approach represents the structure…
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…
Taming Reachability Analysis of DNN-Controlled Systems via Abstraction-Based Training
Jiaxu Tian, Dapeng Zhi, Si Liu +3
The intrinsic complexity of deep neural networks (DNNs) makes it challenging to verify not only the networks themselves but also the hosting DNN-controlled systems. Reachability an…
Cost Analysis of Nondeterministic Probabilistic Programs
Peixin Wang, Hongfei Fu, Amir Kafshdar Goharshady +3
We consider the problem of expected cost analysis over nondeterministic probabilistic programs, which aims at automated methods for analyzing the resource-usage of such programs. P…
Proving Expected Sensitivity of Probabilistic Programs with Randomized Variable-Dependent Termination Time
Peixin Wang, Hongfei Fu, Krishnendu Chatterjee +2
The notion of program sensitivity (aka Lipschitz continuity) specifies that changes in the program input result in proportional changes to the program output. For probabilistic pro…