activity
20132026
most citedOn the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions

20 citations · 32 across the 11 of their papers we have counts for

collaborators

11 papers

cs.SE2026

LimICE: Integrating LLM into ICE Framework for Efficient Loop Invariant Inference

Kai Fan, ShiWen Yu, GuangSheng Fan +3

Loop invariant synthesis is a fundamental problem in program verification, yet the inherent undecidability makes it highly challenging. Recent studies have increasingly employed va…

cs.AI2022

Safety Verification for Neural Networks Based on Set-boundary Analysis

Zhen Liang, Dejin Ren, Wanwei Liu +3

Neural networks (NNs) are increasingly applied in safety-critical systems such as autonomous vehicles. However, they are fragile and are often ill-behaved. Consequently, their beha…

math.OC2022

Reach-avoid Verification Based on Convex Optimization

Bai Xue, Naijun Zhan, Martin Fränzle +2

In this paper we propose novel optimization-based methods for verifying reach-avoid (or, eventuality) properties of continuous-time systems modelled by ordinary differential equati…

cs.IT2021★ 20 cited

On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions

Yufeng Zhang, Wanwei Liu, Zhenbang Chen +2

Kullback-Leibler (KL) divergence is one of the most important divergence measures between probability distributions. In this paper, we prove several properties of KL divergence bet…

cs.AI2020

On Sufficient and Necessary Conditions in Bounded CTL: A Forgetting Approach

Renyan Feng, Erman Acar, Stefan Schlobach +2

Computation Tree Logic (CTL) is one of the central formalisms in formal verification. As a specification language, it is used to express a property that the system at hand is expec…

cs.LG2020

Kullback-Leibler Divergence-Based Out-of-Distribution Detection with Flow-Based Generative Models

Yufeng Zhang, Jialu Pan, Wanwei Liu +5

Recent research has revealed that deep generative models including flow-based models and Variational Autoencoders may assign higher likelihoods to out-of-distribution (OOD) data th…

cs.PL2017★ 6 cited

Scheduling Constraint Based Abstraction Refinement for Multi-Threaded Program Verification

Liangze Yin, Wei Dong, Wanwei Liu +1

Bounded model checking is among the most efficient techniques for the automatic verification of concurrent programs. However, encoding all possible interleavings often requires a h…

cs.LO2016

An Efficient Synthesis Algorithm for Parametric Markov Chains Against Linear Time Properties

Yong Li, Wanwei Liu, Andrea Turrini +2

In this paper, we propose an efficient algorithm for the parameter synthesis of PLTL formulas with respect to parametric Markov chains. The PLTL formula is translated to an almost…

cs.FL2016

A Short Note on Infinite Union/Intersection of Omega Regular Languages

Wanwei Liu

We in this paper show that omega regular languages are not closed under infinite union and intersection. As an attempt, we propose to add step variables and quantifiers to temporal…

cs.LO2015★ 6 cited

A Simple Probabilistic Extension of Modal Mu-calculus

Wanwei Liu, Lei Song, Ji Wang +1

Probabilistic systems are an important theme in AI domain. As the specification language, the logic PCTL is now the default logic for reasoning about probabilistic properties. In t…

cs.LO2013

Counterexample-Preserving Reduction for Symbolic Model Checking

Wanwei Liu, Rui Wang, Xianjin Fu +3

The cost of LTL model checking is highly sensitive to the length of the formula under verification. We observe that, under some specific conditions, the input LTL formula can be re…