6 citations · 11 across the 7 of their papers we have counts for
7 papers
An Automata-Theoretic Approach to Synthesizing Binarized Neural Networks
Ye Tao, Wanwei Liu, Fu Song +3
Deep neural networks, (DNNs, a.k.a. NNs), have been widely used in various tasks and have been proven to be successful. However, the accompanied expensive computing and storage cos…
Verifying Safety of Neural Networks from Topological Perspectives
Zhen Liang, Dejin Ren, Bai Xue +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…
Repairing Deep Neural Networks Based on Behavior Imitation
Zhen Liang, Taoran Wu, Changyuan Zhao +4
The increasing use of deep neural networks (DNNs) in safety-critical systems has raised concerns about their potential for exhibiting ill-behaviors. While DNN verification and test…
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…
Combining Symbolic Execution and Model Checking to Verify MPI Programs
Hengbiao Yu, Zhenbang Chen, Xianjin Fu +5
Message passing is the standard paradigm of programming in high-performance computing. However, verifying Message Passing Interface (MPI) programs is challenging, due to the comple…
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…