1 citations · 1 across the 5 of their papers we have counts for
5 papers
UR4NNV: Neural Network Verification, Under-approximation Reachability Works!
Zhen Liang, Taoran Wu, Ran Zhao +5
Recently, formal verification of deep neural networks (DNNs) has garnered considerable attention, and over-approximation based methods have become popular due to their effectivenes…
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…
Credit Assignment for Trained Neural Networks Based on Koopman Operator Theory
Zhen Liang, Changyuan Zhao, Wanwei Liu +3
Credit assignment problem of neural networks refers to evaluating the credit of each network component to the final outputs. For an untrained neural network, approaches to tackling…
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…