153 citations · 219 across the 5 of their papers we have counts for
5 papers · 1 filter
Towards Repairing Neural Networks Correctly
Guoliang Dong, Jun Sun, Jingyi Wang +2
Neural networks are increasingly applied to support decision making in safety-critical applications (like autonomous cars, unmanned aerial vehicles and face recognition based authe…
There is Limited Correlation between Coverage and Robustness for Deep Neural Networks
Yizhen Dong, Peixin Zhang, Jingyi Wang +7
Deep neural networks (DNN) are increasingly applied in safety-critical systems, e.g., for face recognition, autonomous car control and malware detection. It is also shown that DNNs…
Towards Interpreting Recurrent Neural Networks through Probabilistic Abstraction
Guoliang Dong, Jingyi Wang, Jun Sun +5
Neural networks are becoming a popular tool for solving many real-world problems such as object recognition and machine translation, thanks to its exceptional performance as an end…
Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing
Jingyi Wang, Guoliang Dong, Jun Sun +2
Deep neural networks (DNN) have been shown to be useful in a wide range of applications. However, they are also known to be vulnerable to adversarial samples. By transforming a nor…
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing
Jingyi Wang, Jun Sun, Peixin Zhang +1
Recently, it has been shown that deep neural networks (DNN) are subject to attacks through adversarial samples. Adversarial samples are often crafted through adversarial perturbati…