28 citations · 44 across the 9 of their papers we have counts for
4 papers · 1 filter
Model-Agnostic Reachability Analysis on Deep Neural Networks
Chi Zhang, Wenjie Ruan, Fu Wang +3
Verification plays an essential role in the formal analysis of safety-critical systems. Most current verification methods have specific requirements when working on Deep Neural Net…
Towards Verifying the Geometric Robustness of Large-scale Neural Networks
Fu Wang, Peipei Xu, Wenjie Ruan +1
Deep neural networks (DNNs) are known to be vulnerable to adversarial geometric transformation. This paper aims to verify the robustness of large-scale DNNs against the combination…
How and what to learn:The modes of machine learning
Sihan Feng, Yong Zhang, Fuming Wang +1
Despite their great success, neural networks still remain as black-boxes due to the lack of interpretability. Here we propose a new analyzing method, namely the weight pathway anal…
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude
Fu Wang, Yanghao Zhang, Yanbin Zheng +1
Adversarial training is an effective but time-consuming way to train robust deep neural networks that can withstand strong adversarial attacks. As a response to its inefficiency, w…