158 citations · 212 across the 8 of their papers we have counts for
5 papers · 1 filter
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen +2
Verifying robustness of neural network classifiers has attracted great interests and attention due to the success of deep neural networks and their unexpected vulnerability to adve…
Efficient Neural Network Robustness Certification with General Activation Functions
Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen +2
Finding minimum distortion of adversarial examples and thus certifying robustness in neural network classifiers for given data points is known to be a challenging problem. Neverthe…
On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen +3
CLEVER (Cross-Lipschitz Extreme Value for nEtwork Robustness) is an Extreme Value Theory (EVT) based robustness score for large-scale deep neural networks (DNNs). In this paper, we…
Towards Fast Computation of Certified Robustness for ReLU Networks
Tsui-Wei Weng, Huan Zhang, Hongge Chen +5
Verifying the robustness property of a general Rectified Linear Unit (ReLU) network is an NP-complete problem [Katz, Barrett, Dill, Julian and Kochenderfer CAV17]. Although finding…
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen +5
The robustness of neural networks to adversarial examples has received great attention due to security implications. Despite various attack approaches to crafting visually impercep…