Algorithms for verifying deep neural networks
Deep neural networks are widely used for nonlinear function approximation, with
applications ranging from computer vision to control. Although these networks involve the …
applications ranging from computer vision to control. Although these networks involve the …
General cutting planes for bound-propagation-based neural network verification
Bound propagation methods, when combined with branch and bound, are among the most
effective methods to formally verify properties of deep neural networks such as correctness …
effective methods to formally verify properties of deep neural networks such as correctness …
First three years of the international verification of neural networks competition (VNN-COMP)
This paper presents a summary and meta-analysis of the first three iterations of the annual
International Verification of Neural Networks Competition (VNN-COMP), held in 2020, 2021 …
International Verification of Neural Networks Competition (VNN-COMP), held in 2020, 2021 …
The second international verification of neural networks competition (vnn-comp 2021): Summary and results
This report summarizes the second International Verification of Neural Networks
Competition (VNN-COMP 2021), held as a part of the 4th Workshop on Formal Methods for …
Competition (VNN-COMP 2021), held as a part of the 4th Workshop on Formal Methods for …
The third international verification of neural networks competition (VNN-COMP 2022): Summary and results
This report summarizes the 3rd International Verification of Neural Networks Competition
(VNN-COMP 2022), held as a part of the 5th Workshop on Formal Methods for ML-Enabled …
(VNN-COMP 2022), held as a part of the 5th Workshop on Formal Methods for ML-Enabled …
Marabou 2.0: a versatile formal analyzer of neural networks
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[PDF][PDF] DEEPSPLIT: An Efficient Splitting Method for Neural Network Verification via Indirect Effect Analysis.
P Henriksen, A Lomuscio - IJCAI, 2021 - ijcai.org
We propose a novel, complete algorithm for the verification and analysis of feed-forward,
ReLU-based neural networks. The algorithm, based on symbolic interval propagation …
ReLU-based neural networks. The algorithm, based on symbolic interval propagation …
Adversarial robustness of deep neural networks: A survey from a formal verification perspective
Neural networks have been widely applied in security applications such as spam and
phishing detection, intrusion prevention, and malware detection. This black-box method …
phishing detection, intrusion prevention, and malware detection. This black-box method …
Artificial neural network training criterion formulation using error continuous domain
Z Hu, M Ivashchenko, L Lyushenko… - … Journal of Modern …, 2021 - search.proquest.com
One of the trends in information technologies is implementing neural networks in modern
software packages [1]. The fact that neural networks cannot be directly programmed (but …
software packages [1]. The fact that neural networks cannot be directly programmed (but …
Improved branch and bound for neural network verification via lagrangian decomposition
We improve the scalability of Branch and Bound (BaB) algorithms for formally proving input-
output properties of neural networks. First, we propose novel bounding algorithms based on …
output properties of neural networks. First, we propose novel bounding algorithms based on …