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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Exact verification of relu neural control barrier functions
Abstract Control Barrier Functions (CBFs) are a popular approach for safe control of
nonlinear systems. In CBF-based control, the desired safety properties of the system are …
nonlinear systems. In CBF-based control, the desired safety properties of the system are …
Efficient neural network analysis with sum-of-infeasibilities
Inspired by sum-of-infeasibilities methods in convex optimization, we propose a novel
procedure for analyzing verification queries on neural networks with piecewise-linear …
procedure for analyzing verification queries on neural networks with piecewise-linear …
Tight neural network verification via semidefinite relaxations and linear reformulations
We present a novel semidefinite programming (SDP) relaxation that enables tight and
efficient verification of neural networks. The tightness is achieved by combining SDP …
efficient verification of neural networks. The tightness is achieved by combining SDP …
Neuro-symbolic verification of deep neural networks
Formal verification has emerged as a powerful approach to ensure the safety and reliability
of deep neural networks. However, current verification tools are limited to only a handful of …
of deep neural networks. However, current verification tools are limited to only a handful of …
Incremental verification of neural networks
Complete verification of deep neural networks (DNNs) can exactly determine whether the
DNN satisfies a desired trustworthy property (eg, robustness, fairness) on an infinite set of …
DNN satisfies a desired trustworthy property (eg, robustness, fairness) on an infinite set of …