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 …
Sok: Certified robustness for deep neural networks
Great advances in deep neural networks (DNNs) have led to state-of-the-art performance on
a wide range of tasks. However, recent studies have shown that DNNs are vulnerable to …
a wide range of tasks. However, recent studies have shown that DNNs are vulnerable to …
Generative ai and process systems engineering: The next frontier
This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …
such as large language models (LLMs), can enhance solution methodologies within process …
Certified training: Small boxes are all you need
To obtain, deterministic guarantees of adversarial robustness, specialized training methods
are used. We propose, SABR, a novel such certified training method, based on the key …
are used. We propose, SABR, a novel such certified training method, based on the key …
Efficiently computing local lipschitz constants of neural networks via bound propagation
Lipschitz constants are connected to many properties of neural networks, such as
robustness, fairness, and generalization. Existing methods for computing Lipschitz constants …
robustness, fairness, and generalization. Existing methods for computing Lipschitz constants …
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 …
Connecting certified and adversarial training
Training certifiably robust neural networks remains a notoriously hard problem. While
adversarial training optimizes under-approximations of the worst-case loss, which leads to …
adversarial training optimizes under-approximations of the worst-case loss, which leads to …
The fourth international verification of neural networks competition (VNN-COMP 2023): Summary and results
This report summarizes the 4th International Verification of Neural Networks Competition
(VNN-COMP 2023), held as a part of the 6th Workshop on Formal Methods for ML-Enabled …
(VNN-COMP 2023), held as a part of the 6th Workshop on Formal Methods for ML-Enabled …
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 …
Marabou 2.0: A versatile formal analyzer of neural networks
arXiv:2401.14461v1 [cs.AI] 25 Jan 2024 Page 1 Marabou 2.0: A Versatile Formal Analyzer of
Neural Networks Haoze Wu1, Omri Isac2, Aleksandar Zeljic1, Teruhiro Tagomori1,3, Matthew …
Neural Networks Haoze Wu1, Omri Isac2, Aleksandar Zeljic1, Teruhiro Tagomori1,3, Matthew …