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 …
NNV 2.0: the neural network verification tool
This manuscript presents the updated version of the Neural Network Verification (NNV) tool.
NNV is a formal verification software tool for deep learning models and cyber-physical …
NNV is a formal verification software tool for deep learning models and cyber-physical …
Polar: A polynomial arithmetic framework for verifying neural-network controlled systems
We present POLAR (The source code can be found at https://github. com/ChaoHuang2018/
POLAR_Tool. The full version of this paper can be found at https://arxiv …
POLAR_Tool. The full version of this paper can be found at https://arxiv …
ARCH-COMP23 category report: Artificial intelligence and neural network control systems (AINNCS) for continuous and hybrid systems plants
This report presents the results of a friendly competition for formal verification of continuous
and hybrid systems with artificial intelligence (AI) components. Specifically, machine …
and hybrid systems with artificial intelligence (AI) components. Specifically, machine …
Safety verification of decision-tree policies in continuous time
Decision trees have gained popularity as interpretable surrogate models for learning-based
control policies. However, providing safety guarantees for systems controlled by decision …
control policies. However, providing safety guarantees for systems controlled by decision …
Efficient interaction-aware interval analysis of neural network feedback loops
In this article, we propose a computationally efficient framework for interval reachability of
systems with neural network controllers. Our approach leverages inclusion functions for the …
systems with neural network controllers. Our approach leverages inclusion functions for the …
Polar-express: Efficient and precise formal reachability analysis of neural-network controlled systems
Neural networks (NNs) playing the role of controllers have demonstrated impressive
empirical performance on challenging control problems. However, the potential adoption of …
empirical performance on challenging control problems. However, the potential adoption of …
Provably Safe Neural Network Controllers via Differential Dynamic Logic
While neural networks (NNs) have a large potential as goal-oriented controllers for Cyber-
Physical Systems, verifying the safety of neural network based control systems (NNCSs) …
Physical Systems, verifying the safety of neural network based control systems (NNCSs) …
Tutorial: Neural Network and Autonomous Cyber-Physical Systems Formal Verification for Trustworthy AI and Safe Autonomy
This interactive tutorial describes state-of-the-art methods for formally verifying neural
networks and their usage within safety-critical cyber-physical systems (CPS). The inclusion …
networks and their usage within safety-critical cyber-physical systems (CPS). The inclusion …
Neural abstraction-based controller synthesis and deployment
Abstraction-based techniques are an attractive approach for synthesizing correct-by-
construction controllers to satisfy high-level temporal requirements. A main bottleneck for …
construction controllers to satisfy high-level temporal requirements. A main bottleneck for …