Neural network model compression techniques can address the computation ...
In this paper, a computationally efficient data-driven hybrid automaton ...
This paper aims to enhance the computational efficiency of safety
verifi...
In this paper, we propose a concept of approximate bisimulation relation...
In this paper, a robust optimization framework is developed to train sha...
The vulnerability of artificial intelligence (AI) and machine learning (...
This paper presents the Neural Network Verification (NNV) software tool,...
Convolutional Neural Networks (CNN) have redefined the state-of-the-art ...
Deep neural networks have been widely applied as an effective approach t...
Safety-critical distributed cyber-physical systems (CPSs) have been foun...
This paper presents a specification-guided safety verification method fo...
This survey presents an overview of verification techniques for autonomo...
Reachability analysis is a fundamental problem for safety verification a...
Neural networks have been widely used to solve complex real-world proble...