Data-driven, neural network (NN) based anomaly detection and predictive
...
This paper presents a summary and meta-analysis of the first three itera...
This report summarizes the 3rd International Verification of Neural Netw...
This work in progress paper introduces robustness verification for
autoe...
Satisfiability Modulo Theories (SMT) solvers have been successfully appl...
Continuous deep learning models, referred to as Neural Ordinary Differen...
Reinforcement Learning (RL) has become an increasingly important researc...
Recent advances in machine learning technologies and sensing have paved ...
Safety is a critical concern for the next generation of autonomy that is...
Deep convolutional neural networks have been widely employed as an effec...
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 ...
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...
Embedded systems use increasingly complex software and are evolving into...
Reachability analysis is a fundamental problem for safety verification a...
Affine systems reachability is the basis of many verification methods. W...
Neural networks have been widely used to solve complex real-world proble...
In this paper, we present the virtual prototyping of a solar array with ...
We study the problem of distributed traffic control in the partitioned p...