91 citations · 96 across the 10 of their papers we have counts for
10 papers
Reachability-Based Formal Verification of Graph Neural Networks with Node and Edge Features
Anne M. Tumlin, Ben Wooding, Zhenxuan Shao +3
Graph neural networks (GNNs) have become a prominent approach for developing fast, topology-aware surrogates in electric power systems, supporting tasks such as power flow (PF) ana…
Towards Verified and Targeted Explanations through Formal Methods
Hanchen David Wang, Diego Manzanas Lopez, Preston K. Robinette +3
As deep neural networks are deployed in safety-critical domains such as autonomous driving and medical diagnosis, stakeholders need explanations that are interpretable but also tru…
Probabilistic Robustness Analysis in High Dimensional Space: Application to Semantic Segmentation Network
Navid Hashemi, Samuel Sasaki, Diego Manzanas Lopez +4
Semantic segmentation networks (SSNs) are central to safety-critical applications such as medical imaging and autonomous driving, where robustness under uncertainty is essential. H…
Online Reachability Analysis and Space Convexification for Autonomous Racing
Sergiy Bogomolov, Taylor T. Johnson, Diego Manzanas Lopez +2
This paper presents an optimisation-based approach for an obstacle avoidance problem within an autonomous vehicle racing context. Our control regime leverages online reachability a…
Robustness Verification of Deep Neural Networks using Star-Based Reachability Analysis with Variable-Length Time Series Input
Neelanjana Pal, Diego Manzanas Lopez, Taylor T Johnson
Data-driven, neural network (NN) based anomaly detection and predictive maintenance are emerging research areas. NN-based analytics of time-series data offer valuable insights into…
Reachability Analysis of a General Class of Neural Ordinary Differential Equations
Diego Manzanas Lopez, Patrick Musau, Nathaniel Hamilton +1
Continuous deep learning models, referred to as Neural Ordinary Differential Equations (Neural ODEs), have received considerable attention over the last several years. Despite thei…
An Empirical Analysis of the Use of Real-Time Reachability for the Safety Assurance of Autonomous Vehicles
Patrick Musau, Nathaniel Hamilton, Diego Manzanas Lopez +2
Recent advances in machine learning technologies and sensing have paved the way for the belief that safe, accessible, and convenient autonomous vehicles may be realized in the near…
NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems
Hoang-Dung Tran, Xiaodong Yang, Diego Manzanas Lopez +5
This paper presents the Neural Network Verification (NNV) software tool, a set-based verification framework for deep neural networks (DNNs) and learning-enabled cyber-physical syst…
Verification for Machine Learning, Autonomy, and Neural Networks Survey
Weiming Xiang, Patrick Musau, Ayana A. Wild +5
This survey presents an overview of verification techniques for autonomous systems, with a focus on safety-critical autonomous cyber-physical systems (CPS) and subcomponents thereo…
Reachable Set Estimation and Verification for Neural Network Models of Nonlinear Dynamic Systems
Weiming Xiang, Diego Manzanas Lopez, Patrick Musau +1
Neural networks have been widely used to solve complex real-world problems. Due to the complicate, nonlinear, non-convex nature of neural networks, formal safety guarantees for the…