Linear Differential-Algebraic Equations (Benchmark Proposal). - Patrick Musau; Diego Manzanas Lopez; Hoang-Dung Tran; Taylor T. Johnson (ARCH@ADHS, 2018)

Reachable Set Estimation and Verification for Neural Network Models of Nonlinear Dynamic Systems. - Weiming Xiang 001; Diego Manzanas Lopez; Patrick Musau; Taylor T. Johnson (CoRR, 2018)

Verification for Machine Learning, Autonomy, and Neural Networks Survey. - Weiming Xiang 001; Patrick Musau; Ayana A. Wild; Diego Manzanas Lopez; Nathaniel Hamilton; Xiaodong Yang; Joel A. Rosenfeld; Taylor T. Johnson (CoRR, 2018)

ARCH-COMP19 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. - Diego Manzanas Lopez; Patrick Musau; Hoang-Dung Tran; Souradeep Dutta; Taylor J. Carpenter; Radoslav Ivanov; Taylor T. Johnson (ARCH@CPSIoTWeek, 2019)

Verification of Closed-loop Systems with Neural Network Controllers. - Diego Manzanas Lopez; Patrick Musau; Hoang-Dung Tran; Taylor T. Johnson (ARCH@CPSIoTWeek, 2019)

Star-Based Reachability Analysis of Deep Neural Networks. - Hoang-Dung Tran; Diego Manzanas Lopez; Patrick Musau; Xiaodong Yang; Luan Viet Nguyen; Weiming Xiang 001; Taylor T. Johnson (FM, 2019)

Parallelizable reachability analysis algorithms for feed-forward neural networks. - Hoang-Dung Tran; Patrick Musau; Diego Manzanas Lopez; Xiaodong Yang; Luan Viet Nguyen; Weiming Xiang 001; Taylor T. Johnson (FormaliSE@ICSE, 2019)

Safety Verification of Cyber-Physical Systems with Reinforcement Learning Control. - Hoang-Dung Tran; Feiyang Cai; Diego Manzanas Lopez; Patrick Musau; Taylor T. Johnson; Xenofon D. Koutsoukos (ACM Trans. Embed. Comput. Syst., 2019)

ARCH-COMP20 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. - Taylor T. Johnson; Diego Manzanas Lopez; Patrick Musau; Hoang-Dung Tran; Elena Botoeva; Francesco Leofante; Amir Maleki; Chelsea Sidrane; Jiameng Fan; Chao Huang 015 (ARCH, 2020)

NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems. - Hoang-Dung Tran; Xiaodong Yang; Diego Manzanas Lopez; Patrick Musau; Luan Viet Nguyen; Weiming Xiang 001; Stanley Bak; Taylor T. Johnson (CAV (1), 2020)

Case Study: Safety Verification of an Unmanned Underwater Vehicle. - Diego Manzanas Lopez; Patrick Musau; Nathaniel Hamilton; Hoang-Dung Tran; Taylor T. Johnson (SP (Workshops), 2020)

ARCH-COMP21 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. - Taylor T. Johnson; Diego Manzanas Lopez; Luis Benet; Marcelo Forets; Sebastián Guadalupe; Christian Schilling 001; Radoslav Ivanov; Taylor J. Carpenter; James Weimer; Insup Lee 001 (ARCH@ADHS, 2021)

Robustness Verification of Semantic Segmentation Neural Networks Using Relaxed Reachability. - Hoang-Dung Tran; Neelanjana Pal; Patrick Musau; Diego Manzanas Lopez; Nathaniel Hamilton; Xiaodong Yang; Stanley Bak; Taylor T. Johnson (CAV (1), 2021)

Verification of piecewise deep neural networks: a star set approach with zonotope pre-filter. - Hoang-Dung Tran; Neelanjana Pal; Diego Manzanas Lopez; Patrick Musau; Xiaodong Yang; Luan Viet Nguyen; Weiming Xiang 001; Stanley Bak; Taylor T. Johnson (Formal Aspects Comput., 2021)

ARCH-COMP22 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. - Diego Manzanas Lopez; Matthias Althoff; Luis Benet; Xin Chen 002; Jiameng Fan; Marcelo Forets; Chao Huang 015; Taylor T. Johnson; Tobias Ladner; Wenchao Li 001; Christian Schilling 001; Qi Zhu 002 (ARCH@SAFECOMP, 2022)

Reachability Analysis of a General Class of Neural Ordinary Differential Equations. - Diego Manzanas Lopez; Patrick Musau; Nathaniel Hamilton; Taylor T. Johnson (FORMATS, 2022)

Zero-Shot Policy Transfer in Autonomous Racing: Reinforcement Learning vs Imitation Learning. - Nathaniel Hamilton; Patrick Musau; Diego Manzanas Lopez; Taylor T. Johnson (ICAA, 2022)

On Using Real-Time Reachability for the Safety Assurance of Machine Learning Controllers. - Patrick Musau; Nathaniel Hamilton; Diego Manzanas Lopez; Preston Robinette; Taylor T. Johnson (ICAA, 2022)

An Empirical Analysis of the Use of Real-Time Reachability for the Safety Assurance of Autonomous Vehicles. - Patrick Musau; Nathaniel Hamilton; Diego Manzanas Lopez; Preston Robinette; Taylor T. Johnson (CoRR, 2022)

Zero-Shot Policy Transfer in Autonomous Racing:Reinforcement Learning vs Imitation Learning. - Nathaniel Hamilton; Patrick Musau; Diego Manzanas Lopez; Taylor T. Johnson (Zenodo, 2022)

On Using Real-Time Reachability for the Safety Assurance of Machine Learning Controllers. - Patrick Musau; Nathaniel Hamilton; Diego Manzanas Lopez; Preston Robinette; Taylor T. Johnson (Zenodo, 2022)

An Empirical Analysis of the Use of Real-Time Reachability for the Safety Assurance of Autonomous Vehicles. - Patrick Musau; Nathaniel Hamilton; Diego Manzanas Lopez; Preston Robinette; Taylor T. Johnson (Zenodo, 2022)

ARCH-COMP23 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. - Diego Manzanas Lopez; Matthias Althoff; Marcelo Forets; Taylor T. Johnson; Tobias Ladner; Christian Schilling 001 (ARCH, 2023)

NNV 2.0: The Neural Network Verification Tool. - Diego Manzanas Lopez; Sung Woo Choi; Hoang-Dung Tran; Taylor T. Johnson (CAV (2), 2023)

Tutorial: Neural Network and Autonomous Cyber-Physical Systems Formal Verification for Trustworthy AI and Safe Autonomy. - Hoang-Dung Tran; Diego Manzanas Lopez; Taylor T. Johnson (EMSOFT, 2023)

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 (FMICS, 2023)

Empirical Analysis of Benchmark Generation for the Verification of Neural Network Image Classifiers. - Diego Manzanas Lopez; Taylor T. Johnson (AISoLA, 2023)

Benchmark: Neural Network Malware Classification. - Preston K. Robinette; Diego Manzanas Lopez; Taylor T. Johnson (AISoLA, 2023)

Online Reachability Analysis and Space Convexification for Autonomous Racing. - Sergiy Bogomolov; Taylor T. Johnson; Diego Manzanas Lopez; Patrick Musau; Paulius Stankaitis (FMAS@iFM, 2023)

(Artifact) Case Study: Neural Network Malware Detection Verification for Feature and Image Datasets. - Preston Robinette; Diego Manzanas Lopez; Taylor T. Johnson (Zenodo, 2023)

Tutorial: Safe, Secure, and Trustworthy Artificial Intelligence (AI) via Formal Verification of Neural Networks and Autonomous Cyber-Physical Systems (CPS) with NNV. - Taylor T. Johnson; Diego Manzanas Lopez; Hoang-Dung Tran (DSN-S, 2024)

FairNNV: The Neural Network Verification Tool For Certifying Fairness. - Anne M. Tumlin; Diego Manzanas Lopez; Preston Robinette; Yuying Zhao; Tyler Derr; Taylor T. Johnson (ICAIF, 2024)

Case Study: Neural Network Malware Detection Verification for Feature and Image Datasets. - Preston K. Robinette; Diego Manzanas Lopez; Serena Serbinowska; Kevin Leach; Taylor T. Johnson (FormaliSE@ICSE, 2024)

Robustness Verification of Video Classification Neural Networks. - Samuel Sasaki; Diego Manzanas Lopez; Preston K. Robinette; Taylor T. Johnson (FormaliSE, 2025)

Real-Time Reachability for Neurosymbolic Reinforcement Learning-based Safe Autonomous Navigation. - Nicholas Potteiger; Diego Manzanas Lopez; Taylor T. Johnson; Xenofon D. Koutsoukos (NeuS, 2025)

Neurosymbolic Finite and Pushdown Automata: Improved Multimodal Reasoning versus Vision Language Models (VLMs). - Samuel Sasaki; Diego Manzanas Lopez; Taylor T. Johnson (NeuS, 2025)

Neuro-Symbolic Behavior Trees (NSBTs) and Their Verification. - Serena Serafina Serbinowska; Diego Manzanas Lopez; Dung Thuy Nguyen; Taylor T. Johnson (NeuS, 2025)