Taylor T. Johnson

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 139

Top Venues

Publications

Tianshu Bao, Hengrong Du, Weiming Xiang, Taylor T. Johnson
A New Hybrid Automaton Framework with Partial Differential Equation Dynamics. CoRR (2024)
Ziyan An, Taylor T. Johnson, Meiyi Ma
Formal Logic Enabled Personalized Federated Learning through Property Inference. AAAI (2024)
Preston K. Robinette, Diego Manzanas Lopez, Serena Serbinowska, Kevin Leach, Taylor T. Johnson
Case Study: Neural Network Malware Detection Verification for Feature and Image Datasets. CoRR (2024)
Ziyan An, Taylor T. Johnson, Meiyi Ma
Formal Logic Enabled Personalized Federated Learning Through Property Inference. CoRR (2024)
Preston K. Robinette, Diego Manzanas Lopez, Serena Serbinowska, Kevin Leach, Taylor T. Johnson
Case Study: Neural Network Malware Detection Verification for Feature and Image Datasets. FormaliSE@ICSE (2024)
Joel A. Rosenfeld, Benjamin P. Russo, Rushikesh Kamalapurkar, Taylor T. Johnson
The Occupation Kernel Method for Nonlinear System Identification. SIAM J. Control. Optim. 62 (3) (2024)
Christopher Brix, Mark Niklas Müller, Stanley Bak, Taylor T. Johnson, Changliu Liu
First Three Years of the International Verification of Neural Networks Competition (VNN-COMP). CoRR (2023)
Preston K. Robinette, Hanchen D. Wang, Nishan Shehadeh, Daniel Moyer, Taylor T. Johnson
SUDS: Sanitizing Universal and Dependent Steganography. ECAI (2023)
Neelanjana Pal, Diego Manzanas Lopez, Taylor T. Johnson
Robustness Verification of Deep Neural Networks Using Star-Based Reachability Analysis with Variable-Length Time Series Input. FMICS (2023)
Luan Viet Nguyen, Hoang-Dung Tran, Taylor T. Johnson, Vijay Gupta
Decentralized Safe Control for Distributed Cyber-Physical Systems Using Real-Time Reachability Analysis. IEEE Trans. Control. Netw. Syst. 10 (3) (2023)
Xia Wang, Anda Liang, Jonathan Sprinkle, Taylor T. Johnson
Robustness Verification for Knowledge-Based Logic of Risky Driving Scenes. CoRR (2023)
Preston K. Robinette, Diego Manzanas Lopez, Taylor T. Johnson
Benchmark: Neural Network Malware Classification. AISoLA (2023)
Preston K. Robinette, Hanchen D. Wang, Nishan Shehadeh, Daniel Moyer, Taylor T. Johnson
SUDS: Sanitizing Universal and Dependent Steganography. CoRR (2023)
Hoang-Dung Tran, Diego Manzanas Lopez, Taylor T. Johnson
Tutorial: Neural Network and Autonomous Cyber-Physical Systems Formal Verification for Trustworthy AI and Safe Autonomy. EMSOFT (2023)
Preston K. Robinette, Daniel Moyer, Taylor T. Johnson
Monsters in the Dark: Sanitizing Hidden Threats with Diffusion Models. CoRR (2023)
Taylor T. Johnson
ARCH-COMP23 Repeatability Evaluation Report. ARCH (2023)
Diego Manzanas Lopez, Sung Woo Choi, Hoang-Dung Tran, Taylor T. Johnson
NNV 2.0: The Neural Network Verification Tool. CAV (2) (2023)
Preston K. Robinette, Nathaniel P. Hamilton, Taylor T. Johnson
Self-Preserving Genetic Algorithms for Safe Learning in Discrete Action Spaces. ICCPS (2023)
Neelanjana Pal, Seojin Lee, Taylor T. Johnson
Benchmark: Formal Verification of Semantic Segmentation Neural Networks. AISoLA (2023)
Neelanjana Pal, Taylor T. Johnson
Formal Verification of Long Short-Term Memory based Audio Classifiers: A Star based Approach. CoRR (2023)
Preston K. Robinette, Nathaniel P. Hamilton, Taylor T. Johnson
DEMO: Self-Preserving Genetic Algorithms vs. Safe Reinforcement Learning in Discrete Action Spaces. ICCPS (2023)
Daniel Neider, Taylor T. Johnson
Track C1: Safety Verification of Deep Neural Networks (DNNs). AISoLA (2023)
Ziyan An, Xia Wang, Taylor T. Johnson, Jonathan Sprinkle, Meiyi Ma
Runtime Monitoring of Accidents in Driving Recordings with Multi-type Logic in Empirical Models. RV (2023)
Neelanjana Pal, Diego Manzanas Lopez, Taylor T. Johnson
Robustness Verification of Deep Neural Networks using Star-Based Reachability Analysis with Variable-Length Time Series Input. CoRR (2023)
Christopher Brix, Mark Niklas Müller, Stanley Bak, Taylor T. Johnson, Changliu Liu
First three years of the international verification of neural networks competition (VNN-COMP). Int. J. Softw. Tools Technol. Transf. 25 (3) (2023)
Diego Manzanas Lopez, Matthias Althoff, Marcelo Forets, Taylor T. Johnson, Tobias Ladner, Christian Schilling
ARCH-COMP23 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. ARCH (2023)
Diego Manzanas Lopez, Taylor T. Johnson
Empirical Analysis of Benchmark Generation for the Verification of Neural Network Image Classifiers. AISoLA (2023)
Christopher Brix, Stanley Bak, Changliu Liu, Taylor T. Johnson
The Fourth International Verification of Neural Networks Competition (VNN-COMP 2023): Summary and Results. CoRR (2023)
Sergiy Bogomolov, Taylor T. Johnson, Diego Manzanas Lopez, Patrick Musau, Paulius Stankaitis
Online Reachability Analysis and Space Convexification for Autonomous Racing. CoRR (2023)
Diego Manzanas Lopez, Matthias Althoff, Luis Benet, Xin Chen, Jiameng Fan, Marcelo Forets, Chao Huang, Taylor T. Johnson, Tobias Ladner, Wenchao Li, Christian Schilling, Qi Zhu
ARCH-COMP22 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. ARCH@SAFECOMP (2022)
Xiaodong Yang, Omar Ali Beg, Matthew Kenigsberg, Taylor T. Johnson
A Framework for Identification and Validation of Affine Hybrid Automata from Input-Output Traces. ACM Trans. Cyber Phys. Syst. 6 (2) (2022)
Patrick Musau, Nathaniel Hamilton, Diego Manzanas Lopez, Preston Robinette, Taylor T. Johnson
An Empirical Analysis of the Use of Real-Time Reachability for the Safety Assurance of Autonomous Vehicles. CoRR (2022)
Hoang-Dung Tran, Weiming Xiang, Taylor T. Johnson
Verification Approaches for Learning-Enabled Autonomous Cyber-Physical Systems. IEEE Des. Test 39 (1) (2022)
Nathaniel Hamilton, Patrick Musau, Diego Manzanas Lopez, Taylor T. Johnson
Zero-Shot Policy Transfer in Autonomous Racing: Reinforcement Learning vs Imitation Learning. ICAA (2022)
Patrick Musau, Nathaniel Hamilton, Diego Manzanas Lopez, Preston Robinette, Taylor T. Johnson
On Using Real-Time Reachability for the Safety Assurance of Machine Learning Controllers. ICAA (2022)
Bernard Serbinowski, Taylor T. Johnson
BehaVerify: Verifying Temporal Logic Specifications for Behavior Trees. CoRR (2022)
Nathaniel Hamilton, Preston Robinette, Taylor T. Johnson
Training Agents to Satisfy Timed and Untimed Signal Temporal Logic Specifications with Reinforcement Learning. SEFM (2022)
Mark Niklas Müller, Christopher Brix, Stanley Bak, Changliu Liu, Taylor T. Johnson
The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results. CoRR (2022)
Taylor T. Johnson
ARCH-COMP22 Repeatability Evaluation Report. ARCH@SAFECOMP (2022)
Bernard Serbinowski, Taylor T. Johnson
BehaVerify: Verifying Temporal Logic Specifications for Behavior Trees. SEFM (2022)
Diego Manzanas Lopez, Patrick Musau, Nathaniel Hamilton, Taylor T. Johnson
Reachability Analysis of a General Class of Neural Ordinary Differential Equations. FORMATS (2022)
Diego Manzanas Lopez, Patrick Musau, Nathaniel Hamilton, Taylor T. Johnson
Reachability Analysis of a General Class of Neural Ordinary Differential Equations. CoRR (2022)
Nathaniel Hamilton, Kyle Dunlap, Taylor T. Johnson, Kerianne L. Hobbs
Ablation Study of How Run Time Assurance Impacts the Training and Performance of Reinforcement Learning Agents. CoRR (2022)
Hoang-Dung Tran, Luan Viet Nguyen, Patrick Musau, Weiming Xiang, Taylor T. Johnson
Real-Time Verification for Distributed Cyber-Physical Systems. Leibniz Trans. Embed. Syst. 8 (2) (2022)
Joel A. Rosenfeld, Rushikesh Kamalapurkar, L. Forest Gruss, Taylor T. Johnson
Dynamic Mode Decomposition for Continuous Time Systems with the Liouville Operator. J. Nonlinear Sci. 32 (1) (2022)
Tianshu Bao, Shengyu Chen, Taylor T. Johnson, Peyman Givi, Shervin Sammak, Xiaowei Jia
Physics guided neural networks for spatio-temporal super-resolution of turbulent flows. UAI (2022)
Xiaodong Yang, Tom Yamaguchi, Hoang-Dung Tran, Bardh Hoxha, Taylor T. Johnson, Danil V. Prokhorov
Neural Network Repair with Reachability Analysis. FORMATS (2022)
Omar Ali Beg, Luan Viet Nguyen, Taylor T. Johnson, Ali Davoudi
Cyber-Physical Anomaly Detection in Microgrids Using Time-Frequency Logic Formalism. IEEE Access 9 (2021)
Xiaodong Yang, Tom Yamaguchi, Hoang-Dung Tran, Bardh Hoxha, Taylor T. Johnson, Danil V. Prokhorov
Neural Network Repair with Reachability Analysis. CoRR (2021)
Neelanjana Pal, Taylor T. Johnson
Work In Progress: Safety and Robustness Verification of Autoencoder-Based Regression Models using the NNV Tool. SNR (2021)
Stanley Bak, Changliu Liu, Taylor T. Johnson
The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results. CoRR (2021)
Hoang-Dung Tran, Neelanjana Pal, Patrick Musau, Diego Manzanas Lopez, Nathaniel Hamilton, Xiaodong Yang, Stanley Bak, Taylor T. Johnson
Robustness Verification of Semantic Segmentation Neural Networks Using Relaxed Reachability. CAV (1) (2021)
Weiming Xiang, Hoang-Dung Tran, Xiaodong Yang, Taylor T. Johnson
Reachable Set Estimation for Neural Network Control Systems: A Simulation-Guided Approach. IEEE Trans. Neural Networks Learn. Syst. 32 (5) (2021)
Xiaodong Yang, Tomoya Yamaguchi, Hoang-Dung Tran, Bardh Hoxha, Taylor T. Johnson, Danil V. Prokhorov
Reachability Analysis of Convolutional Neural Networks. CoRR (2021)
Taylor T. Johnson, Diego Manzanas Lopez, Luis Benet, Marcelo Forets, Sebastián Guadalupe, Christian Schilling, Radoslav Ivanov, Taylor J. Carpenter, James Weimer, Insup Lee
ARCH-COMP21 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. ARCH@ADHS (2021)
Joel A. Rosenfeld, Rushikesh Kamalapurkar, L. Forest Gruss, Taylor T. Johnson
On Occupation Kernels, Liouville Operators, and Dynamic Mode Decomposition. ACC (2021)
Hoang-Dung Tran, Neelanjana Pal, Diego Manzanas Lopez, Patrick Musau, Xiaodong Yang, Luan Viet Nguyen, Weiming Xiang, Stanley Bak, Taylor T. Johnson
Verification of piecewise deep neural networks: a star set approach with zonotope pre-filter. Formal Aspects Comput. 33 (4-5) (2021)
Xiaodong Yang, Taylor T. Johnson, Hoang-Dung Tran, Tomoya Yamaguchi, Bardh Hoxha, Danil V. Prokhorov
Reachability analysis of deep ReLU neural networks using facet-vertex incidence. HSCC (2021)
Luan Viet Nguyen, Wesam Haddad, Taylor T. Johnson
Model Checking for Rectangular Hybrid Systems: A Quantified Encoding Approach. SNR (2021)
Tianshu Bao, Xiaowei Jia, Jacob Zwart, Jeffrey Sadler, Alison P. Appling, Samantha Oliver, Taylor T. Johnson
Partial Differential Equation Driven Dynamic Graph Networks for Predicting Stream Water Temperature. ICDM (2021)
Taylor T. Johnson
ARCH-COMP21 Repeatability Evaluation Report. ARCH@ADHS (2021)
Xiaodong Yang, Hoang-Dung Tran, Weiming Xiang, Taylor T. Johnson
Reachability Analysis for Feed-Forward Neural Networks using Face Lattices. CoRR (2020)
Shafiul Azam Chowdhury, Sohil Lal Shrestha, Taylor T. Johnson, Christoph Csallner
SLEMI: finding simulink compiler bugs through equivalence modulo input (EMI). ICSE (Companion Volume) (2020)
Hoang-Dung Tran, Stanley Bak, Weiming Xiang, Taylor T. Johnson
Verification of Deep Convolutional Neural Networks Using ImageStars. CAV (1) (2020)
Stanley Bak, Hoang-Dung Tran, Kerianne Hobbs, Taylor T. Johnson
Improved Geometric Path Enumeration for Verifying ReLU Neural Networks. CAV (1) (2020)
Weiming Xiang, Hoang-Dung Tran, Xiaodong Yang, Taylor T. Johnson
Reachable Set Estimation for Neural Network Control Systems: A Simulation-Guided Approach. CoRR (2020)
Hoang-Dung Tran, Xiaodong Yang, Diego Manzanas Lopez, Patrick Musau, Luan Viet Nguyen, Weiming Xiang, Stanley Bak, Taylor T. Johnson
NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems. CAV (1) (2020)
Diego Manzanas Lopez, Patrick Musau, Nathaniel Hamilton, Hoang-Dung Tran, Taylor T. Johnson
Case Study: Safety Verification of an Unmanned Underwater Vehicle. SP Workshops (2020)
Hoang-Dung Tran, Xiaodong Yang, Diego Manzanas Lopez, Patrick Musau, Luan Viet Nguyen, Weiming Xiang, Stanley Bak, Taylor T. Johnson
NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems. CoRR (2020)
Hoang-Dung Tran, Stanley Bak, Weiming Xiang, Taylor T. Johnson
Verification of Deep Convolutional Neural Networks Using ImageStars. CoRR (2020)
Taylor T. Johnson
ARCH-COMP20 Repeatability Evaluation Report. ARCH (2020)
Shafiul Azam Chowdhury, Sohil Lal Shrestha, Taylor T. Johnson, Christoph Csallner
SLEMI: equivalence modulo input (EMI) based mutation of CPS models for finding compiler bugs in Simulink. ICSE (2020)
Taylor T. Johnson, Diego Manzanas Lopez, Patrick Musau, Hoang-Dung Tran, Elena Botoeva, Francesco Leofante, Amir Maleki, Chelsea Sidrane, Jiameng Fan, Chao Huang
ARCH-COMP20 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. ARCH (2020)
Weiming Xiang, Hoang-Dung Tran, Taylor T. Johnson
Nonconservative Lifted Convex Conditions for Stability of Discrete-Time Switched Systems Under Minimum Dwell-Time Constraint. IEEE Trans. Autom. Control. 64 (8) (2019)
Hoang-Dung Tran, Luan Viet Nguyen, Nathaniel Hamilton, Weiming Xiang, Taylor T. Johnson
Reachability Analysis for High-Index Linear Differential Algebraic Equations. FORMATS (2019)
Diego Manzanas Lopez, Patrick Musau, Hoang-Dung Tran, Souradeep Dutta, Taylor J. Carpenter, Radoslav Ivanov, Taylor T. Johnson
ARCH-COMP19 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. ARCH@CPSIoTWeek (2019)
Tamás Kecskés, Patrik Meijer, Taylor T. Johnson, Marcus Lucas
Demo: a design studio for verification tools. DESTION@CPSIoTWeek (2019)
Stanley Bak, Hoang-Dung Tran, Taylor T. Johnson
Numerical verification of affine systems with up to a billion dimensions. HSCC (2019)
Charles Hartsell, Nagabhushan Mahadevan, Shreyas Ramakrishna, Abhishek Dubey, Theodore Bapty, Taylor T. Johnson, Xenofon D. Koutsoukos, Janos Sztipanovits, Gabor Karsai
CPS Design with Learning-Enabled Components: A Case Study. RSP (2019)
Taylor T. Johnson
ARCH-COMP19 Repeatability Evaluation Report. ARCH@CPSIoTWeek (2019)
Omar Ali Beg, Luan Viet Nguyen, Taylor T. Johnson, Ali Davoudi
Signal Temporal Logic-Based Attack Detection in DC Microgrids. IEEE Trans. Smart Grid 10 (4) (2019)
Hoang-Dung Tran, Luan Viet Nguyen, Patrick Musau, Weiming Xiang, Taylor T. Johnson
Decentralized Real-Time Safety Verification for Distributed Cyber-Physical Systems. FORTE (2019)
Hoang-Dung Tran, Luan Viet Nguyen, Patrick Musau, Weiming Xiang, Taylor T. Johnson
Real-Time Verification for Distributed Cyber-Physical Systems. CoRR (2019)
Hoang-Dung Tran, Diego Manzanas Lopez, Patrick Musau, Xiaodong Yang, Luan Viet Nguyen, Weiming Xiang, Taylor T. Johnson
Star-Based Reachability Analysis of Deep Neural Networks. FM (2019)
Charles Hartsell, Nagabhushan Mahadevan, Shreyas Ramakrishna, Abhishek Dubey, Theodore Bapty, Taylor T. Johnson, Xenofon D. Koutsoukos, Janos Sztipanovits, Gabor Karsai
Model-based design for CPS with learning-enabled components. DESTION@CPSIoTWeek (2019)
Hoang-Dung Tran, Feiyang Cai, Diego Manzanas Lopez, Patrick Musau, Taylor T. Johnson, Xenofon D. Koutsoukos
Safety Verification of Cyber-Physical Systems with Reinforcement Learning Control. ACM Trans. Embed. Comput. Syst. 18 (5s) (2019)
Hoang-Dung Tran, Patrick Musau, Diego Manzanas Lopez, Xiaodong Yang, Luan Viet Nguyen, Weiming Xiang, Taylor T. Johnson
Parallelizable reachability analysis algorithms for feed-forward neural networks. FormaliSE@ICSE (2019)
Joel A. Rosenfeld, Rushikesh Kamalapurkar, Benjamin Russo, Taylor T. Johnson
Occupation Kernels and Densely Defined Liouville Operators for System Identification. CDC (2019)
Stanley Bak, Omar Ali Beg, Sergiy Bogomolov, Taylor T. Johnson, Luan Viet Nguyen, Christian Schilling
Hybrid automata: from verification to implementation. Int. J. Softw. Tools Technol. Transf. 21 (1) (2019)
Diego Manzanas Lopez, Patrick Musau, Hoang-Dung Tran, Taylor T. Johnson
Verification of Closed-loop Systems with Neural Network Controllers. ARCH@CPSIoTWeek (2019)
Andrew Sogokon, Paul B. Jackson, Taylor T. Johnson
Verifying Safety and Persistence in Hybrid Systems Using Flowpipes and Continuous Invariants. J. Autom. Reason. 63 (4) (2019)
Stephen A. Rees, Tamás Kecskés, Patrik Meijer, Taylor T. Johnson, Katie Dey, Paulo Tabuada, Marcus Lucas
Cyber-physical systems virtual organization: Active resources: enabling reproducibility, improving accessibility, and lowering the barrier to entry. ICCPS (2019)
Weiming Xiang, Taylor T. Johnson
Reachability Analysis and Safety Verification for Neural Network Control Systems. CoRR (2018)
Weiming Xiang, Hoang-Dung Tran, Joel A. Rosenfeld, Taylor T. Johnson
Reachable Set Estimation and Safety Verification for Piecewise Linear Systems with Neural Network Controllers. ACC (2018)
Weiming Xiang, Hoang-Dung Tran, Joel A. Rosenfeld, Taylor T. Johnson
Reachable Set Estimation and Safety Verification for Piecewise Linear Systems with Neural Network Controllers. CoRR (2018)
Patrick Musau, Diego Manzanas Lopez, Hoang-Dung Tran, Taylor T. Johnson
Linear Differential-Algebraic Equations (Benchmark Proposal). ARCH@ADHS (2018)
Patrick Musau, Taylor T. Johnson
Verification of Continuous Time Recurrent Neural Networks (Benchmark Proposal). ARCH@ADHS (2018)
Weiming Xiang, Patrick Musau, Ayana A. Wild, Diego Manzanas Lopez, Nathaniel Hamilton, Xiaodong Yang, Joel A. Rosenfeld, Taylor T. Johnson
Verification for Machine Learning, Autonomy, and Neural Networks Survey. CoRR (2018)
Stanley Bak, Hoang-Dung Tran, Taylor T. Johnson
Numerical Verification of Affine Systems with up to a Billion Dimensions. CoRR (2018)
Weiming Xiang, Hoang-Dung Tran, Taylor T. Johnson
Specification-Guided Safety Verification for Feedforward Neural Networks. CoRR (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Taylor T. Johnson