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ORCIDPreston Robinette
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2020 – today
- 2024
[c9]Preston K. Robinette, Daniel Moyer, Taylor T. Johnson:
Sanitizing Hidden Information with Diffusion Models. ECAI 2024: 778-785- [c8]Anne M. Tumlin, Diego Manzanas Lopez, Preston Robinette, Yuying Zhao, Tyler Derr, Taylor T. Johnson:
FairNNV: The Neural Network Verification Tool For Certifying Fairness. ICAIF 2024: 36-44 - [c7]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: 127-137 - [i6]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 abs/2404.05703 (2024) - [i5]Preston K. Robinette, Dung T. Nguyen, Samuel Sasaki, Taylor T. Johnson:
Trigger-Based Fragile Model Watermarking for Image Transformation Networks. CoRR abs/2409.19442 (2024) - 2023
- [c6]Preston K. Robinette, Hanchen D. Wang, Nishan Shehadeh, Daniel Moyer, Taylor T. Johnson:
SUDS: Sanitizing Universal and Dependent Steganography. ECAI 2023: 1978-1985 - [c5]Preston K. Robinette, Nathaniel P. Hamilton, Taylor T. Johnson:
Self-Preserving Genetic Algorithms for Safe Learning in Discrete Action Spaces. ICCPS 2023: 110-119 - [c4]Preston K. Robinette, Nathaniel P. Hamilton, Taylor T. Johnson:
DEMO: Self-Preserving Genetic Algorithms vs. Safe Reinforcement Learning in Discrete Action Spaces. ICCPS 2023: 278-279 - [c3]Preston K. Robinette, Diego Manzanas Lopez, Taylor T. Johnson:
Benchmark: Neural Network Malware Classification. AISoLA 2023: 291-298 - [i4]Preston K. Robinette, Hanchen D. Wang, Nishan Shehadeh, Daniel Moyer, Taylor T. Johnson:
SUDS: Sanitizing Universal and Dependent Steganography. CoRR abs/2309.13467 (2023) - [i3]Preston K. Robinette, Daniel Moyer, Taylor T. Johnson:
Monsters in the Dark: Sanitizing Hidden Threats with Diffusion Models. CoRR abs/2310.06951 (2023) - 2022
- [c2]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: 1-10 - [c1]Nathaniel Hamilton, Preston Robinette, Taylor T. Johnson:
Training Agents to Satisfy Timed and Untimed Signal Temporal Logic Specifications with Reinforcement Learning. SEFM 2022: 190-206 - [i2]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 abs/2205.01419 (2022) - 2020
- [i1]Theodore Papamarkou, Hayley Guy, Bryce Kroencke, Jordan Miller, Preston Robinette, Daniel Schultz, Jacob D. Hinkle, Laura Pullum, Catherine D. Schuman, Jeremy Renshaw, Stylianos Chatzidakis:
Automated detection of pitting and stress corrosion cracks in used nuclear fuel dry storage canisters using residual neural networks. CoRR abs/2003.03241 (2020)
Coauthor Index
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