Zobrazeno 1 - 10 of 20 pro vyhledávání: '"Diego Manzanas Lopez"'
1
Evaluation of Neural Network Verification Methods for Air-to-Air Collision Avoidance
Autor: Diego Manzanas Lopez, Taylor T. Johnson, Stanley Bak, Hoang-Dung Tran, Kerianne L. Hobbs
Publikováno v: Journal of Air Transportation. 31:1-17
Neural network approximations have become attractive to compress data for automation and autonomy algorithms for use on storage-limited and processing-limited aerospace hardware. However, unless these neural network approximations can be exhaustively
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dc19cc347ac1cdfcf7a828be78ecb060
https://doi.org/10.2514/1.d0255
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2
ARCH-COMP22 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants
Autor: 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
Publikováno v: Lopez, D M, Althoff, M, Benet, L, Chen, X, Fan, J, Forets, M, Huang, C, Johnson, T T, Ladner, T, Li, W, Schilling, C & Zhu, Q 2022, ARCH-COMP22 category report: Artificial intelligence and neural network control systems (AINNCS) for continuous and hybrid systems plants . in G Frehse, M Althoff, E Schoitsch & J Guiochet (eds), 9th International Workshop on Applied Verification of Continuous and Hybrid Systems (ARCH22) . EasyChair, EPiC Series in Computing, vol. 90, pp. 142-184, 9th International Workshop on Applied Verification of Continuous and Hybrid Systems (ARCH22), Munich, Germany, 06/09/2022 . https://doi.org/10.29007/wfgr
This report presents the results of a friendly competition for formal verification of continuous and hybrid systems with artificial intelligence (AI) components. Specifically, machine learning (ML) components in cyber-physical systems (CPS), such as
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f14458daeccc4f4b6f6e5f712cd1895
https://doi.org/10.29007/wfgr
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3
Verification of piecewise deep neural networks: a star set approach with zonotope pre-filter
Autor: Luan Viet Nguyen, Stanley Bak, Neelanjana Pal, Weiming Xiang, Xiaodong Yang, Taylor T. Johnson, Patrick Musau, Diego Manzanas Lopez, Hoang-Dung Tran
Publikováno v: Formal Aspects of Computing. 33:519-545
Verification has emerged as a means to provide formal guarantees on learning-based systems incorporating neural network before using them in safety-critical applications. This paper proposes a new verification approach for deep neural networks (DNNs)
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::35886cccc5a5e832422ded3eefabe952
https://doi.org/10.1007/s00165-021-00553-4
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8
Robustness Verification of Semantic Segmentation Neural Networks Using Relaxed Reachability
Autor: Patrick Musau, Neelanjana Pal, Taylor T. Johnson, Xiaodong Yang, Stanley Bak, Nathaniel Hamilton, Diego Manzanas Lopez, Hoang-Dung Tran
Publikováno v: Computer Aided Verification ISBN: 9783030816841
CAV (1)
This paper introduces robustness verification for semantic segmentation neural networks (in short, semantic segmentation networks [SSNs]), building on and extending recent approaches for robustness verification of image classification neural networks
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::38fc31bd46016c42ceb8b98e5bbfb53c
https://doi.org/10.1007/978-3-030-81685-8_12
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9
ARCH-COMP21 Category Report:Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants
Autor: Taylor T. Johnson, Diego Manzanas Lopez, Luis Benet, Marcelo Forets, Sebastián Guadalupe, Christian Schilling, Radoslav Ivanov, Taylor J. Carpenter, James Weimer, Insup Lee
Publikováno v: Johnson, T T, Lopez, D M, Benet, L, Forets, M, Guadalupe, S, Schilling, C, Ivanov, R, Carpenter, T J, Weimer, J & Lee, I 2021, ARCH-COMP21 Category Report : Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants . in G Frehse & M Althoff (eds), 8th International Workshop on Applied Verification of Continuous and Hybrid Systems (ARCH21) . EasyChair, EPiC Series in Computing, vol. 80, pp. 90-119, 8th International Workshop on Applied Verification of Continuous and Hybrid Systems (ARCH21), Bruxelles, Belgium, 09/07/2021 . https://doi.org/10.29007/kfk9
This report presents the results of a friendly competition for formal verification of continuous and hybrid systems with artificial intelligence (AI) components. Specifically, machine learning (ML) components in cyber-physical systems (CPS), such as
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28acd3b5ce15f11c3028c9bd4c57ac8c
https://vbn.aau.dk/da/publications/ed7d6bed-75ae-482e-9c9d-edaef215cf4b
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10
ARCH-COMP20 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants
Autor: Chao Huang, Elena Botoeva, Taylor T. Johnson, Jiameng Fan, Francesco Leofante, Chelsea Sidrane, Amir Maleki, Patrick Musau, Diego Manzanas Lopez, Hoang-Dung Tran
Publikováno v: ARCH
This report presents the results of a friendly competition for formal verification of continuous and hybrid systems with artificial intelligence (AI) components. Specifically, machine learning (ML) components in cyber-physical systems (CPS), such as
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::881be48979fbecd28034dd4a29f5001c
https://doi.org/10.29007/9xgv
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