Robustness Validation
Robustness Validation is a systematic evaluation method that distinguishes itself by assessing the stability and reliability of a process under varying conditions to ensure consistent performance across perturbations, uncertainties, and operational variability.
32
Publications
1.5K
Citations
114
Authors
62
Institutions
Publications per year
2017–2026
18
Parents
32
SoK: Certified Robustness for Deep Neural Networks
Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations
Jeet Mohapatra, Tsui-Wei Weng, Pin‐Yu Chen et al. · 2020 · 60 citations · Full text
Robustness Verification of Classification Deep Neural Networks via Linear Programming
Lin Wang, Zhengfeng Yang, Xin Chen et al. · 2019 · 42 citations
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Shanghai Key Laboratory of Trustworthy Computing
Shanghai, China
3 h-index
8 publications
280 citations

East China Normal University
Shanghai, China
3 h-index
8 publications
280 citations
Tongji University
Shanghai, China
2 h-index
2 publications
56 citations

Universidad de Granada
Granada, Spain
2 h-index
6 publications
144 citations
Moscow Institute of Thermal Technology
Moscow, Russia
1 h-index
3 publications
180 citations

University of Liverpool
Liverpool, United Kingdom
1 h-index
1 publications
18 citations
Nanyang Technological University
Singapore, Singapore
1 h-index
2 publications
88 citations
Infineon Technologies (Germany)
Munich, Germany
1 h-index
1 publications
23 citations
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Repository · 2 publications · 33 citations
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1 publications · 36 citations
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Conference · 1 publications · 26 citations
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1 publications · 22 citations
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1 publications · 38 citations
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