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Framework for Certification of AI-Based Systems

Framework for Certification of AI-Based Systems

21 February 2023
Maxime Gariel
Brian Shimanuki
R. Timpe
E. Wilson
ArXiv (abs)PDFHTMLGithub (15631★)

Papers citing "Framework for Certification of AI-Based Systems"

5 / 5 papers shown
Predictive Uncertainty for Runtime Assurance of a Real-Time Computer Vision-Based Landing System
Predictive Uncertainty for Runtime Assurance of a Real-Time Computer Vision-Based Landing System
Romeo Valentin
Sydney M. Katz
Artur B. Carneiro
Don Walker
Mykel J. Kochenderfer
EDLUQCV
243
1
0
13 Aug 2025
DEM: A Method for Certifying Deep Neural Network Classifier Outputs in
  Aerospace
DEM: A Method for Certifying Deep Neural Network Classifier Outputs in AerospaceSymposium on Dependable Autonomic and Secure Computing (DASC), 2024
Guy Katz
Natan Levy
Idan Refaeli
Raz Yerushalmi
AAML
358
2
0
04 Jan 2024
Formal and Practical Elements for the Certification of Machine Learning
  Systems
Formal and Practical Elements for the Certification of Machine Learning SystemsSymposium on Dependable Autonomic and Secure Computing (DASC), 2023
Jean-Guillaume Durand
Arthur Dubois
Robert J. Moss
181
6
0
05 Oct 2023
gRoMA: a Tool for Measuring the Global Robustness of Deep Neural
  Networks
gRoMA: a Tool for Measuring the Global Robustness of Deep Neural Networks
Natan Levy
Raz Yerushalmi
Guy Katz
AAML
377
2
0
05 Jan 2023
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
2.7K
21,359
0
16 Feb 2016
1
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