111 citations
- Technical University of MunichDE4 papers
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Showing cs.LGShow all
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cs.LG2023
AGNES: Abstraction-guided Framework for Deep Neural Networks Security
Akshay Dhonthi, Marcello Eiermann, Ernst Moritz Hahn +1
Deep Neural Networks (DNNs) are becoming widespread, particularly in safety-critical areas. One prominent application is image recognition in autonomous driving, where the correct…
cs.LG2021★ 2 cited
Classification and Uncertainty Quantification of Corrupted Data using Semi-Supervised Autoencoders
Philipp Joppich, Sebastian Dorn, Oliver De Candido +2
Parametric and non-parametric classifiers often have to deal with real-world data, where corruptions like noise, occlusions, and blur are unavoidable - posing significant challenge…
cs.LG2021★ 49 cited
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Sebastian Houben, Stephanie Abrecht, Maram Akila +38
The use of deep neural networks (DNNs) in safety-critical applications like mobile health and autonomous driving is challenging due to numerous model-inherent shortcomings. These s…