40 citations · 47 across the 5 of their papers we have counts for
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cs.LG2021
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…
cs.LG2020★ 2 cited
Risk Assessment for Machine Learning Models
Paul Schwerdtner, Florens Greßner, Nikhil Kapoor +5
In this paper we propose a framework for assessing the risk associated with deploying a machine learning model in a specified environment. For that we carry over the risk definitio…