4 citations · 4 across the 1 of their papers we have counts for
2 papers
cs.LG2022★ 4 cited
A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty Estimates for AI Models
Pascal Gerber, Lisa Jöckel, Michael Kläs
Outcomes of data-driven AI models cannot be assumed to be always correct. To estimate the uncertainty in these outcomes, the uncertainty wrapper framework has been proposed, which…
cs.CY2019
Hardening of Artificial Neural Networks for Use in Safety-Critical Applications -- A Mapping Study
Rasmus Adler, Mohammed Naveed Akram, Pascal Bauer +6
Context: Across different domains, Artificial Neural Networks (ANNs) are used more and more in safety-critical applications in which erroneous outputs of such ANN can have catastro…