8 citations · 21 across the 8 of their papers we have counts for
4 papers · 1 filter
Safety Performance of Neural Networks in the Presence of Covariate Shift
Chih-Hong Cheng, Harald Ruess, Konstantinos Theodorou
Covariate shift may impact the operational safety performance of neural networks. A re-evaluation of the safety performance, however, requires collecting new operational data and c…
Towards Rigorous Design of OoD Detectors
Chih-Hong Cheng, Changshun Wu, Harald Ruess +1
Out-of-distribution (OoD) detection techniques are instrumental for safety-related neural networks. We are arguing, however, that current performance-oriented OoD detection techniq…
Knowledge as Invariance -- History and Perspectives of Knowledge-augmented Machine Learning
Alexander Sagel, Amit Sahu, Stefan Matthes +5
Research in machine learning is at a turning point. While supervised deep learning has conquered the field at a breathtaking pace and demonstrated the ability to solve inference pr…
Towards Dependability Metrics for Neural Networks
Chih-Hong Cheng, Georg Nührenberg, Chung-Hao Huang +2
Artificial neural networks (NN) are instrumental in realizing highly-automated driving functionality. An overarching challenge is to identify best safety engineering practices for…