10 citations · 14 across the 3 of their papers we have counts for
3 papers
Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models
Sven Kruschel, Nico Hambauer, Sven Weinzierl +3
Machine learning is permeating every conceivable domain to promote data-driven decision support. The focus is often on advanced black-box models due to their assumed performance ad…
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
Patrick Zschech, Sven Weinzierl, Nico Hambauer +2
The number of information systems (IS) studies dealing with explainable artificial intelligence (XAI) is currently exploding as the field demands more transparency about the intern…
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
Maximilian Harl, Marvin Herchenbach, Sven Kruschel +3
In recent years, large pre-trained deep neural networks (DNNs) have revolutionized the field of computer vision (CV). Although these DNNs have been shown to be very well suited for…