4 citations · 9 across the 13 of their papers we have counts for
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cs.LG2023★ 4 cited
Learning to Intervene on Concept Bottlenecks
David Steinmann, Wolfgang Stammer, Felix Friedrich +1
While deep learning models often lack interpretability, concept bottleneck models (CBMs) provide inherent explanations via their concept representations. Moreover, they allow users…
cs.LG2023
One Explanation Does Not Fit XIL
Felix Friedrich, David Steinmann, Kristian Kersting
Current machine learning models produce outstanding results in many areas but, at the same time, suffer from shortcut learning and spurious correlations. To address such flaws, the…