167 citations · 557 across the 21 of their papers we have counts for
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cs.AI2023★ 2 cited
Explaining and visualizing black-box models through counterfactual paths
Bastian Pfeifer, Mateusz Krzyzinski, Hubert Baniecki +3
Explainable AI (XAI) is an increasingly important area of machine learning research, which aims to make black-box models transparent and interpretable. In this paper, we propose a…
cs.AI2021★ 40 cited
Graph-guided random forest for gene set selection
Bastian Pfeifer, Hubert Baniecki, Anna Saranti +2
Machine learning methods can detect complex relationships between variables, but usually do not exploit domain knowledge. This is a limitation because in many scientific discipline…