4 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.HC2021★ 1 cited
Quality Metrics for Transparent Machine Learning With and Without Humans In the Loop Are Not Correlated
Felix Biessmann, Dionysius Refiano
The field explainable artificial intelligence (XAI) has brought about an arsenal of methods to render Machine Learning (ML) predictions more interpretable. But how useful explanati…
cs.CV2019★ 4 cited
A psychophysics approach for quantitative comparison of interpretable computer vision models
Felix Biessmann, Dionysius Irza Refiano
The field of transparent Machine Learning (ML) has contributed many novel methods aiming at better interpretability for computer vision and ML models in general. But how useful the…