13 citations · 20 across the 4 of their papers we have counts for
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eess.IV2021★ 2 cited
Evaluating saliency methods on artificial data with different background types
Céline Budding, Fabian Eitel, Kerstin Ritter +1
Over the last years, many 'explainable artificial intelligence' (xAI) approaches have been developed, but these have not always been objectively evaluated. To evaluate the quality…
stat.ML2021★ 1 cited
Scrutinizing XAI using linear ground-truth data with suppressor variables
Rick Wilming, Céline Budding, Klaus-Robert Müller +1
Machine learning (ML) is increasingly often used to inform high-stakes decisions. As complex ML models (e.g., deep neural networks) are often considered black boxes, a wealth of pr…