290 citations · 646 across the 8 of their papers we have counts for
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stat.ML2019★ 144 cited
Explanations can be manipulated and geometry is to blame
Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders +3
Explanation methods aim to make neural networks more trustworthy and interpretable. In this paper, we demonstrate a property of explanation methods which is disconcerting for both…
cs.LG2019
Software and application patterns for explanation methods
Maximilian Alber
Deep neural networks successfully pervaded many applications domains and are increasingly used in critical decision processes. Understanding their workings is desirable or even req…