897 citations · 1.2k across the 10 of their papers we have counts for
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stat.ML2018
Unsupervised Detection and Explanation of Latent-class Contextual Anomalies
Jacob Kauffmann, Grégoire Montavon, Luiz Alberto Lima +3
Detecting and explaining anomalies is a challenging effort. This holds especially true when data exhibits strong dependencies and single measurements need to be assessed and analyz…
stat.ML2018★ 103 cited
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models
Jacob Kauffmann, Klaus-Robert Müller, Grégoire Montavon
A common machine learning task is to discriminate between normal and anomalous data points. In practice, it is not always sufficient to reach high accuracy at this task, one also w…