18 citations · 18 across the 1 of their papers we have counts for
4 papers
A Unifying Review of Deep and Shallow Anomaly Detection
Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen +5
Deep learning approaches to anomaly detection have recently improved the state of the art in detection performance on complex datasets such as large collections of images or text.…
The Clever Hans Effect in Anomaly Detection
Jacob Kauffmann, Lukas Ruff, Grégoire Montavon +1
The 'Clever Hans' effect occurs when the learned model produces correct predictions based on the 'wrong' features. This effect which undermines the generalization capability of an…
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…
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…