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The 'Clever Hans' effect occurs when the learned model produces correct predictions based on the 'wrong' features.
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Explaining nonlinear classification decisions with deep Taylor decomposition
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Unsupervised anomaly detection with generative adversarial networks to guide marker discovery
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GANomaly: Semi-supervised anomaly detection via adversarial training
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Deep one-class classification
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MVTec AD - A comprehensive real-world dataset for unsupervised anomaly detection
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Inverse-transform autoencoder for anomaly detection
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Unmasking Clever Hans predictors and assessing what machines really learn
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Layer-wise relevance propagation: An overview
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MNIST-C: A robustness benchmark for computer vision
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Towards explaining anomalies: A deep Taylor decomposition of one-class models
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Deep semi-supervised anomaly detection
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