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Sub-clusters of Normal Data for Anomaly Detection
We hypothesize that if there exists reasonably good feature space semantically separating sub-clusters of given normal data, unseen anomaly also can be well distinguished in the space from the normal data.
Mode Penalty Generative Adversarial Network with adapted Auto-encoder
To this end, generator network of GAN learns implicit distribution of real data set from the classification with candidate generated samples.
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