An experimental analysis of under-sampling in deep semi-supervised anomaly detection. This MSc thesis evaluates how different sampling strategies affect the performance and efficiency of the AE-SAD framework.
python computer-science data-science machine-learning research deep-learning pytorch mnist neural-networks semi-supervised-learning autoencoder imbalanced-data anomaly-detection msc-thesis under-sampling
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Updated
Oct 22, 2025 - TeX