Yuma Koizumi

Complementary Set Variational Autoencoder for Supervised Anomaly Detection

2018

Anomalies have broad patterns corresponding to their causes. In industry, anomalies are typically observed as equipment failures. Anomaly detection aims to detect such failures as anomalies. Although this is usually a binary classification task, the …