Author

A. Pruden

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Open access Sep 2026

VRGAN: A Deep Generative Framework for Unsupervised Anomaly Detection in Multivariate Time-Series Data

VRGAN is proposed, a deep generative anomaly detection framework designed for unsupervised multivariate time-series analysis that stands out by eliminating the need for assumptions or true label information.

Joung Min Choi, C. Brown, A. Pruden et al. · Applied Sciences · 0 citations