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GANs for Time-Series Anomaly Detection by rehmatfaruqi11 is a document available to read on EtoBox.

What is GANs for Time-Series Anomaly Detection about?

This paper introduces a GAN-based framework for detecting anomalies in time-series data, particularly effective in finance and IoT applications. The proposed recurrent GAN (R-GAN) outperforms traditional models by effectively modeling temporal dynamics and achieving state-of-the-art results on Yahoo and NAB datasets. The findings suggest that GANs designed for time-series data provide a strong solution for various anomaly detection challenges.

Author

rehmatfaruqi11

Language

EN