Time Series Anomaly Detection by GANs
Time Series Anomaly Detection has always been at the center of active discussion in both academia and business. The areas of the applications of Time Series Anomaly Detection are numerous starting from monitoring systems and ending with stock market analysis. The main purpose of the paper is to suggest a GAN-based Time Series Anomaly Detection algorithm and compare its results with already existing time series anomaly detection algorithms.
Keywords: Generative adversarial networks, neural networks, time series, anomaly detection.