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Found 3 papers, 1 papers with code
A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization
In a wide variety of situations, anomalies in the behaviour of a complex system, whose health is monitored through the observation of a random vector X = (X1,.
Anomaly detection with Wasserstein GAN
W-GAN with encoder seems to produce state of the art anomaly detection scores on MNIST dataset and we investigate its usage on multi-variate time series.
Calibration of One-Class SVM for MV set estimation
Our approach makes it possible to tune the hyperparameters automatically and obtain nested set estimates.
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