Harnessing Feature Clustering For Enhanced Anomaly Detection With Variational Autoencoder And Dynamic Threshold
Author:
Affiliation:
1. University of Maryland Baltimore County Information Systems,Baltimore,MD,21250
2. National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory,Princeton,NJ,USA
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10640794.pdf?arnumber=10640794
Reference16 articles.
1. Graph Neural Network-Based Anomaly Detection in Multivariate Time Series
2. Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network
3. Time-Series Anomaly Detection Service at Microsoft
4. Long short term memory networks for anomaly detection in time series;Malhotra;Esann,2015
5. Conformal k-nn anomaly detector for univariate data streams;Ishimtsev,2017
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