quantile-Long Short Term Memory: A Robust, Time Series Anomaly Detection Method
Author:
Affiliation:
1. Birla Institute of Technology and Science, Goa, India
2. GE Healthcare, Bangalore, India
3. Wadhwani AI, Bangalore, India
Funder
SERB SURE-DST
SERB CRG-DST
DBT-Builder project
Government of India
CDRF BITS Pilani
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/9078688/10635096/10398596.pdf?arnumber=10398596
Reference28 articles.
1. Case Study: A Semi-Supervised Methodology for Anomaly Detection and Diagnosis
2. Activation Anomaly Analysis
3. Variational autoencoder based anomaly detection using reconstruction probability;Jinwon,2015
4. Anomaly Detection Using Autoencoders with Nonlinear Dimensionality Reduction
5. Anomaly Detection Based on Convolutional Recurrent Autoencoder for IoT Time Series
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