PP: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

PROBLEM:

anomaly detection

input: multivariate time series to RNN ------> capture the normal patterns -----> reconstruct input data by the representations ------> use the reconstruction probabilities to determine anomalies. 

INTRODUCTION: 

Anomaly detection in different fields (graph, log messages, time series); 说明不同信息载体（图，文本，时序数据）的方法有很大的差异，可能在某些方面又是共通的。

Multiple univariate time series from the same device (or more generally, an entity) forms a multivariate time series.

RELATED WORK: 

PRELIMINARIES:

SUPPLEMENTARY KNOWLEDGE:

1. what does temporal dependency mean?

PP: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

原文：https://www.cnblogs.com/dulun/p/12241938.html