Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data
Anomalies refer to the departure of systems and devices from their normal behaviour in
standard operating conditions. An anomaly in an industrial device can indicate an upcoming
failure, often in the temporal direction. In this paper, we make two contributions: 1) we
estimate conditional quantiles and consider three different ways to define anomalies based
on the estimated quantiles. 2) we use a new learnable activation function in the popular
Long Short Term Memory networks (LSTM) architecture to model temporal long-range …
standard operating conditions. An anomaly in an industrial device can indicate an upcoming
failure, often in the temporal direction. In this paper, we make two contributions: 1) we
estimate conditional quantiles and consider three different ways to define anomalies based
on the estimated quantiles. 2) we use a new learnable activation function in the popular
Long Short Term Memory networks (LSTM) architecture to model temporal long-range …
QUANTILE-LSTM: A ROBUST LSTM FOR ANOMALY DETECTION
Anomalies refer to departure of systems and devices from their normal behaviour in
standard operating conditions. An anomaly in an industrial device can indicate an upcoming
failure, often in the temporal direction. In this paper, we make two contributions: 1) we
estimate conditional quantiles, and consider three different ways to define anomalies based
on the estimated quantiles and 2) use a new learnable activation function in the popular
Long Short Term Memory (LSTM) architecture to model temporal long-range dependency. In …
standard operating conditions. An anomaly in an industrial device can indicate an upcoming
failure, often in the temporal direction. In this paper, we make two contributions: 1) we
estimate conditional quantiles, and consider three different ways to define anomalies based
on the estimated quantiles and 2) use a new learnable activation function in the popular
Long Short Term Memory (LSTM) architecture to model temporal long-range dependency. In …
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