... scale : The case for deep distributional time series models ' , CORR , abs / 2007.15541 , ( 2020 ) . [ 5 ] Shaojie Bai , J. Zico Kolter , and Vladlen Koltun , ' An empirical eval- uation of generic ... Time Series Anomaly Detection.

... 109, https://doi.org/10.1007/978-3-030-76352-7_14 2021. Fig. 1. Latency metric monitoring with temporal aggregation using different. Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models 1 Introduction.

... anomaly detection methods using (probabilistic) forecasting models. Overview of forecasting models can be found in recent tutorials [7]. These approaches have the advantage ... Deep Distributional Time Series Models 107 6 Conclusion.

... (AIOPS 2020) 85 Performance Diagnosis in Cloud Microservices Using Deep Learning . Li Wu, Jasmin Bogatinovski, Sasho Nedelkoski, Johan Tordsson, and Odej Kao . . . . . Anomaly Detection at Scale: The Case for Deep Distributional Time Series ...