77 citations · 77 across the 2 of their papers we have counts for
2 papers
cs.LG2020
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models
Fadhel Ayed, Lorenzo Stella, Tim Januschowski +1
This paper introduces a new methodology for detecting anomalies in time series data, with a primary application to monitoring the health of (micro-) services and cloud resources. T…
cs.LG2019★ 77 cited
GluonTS: Probabilistic Time Series Models in Python
Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider +10
We introduce Gluon Time Series (GluonTS, available at https://gluon-ts.mxnet.io), a library for deep-learning-based time series modeling. GluonTS simplifies the development of and…