77 citations · 136 across the 2 of their papers we have counts for
2 papers
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…
stat.ML2019★ 59 cited
Deep Factors for Forecasting
Yuyang Wang, Alex Smola, Danielle C. Maddix +3
Producing probabilistic forecasts for large collections of similar and/or dependent time series is a practically relevant and challenging task. Classical time series models fail to…