Authors
Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C Maddix, Syama Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang
Publication date
2020/1/1
Journal
Journal of Machine Learning Research
Volume
21
Issue
116
Pages
1-6
Description
We introduce the Gluon Time Series Toolkit (GluonTS), a Python library for deep learning based time series modeling for ubiquitous tasks, such as forecasting and anomaly detection. GluonTS simplifies the time series modeling pipeline by providing the necessary components and tools for quick model development, efficient experimentation and evaluation. In addition, it contains reference implementations of state-of-the-art time series models that enable simple benchmarking of new algorithms.
Total citations
201920202021202220232024112264889266
Scholar articles
A Alexandrov, K Benidis, M Bohlke-Schneider… - Journal of Machine Learning Research, 2020
A Alexandrov, K Benidis, M Bohlke-Schneider… - arXiv preprint arXiv:1906.05264, 2019
A Alexandrov, K Benidis, M Bohlke-Schneider… - arXiv preprint arXiv:1906.05264, 2019