DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks ​

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Authors: Valentin Flunkert, David Salinas, Jan Gasthaus
Year: 2017
Journal: International Journal of Forecasting
DOI: 10.1016/j.ijforecast.2019.07.001
Publisher: https://arxiv.org/abs/1704.04110

Keywords: deepar, forecasting

Abstract ​

We present DeepAR a probabilistic forecasting method.

Cite this paper ​

@misc{deepar2017,
  title  = {DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks},
  author = {Valentin Flunkert, David Salinas, Jan Gasthaus},
  year   = {2017},
  journal = {International Journal of Forecasting},
  doi    = {10.1016/j.ijforecast.2019.07.001},
  url    = {https://doi.org/10.1016/j.ijforecast.2019.07.001},
}

Source files ​

• [metadata.json](https://raw.githubusercontent.com/badhope/ScholarLib/main/papers/computer-science/Time-Series-Analysis/Forecasting/2019-and-earlier/International Journal of Forecasting/empirical/forecasting/deepar/metadata.json)
• [paper.bib](https://raw.githubusercontent.com/badhope/ScholarLib/main/papers/computer-science/Time-Series-Analysis/Forecasting/2019-and-earlier/International Journal of Forecasting/empirical/forecasting/deepar/paper.bib)