# Appendice B: Riferimenti
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 [Tim Januschowski e Stephan Kolassa. A classification of business forecasting problems. Foresight: The International Journal of Applied Forecasting. 2019](https://foresight.forecasters.org/product/foresight-issue-53/) 

 [David Salinas, Valentin Flunkert, Jan Gasthaus e Tim Januschowski. DeepAR: Probabilistic forecasting with autoregressive recurrent networks. International Journal of Forecasting. 2019](https://arxiv.org/abs/1704.04110) 

 [Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert e Tim Januschowski. Probabilistic Forecasting with Spline Quantile Function RNNs. International Conference on Artificial Intelligence and Statistics, 22a edizione. 2019](http://proceedings.mlr.press/v89/gasthaus19a.html) 

 [Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider e Laurent Callot. Criteria for classifying forecasting methods. International Journal of Forecasting. 2019](https://www.sciencedirect.com/science/article/pii/S0169207019301529) (account di accesso necessario) 

 [Tim Januschowski, Jan Gasthaus, Yuyang Wang, Syama Sundar Rangapuram e Laurent Callot. Deep Learning for Forecasting. Foresight: The International Journal of Applied Forecasting. 2018](https://foresight.forecasters.org/product/foresight-issue-51/) 

 [Tim Januschowski, Jan Gasthaus, Yuyang Wang, Syama Sundar Rangapuram e Laurent Callot. Deep Learning for Forecasting: Current Trends and Challenges. Foresight: The International Journal of Applied Forecasting. 2018](https://foresight.forecasters.org/product/foresight-issue-52/) 

 [Joos-Hendrik Bose, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Dustin Lange, David Salinas, Sebastian Schelter, Matthias Seeger e Yuyang Wang. Probabilistic demand forecasting at scale. Atti di VLDB Endowment. 2017](http://www.vldb.org/pvldb/vol10/p1694-schelter.pdf)