Parameter Efficient Deep Probabilistic Forecasting

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Deep Learningpedpf
Overview

PEDPF Airlab Amsterdam

Parameter Efficient Deep Probabilistic Forecasting (PEDPF) is a repository containing code to run experiments for several deep learning based probabilistic forecasting methods. For more details, see our paper.

Reference

Olivier Sprangers, Sebastian Schelter, Maarten de Rijke. Parameter Efficient Deep Probabilistic Forecasting. Accepted as journal paper to International Journal of Forecasting.

License

This project is licensed under the terms of the Apache 2.0 license.

Acknowledgements

This project was developed by Airlab Amsterdam.

Owner
Olivier Sprangers
PhD student at University of Amsterdam
Olivier Sprangers
GitHub Repository
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