Personalizing Sustainable Agriculture with Causal Machine Learning

This repository contains the code developed for the Personalizing Sustainable Agriculture with Causal Machine Learning paper, published at the "Tackling Climate Change with Machine Learning" Workshop as part of NeurIPS'22. The paper won the "Best Proposal Paper" Award.

Authors: Georgios Giannarakis, Vasileios Sitokonstantinou, Roxanne Suzette Lorilla, Charalampos Kontoes

Email contact: giannarakis (at) noa.gr

To cite this work, copy:

@article{giannarakis2022personalizing,
  title   = {Personalizing Sustainable Agriculture with Causal Machine Learning},
  author  = {Giannarakis, Georgios and Sitokonstantinou, Vasileios and Lorilla, Roxanne Suzette and Kontoes, Charalampos},
  journal = {arXiv preprint arXiv:2211.03179},
  year    = {2022}
}

Dependencies

The code was developed and tested in Python 3.9.12. To install the dependencies run:

pip install -r requirements.txt

Acknowledgements

This work has been supported by the EIFFEL project (EU Horizon 2020 - GA No. 101003518) and the MICROSERVICES project (2019-2020 BiodivERsA joint call, under the BiodivClim ERA-Net COFUND programme, and with the GSRI, Greece - No. T12ERA5-00075).

Agri-Hub/CCAI-NeurIPS22-Personalizing

Personalizing Sustainable Agriculture with Causal Machine Learning

Dependencies

Acknowledgements