A tensorflow implementation of the model proposed in "A Low Rank Weighted Graph Convolutional Approach to Weather Prediction" by Tyler Wilson, Pang-Ning Tan, and Lifeng Luo. Running the demo.py file will train and evaluate a model on the IGRA temperature prediction task described in the paper.

The implementation of the graph convolutional LSTM cell is based on Oliver Hennigh's implementation of a gridded convolutional LSTM cell available here.

When citing, please use: @inproceedings{wilson2018low, title={A Low Rank Weighted Graph Convolutional Approach to Weather Prediction}, author={Wilson, Tyler and Tan, Pang-Ning and Luo, Lifeng}, booktitle={2018 IEEE International Conference on Data Mining (ICDM)}, pages={627--636}, year={2018}, organization={IEEE} }

To install:

1. clone the github project
2. navigate to the cloned project directory on your machine
3. create a pip virtual environment that uses python 3.5+
4. activate the pip virtual environment you just created
5. install the requirements with "pip install -r requirements.txt"
6. Run the demo with "python demo.py"