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