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(PyTorch implementation) An expremely simple & fast graph filtering for CF
Jupyter Notebook 53.87%
Python 46.13%
linear_gf's Introduction
- Extremely faster implementation of linear low-pass graph filter part in GF-CF [Shen et al. CIKM'21]
- Specifically, we use sparse matrices & GPU acceleration for the inference
- You can find the original implementation of full GF-CF method in: https://github.com/yshenaw/GF_CF
- You can simply test & run cells in 'Graph Filtering (Light).ipynb'
- Our code provides 'MovieLens-1M', 'Yelp', 'Gowalla', and 'Amazon-Book' datasets
- One can possibly customize the code to implement batch inference-fashion based on your preference
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