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Graph Convolutional Matrix Completion (Pytorch)

Re-implementation of Graph Convolutional Matrix Completion (PyTorch and PyTorch Geometric)

overview

approach

Note

This repository is NOT an official implementation of the paper.
The official implementation is this (Tensorflow).
Our experimental result is shown below and it doesn't reach to the score of the original.

Setup

  • Setup a virtual environment with python 3.6 or newer
  • Install requirements (pip)
    pip install -r requirements/1.txt
    pip install --verbose --no-cache-dir -r requirements/2.txt
    pip install -r requirements/3.txt
    

Installation of Pytorch Geometric is very troublesome and may destroy your python environment.
So, we strongly recommend to use a virtual environment (e.g. pyenv, virtualenv, pipenv, etc.).
Please see Pytorch Geometirc official document for more details.

Train and Test

cd src
python train.py
  • Configuration:
    The settings for train and test are in config.yml.

  • Dataset:
    Training dataset is MovieLens-100k. The dataset is automatically downloaded in data/ by running src/train.py.

Results

Note that this repo doesn't reach to the original one.

Test RMSE
Ours 0.968
Original 0.910

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Re-Implement "Graph Convolutional Matrix Completion" (PyTorch and PyTorch Geometric)

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