https://github.com/aveek-saha/graph-conv-net

A TensorFlow 2 implementation of Graph Convolutional Networks (GCN)

https://github.com/aveek-saha/graph-conv-net

Science Score: 23.0%

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Keywords

gcn gcnn graph-convolutional-networks graph-neural-networks graphs tensoflow tensorflow2
Last synced: 5 months ago · JSON representation

Repository

A TensorFlow 2 implementation of Graph Convolutional Networks (GCN)

Basic Info
  • Host: GitHub
  • Owner: Aveek-Saha
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 174 KB
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Topics
gcn gcnn graph-convolutional-networks graph-neural-networks graphs tensoflow tensorflow2
Created over 5 years ago · Last pushed over 5 years ago
Metadata Files
Readme License

README.md

Graph Convolutional Networks

A TensorFlow 2 implementation of Graph Convolutional Networks for classification of nodes from the paper, Thomas N. Kipf, Max Welling, Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)

This is my attempt at trying to understand and recreate the neural network from from the paper. You can find the official implementation here: https://github.com/tkipf/gcn

Requirements

  • tensorflow 2
  • networkx
  • numpy
  • scikit-learn

Run

To train and test the network with the CORA dataset.

bash python train.py

Cite

Please cite the original paper if you use this code in your own work:

@inproceedings{kipf2017semi, title={Semi-Supervised Classification with Graph Convolutional Networks}, author={Kipf, Thomas N. and Welling, Max}, booktitle={International Conference on Learning Representations (ICLR)}, year={2017} }

Owner

  • Name: Aveek Saha
  • Login: Aveek-Saha
  • Kind: user
  • Location: Boston, MA
  • Company: @akamai

Cloud Computing, Machine Learning and Full Stack. SDE co-op @akamai. MSCS student @northeastern. Previously at @HewlettPackard, @altimetrik & @ IIT Kgp.

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