https://github.com/aveek-saha/graph-attention-net
A TensorFlow 2 implementation of Graph Attention Networks (GAT)
Science Score: 23.0%
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Low similarity (5.7%) to scientific vocabulary
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Repository
A TensorFlow 2 implementation of Graph Attention Networks (GAT)
Basic Info
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- Stars: 4
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Metadata Files
README.md
Graph Attention Networks
A TensorFlow 2 implementation of Graph Attention Networks for classification of nodes from the paper, Graph Attention Networks (Veličković et al., ICLR 2018).
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/PetarV-/GAT
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:
@article{
velickovic2018graph,
title="{Graph Attention Networks}",
author={Veli{\v{c}}kovi{\'{c}}, Petar and Cucurull, Guillem and Casanova, Arantxa and Romero, Adriana and Li{\`{o}}, Pietro and Bengio, Yoshua},
journal={International Conference on Learning Representations},
year={2018},
url={https://openreview.net/forum?id=rJXMpikCZ},
note={accepted as poster},
}
Owner
- Name: Aveek Saha
- Login: Aveek-Saha
- Kind: user
- Location: Boston, MA
- Company: @akamai
- Website: home.aveek.io
- Repositories: 66
- Profile: https://github.com/Aveek-Saha
Cloud Computing, Machine Learning and Full Stack. SDE co-op @akamai. MSCS student @northeastern. Previously at @HewlettPackard, @altimetrik & @ IIT Kgp.
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