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GitHub - svjan5/GNNs-for-NLP: Graph Neural Networks for Natural Language Process...
source link: https://github.com/svjan5/GNNs-for-NLP
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Readme.md
Graph Neural Networks for Natural Language Processing
The repository contains code examples for GNN-for-NLP tutorial at EMNLP 2019.
Slides can be downloaded from here.
Dependencies
- Compatible with PyTorch 1.x, TensorFlow 1.x and Python 3.x.
- Dependencies can be installed using
requirements.txt
.
TensorFlow Examples:
tf_gcn.py
contains simplified implementation of first-order approximation of GCN model proposed by Kipf et. al. (2016)- Extensions of the same implementation for different problems:
- Relation Extraction: RESIDE
- GCNs for Word Embeddings: WordGCN
- Document Time-stamping: NeuralDater
PyTorch Examples:
pytorch_gcn.py
is pytorch equivalent oftf_gcn.py
implemented using pytorch-geometric.- Several other examples are available here.
Additional Resources:
- Short writeup on theory behind Graph Convolutional Networks [Pdf] (refer Chapter-2).
- GNN recent papers.
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