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# Local Neighborhood Graph Autoencoders
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# Multi-Task Graph Autoencoders
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This is a Keras implementation of the symmetrical autoencoder architecture with parameter sharing for the tasks of unsupervised link prediction and semi-supervised node classification, as described in the following:
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This is a Keras implementation of the symmetrical autoencoder architecture with parameter sharing for the tasks of link prediction and semi-supervised node classification, as described in the following:
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Tran, Phi Vu. [Learning to Make Predictions on Graphs with Autoencoders.](https://arxiv.org/abs/1802.08352) Proceedings of the 5th IEEE International
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Conference on Data Science and Advanced Analytics (2018). Full oral paper.
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Tran, Phi Vu. [Multi-Task Graph Autoencoders.](https://arxiv.org/abs/1811.02798) NIPS 2018 Workshop on Relational Representation Learning. Short poster paper.
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![FCN_schematic](figure1.png?raw=true)
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![schematic](figure1.png?raw=true)
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## Requirements
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The code is tested on Ubuntu 16.04 with the following components:

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