Variational Graph Auto-Encoder (VGAE)

Our researchers Tao Wu and Salli MOUSTAFA, PhD enabled Variational Graph Auto-Encoder (VGAE) on our technology platform. T. N. Kipf and M. Welling proposed the model to make link predictions of network-structured data. The training and inference source code can be found in the following source code repository. We hope that this contribution fosters the research of Graph Neural Networks (GNNs).

This repository contains the training and inference source code of a VGAE model for our technology platform. Please note that model training requires TensorFlow 1.15 and model inference from our pyACL framework.

Please use the following link to visit our repository.
https://gitee.com/ascend/modelzoo/tree/master/built-in/TensorFlow/Research/gnn/VGAE_ID2868_for_TensorFlow