Graph Generation via Scattering

@article{Zou2018GraphGV,
  title={Graph Generation via Scattering},
  author={Dongmian Zou and Gilad Lerman},
  journal={ArXiv},
  year={2018},
  volume={abs/1809.10851}
}
Generative networks have made it possible to generate meaningful signals such as images and texts from simple noise. Recently, generative methods based on GAN and VAE were developed for graphs and graph signals. However, some of these methods are complex as well as difficult to train and fine-tune. This work proposes a graph generation model that uses a recent adaptation of Mallat's scattering transform to graphs. The proposed model is naturally composed of an encoder and a decoder. The encoder… 
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