SGVAE: Sequential Graph Variational Autoencoder

17 Dec 2019Bowen JingEthan A. ChiJillian Tang

Generative models of graphs are well-known, but many existing models are limited in scalability and expressivity. We present a novel sequential graphical variational autoencoder operating directly on graphical representations of data... (read more)

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