Deep Graph Translation

ICLR 2020 Anonymous

Deep graph generation models have achieved great successes recently, among which, however, are typically unconditioned generative models that have no control over the target graphs are given an input graph. In this paper, we propose a novel Graph-Translation-Generative-Adversarial-Networks (GT-GAN) that transforms the input graphs into their target output graphs... (read more)

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