Machine Learning, Computational Graphs, Generative Adversarial, Deep Learning.
We developed a method to generate graphs that are topologically equivalent to subgraphs in a much larger network. Using the generated graphs as training data in lieu of the given network, we showed that models using this approach can outperform state-of-the-art algorithms in both speed and