  Planar graph drawings tend to be aesthetically pleasing. In this poster we
explore a Neural Network's capability of learning various planar graph classes.
Additionally, we also investigate the effectiveness of the model in
generalizing beyond planarity. We find that the model can outperform
conventional techniques for certain graph classes. The model, however, appears
to be more susceptible to randomness in the data, and seems to be less robust
than expected.
