Seems like all the results are better than DrBC baseline

Use PReLU in the model
Use Adam optimizer with a big learning rate
Try to have a variable number of edges in the generated graphs
Try dropping edges while training
Graphs are only of 'powerlaw' type.
Use unique convolutions.
Use blocks of convolutions followed with max-pooling and skip connections
Use gradient clipping