  One of the most discussed issues in graph generative modeling is the ordering
of the representation. One solution consists of using equivariant generative
functions, which ensure the ordering invariance. After having discussed some
properties of such functions, we propose 3G-GAN, a 3-stages model relying on
GANs and equivariant functions. The model is still under development. However,
we present some encouraging exploratory experiments and discuss the issues
still to be addressed.
