TY - CONF A1 - Boget, Yoann A1 - Gregorová, Magda A1 - Kalousis, Alexandros T1 - Permutation Equivariant Generative Adversarial Networks for Graphs T2 - Neural Compression Workshop (CoRR) N2 - 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. Y1 - 2021 UR - https://opus4.kobv.de/opus4-fhws/frontdoor/index/index/docId/4956 VL - abs/2112.03621 ER -