To benchmark the performance of LoGAN for non-periodic systems at different stoichiometries from the training set, we aimed to reproduce the 14 ), while the atomic descriptors are the raw P i . Thus, the atomic descriptors reflect the information that the critic receives during training, namely the local environments of which there are only few relevant ones. In contrast, the molecular descriptors reflect the conformation and diversity of the resulting predicted structures, as well as the information that the filtering procedure receives. The atom representations (Fig. ) cluster strongly according to their atom-type. Within one atom type, the local environments of the training and test sets are very similar and follow a similar distribution. In contrast, the molecular representations (Fig. right) of the training and test set are less similar, underlining our assumption that there are many physically valid structures, while there are only few important local environments. Therefore, a discriminator between real and fake structures can be trained more easily and efficiently on atomic environments.