Examples of distribution-learning models for molecules include auto-regressive approaches , generative adversarial networks , and adversarial auto-encoders Overall, evaluation of generative models is not straightforward and required the development of new metrics ). However, these metrics do not detect if methods reproduce the training data with minimal changes, which we term the copy problem.