Bias and Generalization in Deep Generative Models: An Empirical Study

Inthis paper we propose aframework to systematically investigate bias and generalization in deep generative models of images. Inspired byexperimental methods fromcognitivepsychology,weprobe each learning algorithm with carefully designed training datasets tocharacterize when and howexisting models generate novelattributes and their combinations.