Invert and Defend: Model-based Approximate Inversion of Generative Adversarial Networks for Secure Inference

Wei-An Lin, Yogesh Balaji, Pouya Samangouei +1

Inferring the latent variable generating a given test sample is a challenging problem in Generative Adversarial Networks (GANs). In this paper, we propose InvGAN - a novel framewor…