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cs.LG2019★ 8 cited
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…
cs.LG2018
Task-Aware Compressed Sensing with Generative Adversarial Networks
Maya Kabkab, Pouya Samangouei, Rama Chellappa
In recent years, neural network approaches have been widely adopted for machine learning tasks, with applications in computer vision. More recently, unsupervised generative models…