# Robust compressed sensing of generative models

16 Jun 2020Ajil JalalLiu LiuAlexandros G. DimakisConstantine Caramanis

The goal of compressed sensing is to estimate a high dimensional vector from an underdetermined system of noisy linear equations. In analogy to classical compressed sensing, here we assume a generative model as a prior, that is, we assume the vector is represented by a deep generative model $G: \mathbb{R}^k \rightarrow \mathbb{R}^n$... (read more)

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