2022
Signal Recovery with Non-Expansive Generative Network Priors
NeurIPS 2022accept
We study compressive sensing with a deep generative network prior. Initial theoretical guarantees for efficient recovery from compressed linear measurements have been developed for signals in the range of a ReLU network with Gaussian weights and logarithmic expansivity: that is when each layer is la…