The Generalized Lasso with Nonlinear Observations and Generative Priors
NIPS 2020, 2020.
We have provided recovery guarantees for the generalized Lasso with nonlinear observations and generative priors
In this paper, we study the problem of signal estimation from noisy non-linear measurements when the unknown $n$-dimensional signal is in the range of an $L$-Lipschitz continuous generative model with bounded $k$-dimensional inputs. We make the assumption of sub-Gaussian measurements, which is satisfied by a wide range of measurement mo...More
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