Global guarantees for enforcing deep generative priors by empirical risk
P Hand, V Voroninski - IEEE Transactions on Information …, 2019 - ieeexplore.ieee.org
We examine the theoretical properties of enforcing priors provided by generative deep
neural networks via empirical risk minimization. In particular we consider two models, one in …
neural networks via empirical risk minimization. In particular we consider two models, one in …
[PDF][PDF] Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk
P Hand, V Voroninski - IEEE Transactions on Information Theory, 2020 - par.nsf.gov
We examine the theoretical properties of enforcing priors provided by generative deep
neural networks via empirical risk minimization. In particular we consider two models, one in …
neural networks via empirical risk minimization. In particular we consider two models, one in …
Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk
P Hand, V Voroninski - IEEE Transactions on Information Theory, 2020 - dl.acm.org
We examine the theoretical properties of enforcing priors provided by generative deep
neural networks via empirical risk minimization. In particular we consider two models, one in …
neural networks via empirical risk minimization. In particular we consider two models, one in …
[PDF][PDF] Global Guarantees for Enforcing Deep Generative Priors by Empirical Risk
P Hand, V Voroninski - ieeexplore.ieee.org
We examine the theoretical properties of enforcing priors provided by generative deep
neural networks via empirical risk minimization. In particular we consider two models, one in …
neural networks via empirical risk minimization. In particular we consider two models, one in …