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Found 2 papers, 1 papers with code
Adversarial Estimators
As a corollary, we obtain the normality of neural-net M-estimators, overcoming technical issues previously identified by the literature.
Using Wasserstein Generative Adversial Networks for the Design of Monte Carlo Simulations
We discuss the use of Wasserstein Generative Adversarial Networks (WGANs) as a method for systematically generating artificial data that mimic closely any given real data set without the researcher having many degrees of freedom.
Econometrics Methodology
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