Generative Models and Model Criticism via Optimized Maximum Mean DiscrepancyEI

    Cited by: 41|Bibtex|25|

    ICLR, Volume abs/1611.044882017,

    Abstract:

    We propose a method to optimize the representation and distinguishability of samples from two probability distributions, by maximizing the estimated power of a statistical test based on the maximum mean discrepancy (MMD). This optimized MMD is applied to the setting of unsupervised learning by generative adversarial networks (GAN), in whi...More
    Your rating :
    0

     

    Tags
    Comments