Corpus ID: 224722235

Statistical guarantees for generative models without domination.

@article{Schreuder2020StatisticalGF,
  title={Statistical guarantees for generative models without domination.},
  author={Nicolas Schreuder and Victor-Emmanuel Brunel and A. Dalalyan},
  journal={arXiv: Statistics Theory},
  year={2020}
}

Nicolas Schreuder, Victor-Emmanuel Brunel, A. Dalalyan

Published 2020

Mathematics

arXiv: Statistics Theory

In this paper, we introduce a convenient framework for studying (adversarial) generative models from a statistical perspective. It consists in modeling the generative device as a smooth transformation of the unit hypercube of a dimension that is much smaller than that of the ambient space and measuring the quality of the generative model by means of an integral probability metric. In the particular case of integral probability metric defined through a smoothness class, we establish a risk bound… CONTINUE READING

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