Generate Generative Data for a Data Source.
Generative Adversarial Networks are applied to generate generative data for a data source. In iterative training steps the distribution of generated data converges to that of the data source. Direct applications of generative data are the created functions for data classifying and missing data completion. Reference: Goodfellow et al. (2014) <arXiv:1406.2661v1>.