Discrepancy-based inference for intractable generative models using Quasi-Monte Carlo
Discrepancy-based inference for intractable generative models using Quasi-Monte Carlo
Intractable generative models, or simulators, are models for which the likelihood is unavailable but sampling is possible. Most approaches to parameter inference in this setting require the computation of some discrepancy between the data and the generative model. This is for example the case for minimum distance estimation and approximate …