Working With Jensen Shannon Divergence Part3(machine Learning)

Researchers have recently proposed a new method for likelihood-free inference for simulator-based statistical models. This method offers a rapid alternative to more computationally intensive methods, and can be used in applications with big data. The new method uses asymptotic properties of the Jensen-Shannon divergence to enable estimation, hypothesis testing and construction of confidence intervals for model parameters.