GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation

Understand

Scientists often express their understanding of the world through a computationally demanding simulation program.

• Analyzing the posterior distribution of the parameters given observations (the inverse problem) can be extremely challenging.
• The Approximate Bayesian Computation (ABC) framework is the standard statistical tool to handle these likelihood free problems, but they require a very large number of simulations.
• In this work we develop two new ABC sampling algorithms that significantly reduce the number of simulations necessary for posterior inference.