Hyperparameter optimization for approximate bayesian computation

Approximate Bayesian computation is a popular methodology for simulation-based parameter inference in scenarios where the likelihood function is either analytically intractable or computationally infeasible. The likelihood of simulator parameters fitting given data is approximated by iteratively sim... View More