Automatic Posterior Transformation for Likelihood-Free Inference

https://arxiv.org/abs/1905.07488

Sequential neural posterior estimation with arbitrary, dynamically updated proposals and normalizing-flow density estimators; works on high-dimensional time series and images.

Simulation-based inference for calibrating simulators