neural posterior estimation for population genetics

With Jiseon Min, Nathaniel Pope, and Andrew Kern we worked on a workflow that enables simulation based machine learning inference for population genetics. popgen-npe infers population genetic parameters using neural posterior estimation, enabling likelihood-free analysis of complex evolutionary models in a Bayesian framework.

If you want to try it go to github.