ProxNest: Proximal nested sampling for high-dimensional Bayesian model selection

ProxNest is an open source, well tested and documented Python implementation of the proximal nested sampling algorithm, which is uniquely suited for sampling from very high-dimensional posteriors that are log-concave and potentially not smooth (e.g. Laplace priors). This is achieved by exploiting tools from proximal calculus and Moreau-Yosida regularisation to efficiently sample from the prior subject to the hard likelihood constraint.