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.
Publications
Talks
Scientific machine learning in astrophysics: machine learning for physics; physics for machine learning
Sep 2023
Harwell
Proximal nested sampling for high-dimensional Bayesian model selection
Jul 2023
Max-Planck-Institut fur Plasmaphysik