Generative Nested Sampling of Atomistic Thermodynamic Landscapes
This work introduces NS-Flows: a single conditional normalizing flow, conditioned on the NS energy bound and trained on a sliding window of recent live sets, that replaces MCMC by direct parallel draws corrected by importance-weighted rejection resampling, allowing flow training without structured priors or a pre-exist...