Flowmc: normalizing flow enhanced sampling package for probabilistic inference in jax

HIGHLIGHTS

• who: Kaze W. K. Wong and colleagues from the Center for, Palaiseau, France have published the paper: flowMC: Normalizing flow enhanced sampling package for probabilistic inference in JAX, in the Journal: (JOURNAL) of 10/Nov/2022
• what: The authors provide a simple black-box interface for the users who want to use flowMC by its default parameters, as well as an extensive guide explaining trade-offs while tuning the sampler parameters. While the authors provide a high-level interface suitable for most practitioners, the code is also designed to be extensible.

SUMMARY

 



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