PyVBMC: Efficient Bayesian inference in Python
This upload archives the v1.0.1 release of PyVBMC, as prepared for submission to the Journal of Open Source Software. PyVBMC is a Python implementation of the Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference for *black-box* computational models. VBMC is an approximate inference method designed for efficient parameter estimation and model assessment when model evaluations are mildly-to-very expensive (e.g., a second or more) and/or noisy.