This Primer examines Skilling’s nested sampling algorithm for Bayesian inference and, more broadly, multidimensional integration. The principles of nested sampling are summarize ...

Bayesian inference offers a principled mechanism for updating beliefs by combining prior distributions with observed data via Bayes’s theorem. Central to this approach is the specification of a ...

Google Researchers have proposed a training method that teaches large language models to approximate Bayesian reasoning by learning from the predictions of an optimal Bayesian system. The approach ...