Researchers have introduced new dimension and model reduction methods that extend optimal Bayesian inference to problems with ...

Researchers have developed an importance-sampling-based black box variational inference algorithm that reuses earlier ...

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

This paper develops new econometric methods to infer hospital quality in a model with discrete dependent variables and non-random selection. Mortality rates in patient discharge records are widely ...

Probabilities that created rebels, hidden signatures, unrecorded drivers, inbox gatekeepers, and those who predict the ...

Can mass shootings be forecasted? Mohammad R.K. Mofrad and colleagues constructed an agent-based model of mass shootings within a Bayesian inference ...

Large language models (LLMs), the artificial intelligence (AI) systems underpinning the functioning of ChatGPT and other ...