Empirical Bayesian methods occupy a unique position at the interface of frequentist and Bayesian paradigms by estimating prior distributions directly from observed data. This approach preserves the ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

The demand for uncertainty quantification in modern sequence modeling tasks has prompted researchers to explore deep integration between Bayesian inference and Transformer architectures, but existing ...