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 ...

Our recently developed fully robust Bayesian semiparametric mixed-effect model for high-dimensional longitudinal studies with heterogeneous observations can be implemented through this package. This ...

Abstract: Predicting transformer degradation is essential for ensuring the reliability and efficiency of power systems. This study explores Bayesian inference as a robust alternative to traditional ...

Dormancy is a widespread bet-hedging strategy across taxa, enabling organisms to survive natural and anthropogenic disturbances. It fundamentally alters eco-evolutionary processes, including ...

Perceptual judgments of ambiguous stimuli are often biased by prior expectations. These biases may offer a window into the neural computations that give rise to perceptual interpretations of the ...

Bayesian inference offers a coherent framework for updating beliefs about unknown quantities in light of observed data. At its core lies Bayes’ theorem, which combines a prior distribution, ...

1 Department of Mathematics and Statistics, Université de Moncton, New Brunswick, Canada. 2 Faculty of Mathematics and Computer Science, Hochiminh University of Science, Ho Chi Minh, Vietnam.

ABSTRACT: This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, ...