Instead of bending a training-centric design, we must start with a clean sheet and apply a new set of rules tailored to ...

In the predawn hours of August 19, 2024, bolts of lightning began to fork through the purple-black clouds above the Mediterranean. From the rail of a 184-foot vessel, a 22-year-old named Matthew ...

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

Objectives: We aimed to clarify the influence of facial expressions on providing early recognition and diagnosis of Parkinson’s disease (PD). Methods: We included 18 people with PD and 18 controls.

Frequentist methods, without the coherence guarantees of fully Bayesian methods, are known to yield self-contradictory inferences in certain settings. The framework introduced in this paper provides a ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

ABSTRACT: Geographical variations in all-cause mortality rates may be influenced by residents’ place of residence and the time period under study. Understanding these variations is essential for ...

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, ...

Recursive Bayesian inference, in which posterior beliefs are updated in light of accumulating data, is a tool for implementing Bayesian models in applications with streaming and/or very large data ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...