Machine learning and artificial intelligence wouldn't be possible without the statistical models that underpin their analytic ...

It relies on probability to assess how new evidence affects a hypothesis.,Bayesian methods are widely used in fields from ...

Hostile environment policy mental health - Briony Tatem on the effect of immigration policy reform on mental health in people ...

To address these challenges, a Bayesian optimization framework was proposed herein ... The Jackknife and Bootstrap methods are used to estimate variance and calculate the acquisition function.

Kirk, C, Langan-Evans, C, Clark, DR and Morton, JP (2023) The Relationships Between External and Internal Training Loads in Mixed Martial Arts. International Journal of Sports Physiology and ...

If we want to identify nations efficiently developing their sporting talent, we need to measure more than just total Olympic ...

The following is a summary of “Causality between autoimmune diseases and schizophrenia: a bidirectional Mendelian ...

Methods: This study used data collected from US adults (aged ... or a given outcome of interest. Bayesian networks (BNs) mapping out the relationship between risk factors and each outcome were ...

While Bayesian deep learning methods have shown promise for uncertainty estimation, most research has focused on single-label tasks. Researchers from the Institute of Automation, Chinese Academy of ...

Our advanced computing capacity and world-leading informatics enable us to harness data and computational methods across ...

In this paper, we propose a fast sparse Bayesian learning method with truncated singular value (FSBL-T) to quickly improve the azimuth resolution. Firstly, we truncate the small singular value of the ...