The Optimality of Antihypertensive Drug Reduction: Re-examining Prior Probabilities via Bayesian Inference

The clinical common sense that "if you can reduce medication, that is the correct answer" does not hold true for individual patients. Unless you update the "prior probability" you believe in with ...

Bayesian Inference and Deep Learning: Theory and Practice of Generative Models

IntroductionPurpose of this bookThis book depicts the path from Bayesian inference to deep learning as a single long-form technical volume. There is one central theme: how can we handle uncertainty in ...
Phys.org

Researchers develop Bayesian inference for hidden dependence structures in multi-group high-dimensional data

In today's scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly increasing ...
Nature

Inference in Bayesian networks

How does one model a simple cell-signaling pathway? Consider a simple example consisting of a stimulant, an extracellular signal, an inhibitor of the signal, a G protein–coupled receptor, a G protein ...
San Francisco Fed

Bayesian Inference for Hospital Quality in a Selection Model

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 ...

Mass shooting model identifies firearm availability as key limit on risk

Can mass shootings be forecast? Mohammad R.K. Mofrad and colleagues constructed an agent-based model of mass shootings within ...
technologynetworks

An Introduction to Bayesian Statistics

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 ...
Ars Technica

Bayes’ theorem: Its triumphs and discontents

Nate Silver, baseball statistician turned political analyst, gained a lot of attention during the 2012 United States elections when he successfully predicted the outcome of the presidential vote in ...