This book's organization : read me first! -- Introduction : models we believe in -- What is this stuff called probability? -- Bayes' rule -- Inferring a binomial proportion via exact mathematical ...

We will keep our notes and code on dealing with censored variables in Bayesian models in this repo. My initial idea for this is that we can basically treat each worked out example or section that we ...

Abstract: Increasingly, for many application areas, it is becoming important to include elements of nonlinearity and non-Gaussianity in order to model accurately the underlying dynamics of a physical ...

Abstract: Bayesian optimization (BO) is a framework for global optimization of expensive-to-evaluate objective functions. Classical BO methods assume that the objective function is a black box.

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

Pupil dilation provides a physiological readout of information gain during the brain's internal process of belief updating in the context of associative learning.

Bayesian Optimization in Action teaches you how to build Bayesian optimization systems from the ground up. This book transforms state-of-the-art research into usable techniques that you can easily put ...

We use Bayesian meta-analysis methods to estimate the impact of unconditional cash transfers (UCTs). Aggregating evidence from 115 studies of 72 UCT programs in middle and low income countries, we ...

Experiments on neutrino oscillations have confirmed that neutrinos have small, but non-zero masses, and that the interacting neutrino states do not have definite masses, but are mixtures of such ...