Bayesian experimental design (BED) provides a powerful and general framework for
optimizing the design of experiments. However, its deployment often poses substantial …

The use of Bayesian methods for data analysis is creating a revolution in fields ranging from
genetics to marketing. Yet, results of our literature review, including more than 10,000 …

Abstract Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of
machine learning systems. For instance, in autonomous driving, we would like the driving …

" A supremely enjoyable, intoxicating work."—Nature How did we come to have minds? For
centuries, poets, philosophers, psychologists, and physicists have wondered how the …

We introduce a new, efficient, principled and backpropagation-compatible algorithm for
learning a probability distribution on the weights of a neural network, called Bayes by …

Untitled Page 1 Page 2 A Student’s Guide to BAYESIAN STATISTICS Page 3 Sara Miller
McCune founded SAGE Publishing in 1965 to support the dissemination of usable knowledge …

Folklore has a critical role as a cultural transmitter, all the while being a socially accepted
medium for the expressions of culturally contradicting wishes and conducts. In this study of …

A substantial school in the philosophy of science identifies Bayesian inference with inductive
inference and even rationality as such, and seems to be strengthened by the rise and …

Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences
provides a two-semester, graduate-level introduction to basic statistical techniques that …

The optimal selection of experimental conditions is essential to maximizing the value of data
for inference and prediction, particularly in situations where experiments are time …