They make use of an algorithm that takes advantage of “ Bayesian Program Learning,” or BPL. This is when a computer creates its own additional examples after being fed data, and then ...

Even in this day and age, computer learning is far behind the learning capability of humans. A team of researchers seek to shrink the gap, however, developing a technique called “Bayesian Program… ...

The algorithm takes advantage of a probabilistic approach the researchers call “Bayesian Program Learning,” or BPL. Essentially, the computer generates its own additional examples, and then ...

This paper proposes Bayesian nonparametric mixing for some well-known and popular models. The distribution of the observations is assumed to contain an unknown mixed effects term which includes a ...

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...

We therefore constructed Bayesian hierarchical negative binomial models to account for nuisance variables and to estimate population size of trumpeter swans using aerial survey data from all known ...