The ability to express the joint probability in this way (exploiting conditional independencies) provides a concise representation in terms of simple component distributions (factors), thereby ...

H. K. ALEXANDER, CONDITIONAL DISTRIBUTIONS AND WAITING TIMES IN MULTITYPE BRANCHING PROCESSES, Advances in Applied Probability, Vol. 45, No. 3 (SEPTEMBER 2013), pp. 692-718 ...

The course covers the probability and distribution theory needed for advanced courses in statistics and econometrics.: Topics covered: Probability. Conditional probability and independence. Random ...

To learn the complex conditional probability distribution of the data, the researchers used a special type of deep-learning model called a normalizing flow, which is particularly effective at ...

The course covers the probability, distribution theory and statistical inference needed for advanced courses in statistics and econometrics. Michaelmas term: Probability.

We investigate the almost sure convergence of a kernel-type conditional empirical distribution function both in sup-norm and weighted sup-norms. As an application we get a strong law for the ...

Probability theorem gets quantum makeoverWhat would Thomas Bayes think? In 1763, he proposed a new approach to calculate ...

An international team of researchers have successfully derived a quantum version of Bayes’ rule, a cornerstone of probability theory ...