Skewed distribution models constitute a fundamental extension of classical symmetric families, enabling statisticians to describe asymmetry and heavy-tailed behaviour observed across diverse empirical ...

Hidden Markov models (HMMs) provide a powerful framework for inferring unobserved processes that evolve over time or space by linking an underlying Markovian state sequence to observed data via ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Model inversion and membership inference attacks create unique risks to organizations that are allowing artificial intelligences to be trained using their data. Companies may wish to begin to evaluate ...