Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

In genetic analysis, there are often competing explanations for the same data. Sophisticated mathematical models have been developed that can encapsulate these problems in terms of parameters that ...

In this talk, I will introduce a part of my research from the last 10 years (since the start of my PhD in 2013) on Bayesian ...

Regular Bayesian and frequentist approximations in statistics are studied within a unified framework. In particular it is shown how some higher-order likelihood-based approximations arise from their ...

The parametric bootstrap can be used for the efficient computation of Bayes posterior distributions. Importance sampling formulas take on an easy form relating to the deviance in exponential families ...

Nate Silver, baseball statistician turned political analyst, gained a lot of attention during the 2012 United States elections when he successfully predicted the outcome of the presidential vote in ...

Everyone who spends time with children knows how incredibly much they learn. But how can babies and young children possibly learn so much so quickly? In a recent article in Science, I describe a ...