Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 181, No. 3 (2018), pp. 635-647 (13 pages) Statistical agencies are increasingly adopting synthetic data methods for ...

Bayesian nonparametric modelling and inference encompasses a class of probabilistic methods that dispense with fixed‐dimensional parameter spaces in favour of priors defined on function or measure ...

Bayesian inference in nonparametric settings offers a coherent framework for learning complex, infinite-dimensional objects, such as probability densities, regression functions or solutions to inverse ...

In the Big Data era, many scientific and engineering domains are producing massive data streams, with petabyte and exabyte scales becoming increasingly common. Besides the explosive growth in volume, ...

The Annals of Statistics, Vol. 48, No. 4 (August 2020), pp. 2277-2302 (26 pages) Motivated by problems in data clustering, we establish general conditions under which families of nonparametric mixture ...

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