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 ...
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 ...
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, ...
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 ...
The Stiefel manifold Vp,d is the space of all d × p orthonormal matrices, with the d−1 hypersphere and the space of all orthogonal matrices constituting special cases. In modeling data lying on the ...
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