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 ...
This short course will provide an overview of non-parametric statistical techniques. The course will first describe what non-parametric statistics are, when they should be used, and their advantages ...
Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...
Bayesian nonparametric modelling and inference encompasses a class of probabilistic methods that dispense with fixedâdimensional parameter spaces in favour of priors defined on function or measure ...
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