Our approach avoids nested simulation or simulation and regression of cashflows by learning a Gaussian metamodel for the mark-to-market cube of a derivative portfolio. We model the joint posterior of ...

In this article, we propose a generalized Gaussian process concurrent regression model for functional data, where the functional response variable has a binomial. Poisson, or other non-Gaussian ...

Gaussian process regression is a sophisticated technique that uses what is called the kernel trick to deal with complex non-linear data, and L2 regularization to avoid model overfitting where a model ...