This page covers some of the key modules in Effective Quadratures; they are split into two parts. First we have the core building blocks to assist users in creating bespoke polynomial approximations for their data.

Then we have the polynomial exploiting utilities that leverage a polynomial approximation to facilitate specific user centric tasks. These include finding dimension reducing subspaces, optimisation with polynomial surrogates, polynomial based deep learning and generating correlated sample sets.