The package contains code to interpolate a function in 2D using Sparse Grids.
Solving PDEs in higher dimensions poses a computational challenge due to the curse of dimensionality. Sparse grids [1] present an alternative in overcoming the curse of dimensionality. The method is based on a hierarchical basis, which is a discrete representation of a continuous function. A sparse grid is then generated by a sparse tensor product construction, thus reducing the total number of basis functions we need to calculate while only slightly reducing the accuracy.
[1] Garcke J. (2012) Sparse Grids in a Nutshell. In: Garcke J., Griebel M. (eds) Sparse Grids and Applications. Lecture Notes in Computational Science and Engineering, vol 88. Springer, Berlin, Heidelberg.