minterpy: Multivariate Interpolation in Python

Many solutions to the computational challenges arising in the fields of computational science and engineering rely on solving interpolation tasks of highly-varying sparse and scattered data. The tasks include surrogate modeling, sparse data regression, global black-box optimization, model inference, as well as solutions for partial differential equations (PDE) on complex geometries.

Interpolation tasks in multi-dimensional space typically suffer from the curse of dimensionality in which the computational cost of interpolation scales exponentially with the number of dimensions.

The open-source Python package minterpy developed and maintained by the Hecht-Lab, CASUS, aims to lift the curse of dimensionality from a brand field of interpolation tasks arising across scientific disciplines.