Description

This Python module implements existing approaches, directly derived from numerical linear algebra, to sample from high-dimensional Gaussian probability distributions. The latter can be divided into three groups, namely:

• factorization approaches (e.g., Cholesky or square-root samplers),
• square-root approximation approaches (e.g., Chebyshev and Lanczos samplers),
• conjugate-gradient samplers.

For more details, we refer the interested reader to Section 3 of the companion paper.