Welcome to PyGauss’s documentation!¶
As a contraction of Python and Gaussian, PyGauss is the companion package associated to the paper entitled High-dimensional Gaussian sampling: A review and a unifying approach based on a stochastic proximal point algorithm [1] which is publicy available on arXiv.
This package, written in PYTHON, aims at both reproducing the illustrations and experiments of [1] and providing the readers implementations of the Gaussian sampling approaches reviewed in [1].
 |
 |
| Precision matrix for Coepra dataset | Precision matrix for MNIST dataset |
 |
 |
| Eigenvalues of estimated covariance matrices | ESS ratio for two samplers |
Installation instructions¶
See the installation instructions on GitHub.