The Sparse Grids Matlab kit--a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification
C Piazzola, L Tamellini - arXiv preprint arXiv:2203.09314, 2022 - arxiv.org
The Sparse Grids Matlab Kit provides a Matlab implementation of sparse grids, and can be
used for approximating high-dimensional functions and, in particular, for surrogate-model …
used for approximating high-dimensional functions and, in particular, for surrogate-model …
Algorithm 1040: The Sparse Grids Matlab Kit-a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification
C Piazzola, L Tamellini - ACM Transactions on Mathematical Software, 2024 - dl.acm.org
The Sparse Grids Matlab Kit provides a Matlab implementation of sparse grids, and can be
used for approximating high-dimensional functions and, in particular, for surrogate-model …
used for approximating high-dimensional functions and, in particular, for surrogate-model …
[HTML][HTML] Lowering the Entry Barrier to Uncertainty Quantification
L Seelinger, A Reinarz - Collections, 2023 - siam.org
Uncertainties in data are omnipresent, encompassing factors such as measurement errors,
incomplete information, and random processes. The goal of uncertainty quantification (UQ) …
incomplete information, and random processes. The goal of uncertainty quantification (UQ) …