Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification

7 February 2024

Papers citing "Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification"

4 / 4 papers shown

Title
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems Katiana Kontolati Dimitrios Loukrezis D. D. Giovanis Lohit Vandanapu Michael D. Shields 47 43 0 09 Feb 2022
Heterogeneous Multi-output Gaussian Process Prediction P. Moreno-Muñoz Antonio Artés-Rodríguez Mauricio A. Alvarez 41 72 0 19 May 2018
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification Rohit Tripathy Ilias Bilionis AI4CE 58 406 0 02 Feb 2018
Polynomial meta-models with canonical low-rank approximations: numerical insights and comparison to sparse polynomial chaos expansions K. Konakli Bruno Sudret 29 113 0 23 Nov 2015