A compressed sensing approach for partial differential equations with random input data

By Lionel Mathelin, Kyle A. Gallivan. 2012

84 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computational Theory and Mathematics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/fe6492d78eea890cce9227f980a31fc9fc943e32

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Alireza Doostan
2. Jerrad Hampton
3. Liang Yan
4. Ling Guo
5. Anthony Nouy
6. Mohammad Hadigol

In Computational Theory and Mathematics

1. Jerrad Hampton
2. Liang Yan
3. Ling Guo
4. Alireza Doostan

In Statistics and Probability

1. Jerrad Hampton
2. Alireza Doostan
3. Liang Yan
4. Ling Guo
5. G. Em Karniadakis
6. Anthony Nouy
7. Mohammad Hadigol
8. Lu Lu

Citations in the corpus

• Stochastic Collocation Algorithms Using l1-Minimization for Bayesian Solution of Inverse Problems (2015, methodology): “In this work, we only use a randomly generated sample from the uniform measure; however, other choices such as Chebyshev measure [32, 45], Sobol sequence based samples [29], and deterministic methods [44] may also be used.”
• Coherence motivated sampling and convergence analysis of least squares polynomial Chaos regression (2014, methodology): “Such a sampling, dubbed here standard sampling, is commonly used in PC regression, [7, 2, 27, 28].”