Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Entropy-Conservative Discontinuous Galerkin Methods for the Shallow Water Equations with Uncertainty

Janina Bender and Philipp Öffner
Communications on Applied Mathematics and Computation (2024)
https://doi.org/10.1007/s42967-024-00369-y

Multiresolution analysis for stochastic hyperbolic conservation laws

M Herty, A Kolb and S Müller
IMA Journal of Numerical Analysis 44 (1) 536 (2024)
https://doi.org/10.1093/imanum/drad010

Global sensitivity analysis using multi-resolution polynomial chaos expansion for coupled Stokes–Darcy flow problems

Ilja Kröker, Sergey Oladyshkin and Iryna Rybak
Computational Geosciences 27 (5) 805 (2023)
https://doi.org/10.1007/s10596-023-10236-z

Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator: concept for bias correction, assessment of surrogate reliability and its application to the carbon dioxide benchmark

Rebecca Kohlhaas, Ilja Kröker, Sergey Oladyshkin and Wolfgang Nowak
Computational Geosciences 27 (3) 369 (2023)
https://doi.org/10.1007/s10596-023-10199-1

Deep neural network expression of posterior expectations in Bayesian PDE inversion

Lukas Herrmann, Christoph Schwab and Jakob Zech
Inverse Problems 36 (12) 125011 (2020)
https://doi.org/10.1088/1361-6420/abaf64

Sensitivity Analysis of Burgers' Equation with Shocks

Qin Li, Jian-Guo Liu and Ruiwen Shu
SIAM/ASA Journal on Uncertainty Quantification 8 (4) 1493 (2020)
https://doi.org/10.1137/18M1211763

Uncertainty quantification methodology for hyperbolic systems with application to blood flow in arteries

M. Petrella, S. Tokareva and E.F. Toro
Journal of Computational Physics 386 405 (2019)
https://doi.org/10.1016/j.jcp.2019.02.013

Model order reduction for parametrized nonlinear hyperbolic problems as an application to uncertainty quantification

R. Crisovan, D. Torlo, R. Abgrall and S. Tokareva
Journal of Computational and Applied Mathematics 348 466 (2019)
https://doi.org/10.1016/j.cam.2018.09.018

Uncertainty Quantification for Hyperbolic and Kinetic Equations

Rémi Abgrall and Svetlana Tokareva
SEMA SIMAI Springer Series, Uncertainty Quantification for Hyperbolic and Kinetic Equations 14 1 (2017)
https://doi.org/10.1007/978-3-319-67110-9_1

Handbook of Numerical Methods for Hyperbolic Problems - Applied and Modern Issues

R. Abgrall and S. Mishra
Handbook of Numerical Analysis, Handbook of Numerical Methods for Hyperbolic Problems - Applied and Modern Issues 18 507 (2017)
https://doi.org/10.1016/bs.hna.2016.11.003

Uncertainty Quantification for Hyperbolic and Kinetic Equations

Siddhartha Mishra and Christoph Schwab
SEMA SIMAI Springer Series, Uncertainty Quantification for Hyperbolic and Kinetic Equations 14 231 (2017)
https://doi.org/10.1007/978-3-319-67110-9_7

Numerical Solution of Scalar Conservation Laws with Random Flux Functions

Siddhartha Mishra, Nils Henrik Risebro, Christoph Schwab and Svetlana Tokareva
SIAM/ASA Journal on Uncertainty Quantification 4 (1) 552 (2016)
https://doi.org/10.1137/120896967

High Order Nonlinear Numerical Schemes for Evolutionary PDEs

Svetlana Tokareva, Christoph Schwab and Siddhartha Mishra
Lecture Notes in Computational Science and Engineering, High Order Nonlinear Numerical Schemes for Evolutionary PDEs 99 109 (2014)
https://doi.org/10.1007/978-3-319-05455-1_7

Uncertainty Quantification in Computational Fluid Dynamics

Siddhartha Mishra, Christoph Schwab and Jonas Šukys
Lecture Notes in Computational Science and Engineering, Uncertainty Quantification in Computational Fluid Dynamics 92 225 (2013)
https://doi.org/10.1007/978-3-319-00885-1_6