Ilja  Kröker
Titel
Zitiert von
Zitiert von
Jahr
Finite volume schemes for hyperbolic balance laws with multiplicative noise
I Kröker, C Rohde
Applied Numerical Mathematics 62 (4), 441-456, 2012
382012
A hybrid stochastic Galerkin method for uncertainty quantification applied to a conservation law modelling a clarifier‐thickener unit
R Buerger, I Kroeker, C Rohde
ZAMM‐Journal of Applied Mathematics and Mechanics/Zeitschrift für Angewandte …, 2014
242014
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario
M Köppel, F Franzelin, I Kröker, S Oladyshkin, G Santin, D Wittwar, ...
Computational Geosciences 23 (2), 339-354, 2019
182019
A stochastically and spatially adaptive parallel scheme for uncertain and nonlinear two-phase flow problems
I Kröker, W Nowak, C Rohde
Computational Geosciences 19 (2), 269-284, 2015
162015
Computational uncertainty quantification for a clarifier-thickener model with several random perturbations: A hybrid stochastic Galerkin approach
A Barth, R Bürger, I Kröker, C Rohde
Computers & Chemical Engineering 89, 11-26, 2016
122016
Uncertainty Quantification for a Clarifier–Thickener Model with Random Feed
R Bürger, I Kröker, C Rohde
Finite Volumes for Complex Applications VI Problems & Perspectives, 195-203, 2011
102011
Stochastic modeling for heterogeneous two-phase flow
M Köppel, I Kröker, C Rohde
Finite Volumes for Complex Applications VII-Methods and Theoretical Aspects …, 2014
92014
Intrusive uncertainty quantification for hyperbolic-elliptic systems governing two-phase flow in heterogeneous porous media
M Köppel, I Kröker, C Rohde
Computational Geosciences 21 (4), 807-832, 2017
52017
Hybrid stochastic Galerkin finite volumes for the diffusively corrected Lighthill-Whitham-Richards traffic model
R Bürger, I Kröker
International Conference on Finite Volumes for Complex Applications, 189-197, 2017
42017
Finite volume methods for conservation laws with noise
I Kröker
Finite volumes for complex applications V, 527-534, 2008
42008
Bayesian3 Active Learning for the Gaussian Process Emulator Using Information Theory
S Oladyshkin, F Mohammadi, I Kroeker, W Nowak
Entropy 22 (8), 890, 2020
22020
Computational uncertainty quantification for some strongly degenerate parabolic convection–diffusion equations
R Bürger, I Kröker
Journal of Computational and Applied Mathematics 348, 490-508, 2019
22019
A hybrid stochastic Galerkin method for uncertainty quantification applied to a conservation law modelling a clarifier-thickener unit with several random sources
A Barth, R Bürger, I Kröker, C Rohde
Preprint 34, 2015
12015
Finite Volume Methods for Hyperbolic Partial Differential Equations with Spatial Noise
A Barth, I Kröker
XVI International Conference on Hyperbolic Problems: Theory, Numerics …, 2016
2016
Stochastic models for nonlinear convection-dominated flows
I Kröker
Verlag Dr. Hut, 2013
2013
Numerical methods for stochastic conservation laws Milestone Report
I Kröker
2010
UNCERTAINTY QUANTIFICATION FOR STRONGLY DEGENERATE PARABOLIC EQUATIONS MODELLING SEDIMENTATION
R BÜRGER, I KRÖKER
NUMERICAL METHODS FOR CONSERVATION LAWS WITH MULTIPLICATIVE NOISE
I KRÖKER, C ROHDE
A HYBRID STOCHASTIC GALERKIN METHOD FOR UNCERTAINTY QUANTIFICATION APPLIED TO CLARIFER-THICKENER MODEL WITH SEVERAL RANDOM PERTURBATIONS
A BARTH, R BÜRGER, I KRÖKER, C ROHNDE
Multi-Resolution Methods for Quantifying Uncertainties in Geophysical Applications
I Kröker
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