Direkt zu

zur Startseite

Publikationen

Preprints

Barth, A. & Stein, A.: A study of elliptic partial differential equations with jump diffusion coefficients, 2017. Zeige BibTex

Köppel, M.; Franzelin, F.; Kröker, I.; Oladyshkin, S.; Santin, G.; Wittwar, D.; Barth, A.; Haasdonk, B.; Nowak, W.; Pflüger, D. & Rohde, C.: Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario, University of Stuttgart, submitted to Comput. Geosci., 2017. Zeige BibTex Zeige Abstract

Barth, A. & Stein, A.: Approximation and simulation of infinite-dimensional Lévy processes, Arxiv, 2016. Zeige BibTex

Carlberg, K.; Brencher, L.; Haasdonk, B. & Barth, A.: Data-driven time parallelism via forecasting, 2016. Zeige BibTex

Publikationen

Barth, A. & Stüwe, T.: Weak convergence of Galerkin approximations of stochastic partial differential equations driven by additive Lévy noise, Math. Comput. Simulation, 2018, 143, 215-225. Zeige BibTex

Barth, A. & Fuchs, F. G.: Uncertainty quantification for linear hyperbolic equations with stochastic process or random field coefficients, Appl. Numer. Math., 2017, 121, 38-51. Zeige BibTex

Barth, A.; Harrach, B.; Hyvönen, N. & Mustonen, L.: Detecting stochastic inclusions in electrical impedance tomography, Inv. Prob., 2017, 33, 115012. Zeige BibTex

Köppel, M.; Kröker, I. & Rohde, C.: Intrusive Uncertainty Quantification for Hyperbolic-Elliptic Systems Governing Two-Phase Flow in Heterogeneous Porous Media, Comput. Geosci., 2017, 21, 807-832. Zeige BibTex

Barth, A.; Bürger, R.; Kröker, I. & Rohde, C.: Computational uncertainty quantification for a clarifier-thickener model with several random perturbations: A hybrid stochastic Galerkin approach, Computers & Chemical Engineering , 2016, 89, 11 - 26. Zeige BibTex

Barth, A. & Fuchs, F. G.: Uncertainty quantification for hyperbolic conservation laws with flux coefficients given by spatiotemporal random fields, SIAM J. Sci. Comput., 2016, 38, A2209-A2231. Zeige BibTex

Barth, A. & Kröker, I.: Finite volume methods for hyperbolic partial differential equations with spatial noise, Springer International Publishing, 2016, submitted. Zeige BibTex

Barth, A.; Moreno-Bromberg, S. & Reichmann, O.: A Non-stationary Model of Dividend Distribution in a Stochastic Interest-Rate Setting, Comp. Economics, 2016, 47, 447-472. Zeige BibTex

Barth, A.; Schwab, C. & Sukys, J.: Multilevel Monte Carlo simulation of statistical solutions to the Navier-Stokes equations, Monte Carlo and quasi-Monte Carlo methods, Springer, [Cham], 2016, 163, 209-227. Zeige BibTex

Kröker, I.; Nowak, W. & Rohde, C.: A stochastically and spatially adaptive parallel scheme for uncertain and nonlinear two-phase flow problems, Comput. Geosci., Springer International Publishing, 2015, 19, 269-284. Zeige BibTex

Bürger, R.; Kröker, I. & Rohde, C.: A hybrid stochastic Galerkin method for uncertainty quantification applied to a conservation law modelling a clarifier-thickener unit, ZAMM Z. Angew. Math. Mech., 2014, 94, 793-817. Zeige BibTex

Barth, A. & Benth, F. E.: The forward dynamics in energy markets -- infinite-dimensional modelling and simulation, Stochastics, 2014, 86, 932-966. Zeige BibTex

Barth, A. & Moreno-Bromberg, S.: Optimal risk and liquidity management with costly refinancing opportunities, Insurance Math. Econom., 2014, 57, 31-45. Zeige BibTex

Köppel, M.; Kröker, I. & Rohde, C.: Fuhrmann, Jürgen and Ohlberger, Mario and Rohde, Christian (Eds.), Stochastic Modeling for Heterogeneous Two-Phase Flow, Finite Volumes for Complex Applications VII-Methods and Theoretical Aspects, Springer International Publishing, 2014, 77, 353-361. Zeige BibTex

Abdulle, A.; Barth, A. & Schwab, C.: Multilevel Monte Carlo methods for stochastic elliptic multiscale PDEs, Multiscale Model. Simul., 2013, 11, 1033-1070. Zeige BibTex

Barth, A. & Lang, A.: L^p and almost sure convergence of a Milstein scheme for stochastic partial differential equations, Stochastic Process. Appl., 2013, 123, 1563-1587. Zeige BibTex

Barth, A.; Lang, A. & Schwab, C.: Multilevel Monte Carlo method for parabolic stochastic partial differential equations, BIT, 2013, 53, 3-27. Zeige BibTex

Barth, A. & Lang, A.: Multilevel Monte Carlo method with applications to stochastic partial differential equations, Int. J. Comput. Math., 2012, 89, 2479-2498. Zeige BibTex

Barth, A. & Lang, A.: Simulation of stochastic partial differential equations using finite element methods, Stochastics, 2012, 84, 217-231. Zeige BibTex

Barth, A. & Lang, A.: Milstein approximation for advection-diffusion equations driven by multiplicative noncontinuous martingale noises, Appl. Math. Optim., 2012, 66, 387-413. Zeige BibTex

Kröker, I. & Rohde, C.: Finite volume schemes for hyperbolic balance laws with multiplicative noise, Appl. Numer. Math., 2012, 62, 441-456. Zeige BibTex

Barth, A.; Benth, F. E. & Potthoff, J.: Hedging of spatial temperature risk with market-traded futures, Appl. Math. Finance, 2011, 18, 93-117. Zeige BibTex

Barth, A.; Schwab, C. & Zollinger, N.: Multi-level Monte Carlo finite element method for elliptic PDEs with stochastic coefficients, Numer. Math., 2011, 119, 123-161. Zeige BibTex

Bürger, R.; Kröker, I. & Rohde, C.: Uncertainty quantification for a clarifier-thickener model with random feed, Finite volumes for complex applications. VI. Problems & perspectives. Volume 1, 2, Springer, 2011, 4, 195-203. Zeige BibTex

Barth, A.: A finite element method for martingale-driven stochastic partial differential equations, Commun. Stoch. Anal., 2010, 4, 355-375. Zeige BibTex

Kröker, I.: Finite volume methods for conservation laws with noise, Finite volumes for complex applications V, ISTE, London, 2008, 527-534. Zeige BibTex