Multi-level Monte Carlo Finite Element method for elliptic PDEs with stochastic coefficients. - Andrea Barth; Christoph Schwab; Nathaniel Zollinger (Numerische Mathematik, 2011)

Multilevel Monte Carlo method with applications to stochastic partial differential equations. - Andrea Barth; Annika Lang (Int. J. Comput. Math., 2012)

Multilevel Monte Carlo Methods for Stochastic Elliptic Multiscale PDEs. - Assyr Abdulle; Andrea Barth; Christoph Schwab (Multiscale Model. Simul., 2013)

Multilevel Monte Carlo Simulation of Statistical Solutions to the Navier-Stokes Equations. - Andrea Barth; Christoph Schwab; Jonas Sukys (MCQMC, 2014)

Computational uncertainty quantification for a clarifier-thickener model with several random perturbations: A hybrid stochastic Galerkin approach. - Andrea Barth; Raimund Bürger; Ilja Kröker; Christian Rohde (Comput. Chem. Eng., 2016)

Uncertainty Quantification for Hyperbolic Conservation Laws with Flux Coefficients Given by Spatiotemporal Random Fields. - Andrea Barth; Franz G. Fuchs (SIAM J. Sci. Comput., 2016)

Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. - Markus Köppel; Fabian Franzelin; Ilja Kröker; Sergey Oladyshkin; Gabriele Santin; Dominik Wittwar; Andrea Barth; Bernard Haasdonk; Wolfgang Nowak; Dirk Pflüger; Christian Rohde (CoRR, 2018)

A Study of Elliptic Partial Differential Equations with Jump Diffusion Coefficients. - Andrea Barth; Andreas Stein (SIAM/ASA J. Uncertain. Quantification, 2018)

Weak convergence of Galerkin approximations of stochastic partial differential equations driven by additive Lévy noise. - Andrea Barth; Tobias Stüwe (Math. Comput. Simul., 2018)

A stochastic transport problem with Lévy noise: Fully discrete numerical approximation. - Andrea Barth; Andreas Stein (CoRR, 2019)

Data-Driven Time Parallelism via Forecasting. - Kevin Carlberg; Lukas Brencher; Bernard Haasdonk; Andrea Barth (SIAM J. Sci. Comput., 2019)

Subordinated Gaussian Random Fields in Elliptic Partial Differential Equations. - Andrea Barth; Robin Merkle (CoRR, 2020)

An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation. - Lukas Mehl; Cedric Beschle; Andrea Barth; Andrés Bruhn (SSVM, 2021)

Scalar conservation laws with stochastic discontinuous flux function. - Lukas Brencher; Andrea Barth (CoRR, 2021)

Multilevel Monte Carlo estimators for elliptic PDEs with Lévy-type diffusion coefficient. - Andrea Barth; Robin Merkle (CoRR, 2021)

Uncertainty visualization: Fundamentals and recent developments. - David Hägele; Christoph Schulz 001; Cedric Beschle; Hannah Booth; Miriam Butt; Andrea Barth; Oliver Deussen; Daniel Weiskopf (it Inf. Technol., 2022)

Replication Data for: An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation. - Lukas Mehl; Cedric Beschle; Andrea Barth; Andrés Bruhn (DaRUS, 2022)

Replication Data for: An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation. - Lukas Mehl; Cedric Beschle; Andrea Barth; Andrés Bruhn (DaRUS, 2022)

Quasi continuous level Monte Carlo for random elliptic PDEs. - Cedric Aaron Beschle; Andrea Barth (CoRR, 2023)

Quasi continuous level Monte Carlo. - Cedric Aaron Beschle; Andrea Barth (CoRR, 2023)

Deep learning methods for stochastic Galerkin approximations of elliptic random PDEs. - Fabio Musco; Andrea Barth (CoRR, 2024)

Stochastic transport with Lévy noise fully discrete numerical approximation. - Andreas Stein; Andrea Barth (Math. Comput. Simul., 2025)