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2020 – today
- 2025
[j51]Linus Seelinger
, Anne Reinarz, Mikkel Bue Lykkegaard, Robert Akers, Amal Mohammed A. Alghamdi, David Aristoff, Wolfgang Bangerth, Jean Bénézech, Matteo Diez, Kurt Frey, John D. Jakeman, Jakob Sauer Jørgensen, Ki-Tae Kim, Benjamin M. Kent, Massimiliano Martinelli, Matthew D. Parno, Riccardo Pellegrini, Noemi Petra, Nicolai André Brogaard Riis, Katherine Rosenfeld, Andrea Serani, Lorenzo Tamellini, Umberto Villa, Tim J. Dodwell, Robert Scheichl:
Democratizing uncertainty quantification. J. Comput. Phys. 521: 113542 (2025)- 2024
- [j50]Jean Bénézech, Linus Seelinger, Peter Bastian, Richard Butler, Timothy Dodwell, Chupeng Ma, Robert Scheichl:
Scalable multiscale-spectral GFEM with an application to composite aero-structures. J. Comput. Phys. 508: 113013 (2024) - [j49]Tiangang Cui, Hans De Sterck, Alexander D. Gilbert, Stanislav Polishchuk, Robert Scheichl:
Multilevel Monte Carlo Methods for Stochastic Convection-Diffusion Eigenvalue Problems. J. Sci. Comput. 99(3): 77 (2024) - [j48]Daniel Elfverson, Robert Scheichl, Simon Weissmann, Francisco Alejandro Diaz De la O:
Adaptive Multilevel Subset Simulation with Selective Refinement. SIAM/ASA J. Uncertain. Quantification 12(3): 932-963 (2024) - [j47]Tiangang Cui, Sergey Dolgov, Robert Scheichl:
Deep Importance Sampling Using Tensor Trains with Application to a Priori and a Posteriori Rare Events. SIAM J. Sci. Comput. 46(1): 1- (2024) - [i33]Karina Koval, Roland Herzog, Robert Scheichl:
Tractable Optimal Experimental Design using Transport Maps. CoRR abs/2401.07971 (2024) - [i32]Linus Seelinger, Anne Reinarz, Mikkel Bue Lykkegaard, Amal Mohammed A. Alghamdi, David Aristoff, Wolfgang Bangerth, Jean Bénézech, Matteo Diez, Kurt Frey, John D. Jakeman, Jakob Sauer Jørgensen, Ki-Tae Kim, Massimiliano Martinelli, Matthew D. Parno, Riccardo Pellegrini, Noemi Petra, Nicolai André Brogaard Riis, Katherine Rosenfeld, Andrea Serani, Lorenzo Tamellini, Umberto Villa, Tim J. Dodwell, Robert Scheichl:
Democratizing Uncertainty Quantification. CoRR abs/2402.13768 (2024) - [i31]Christian Alber, Chupeng Ma, Robert Scheichl:
A Mixed Multiscale Spectral Generalized Finite Element Method. CoRR abs/2403.16714 (2024) - [i30]Yoshihito Kazashi, Eike H. Müller, Robert Scheichl:
Multigrid Monte Carlo Revisited: Theory and Bayesian Inference. CoRR abs/2407.12149 (2024) - [i29]Arne Strehlow, Chupeng Ma, Robert Scheichl:
Fast-convergent two-level restricted additive Schwarz methods based on optimal local approximation spaces. CoRR abs/2408.16282 (2024) - [i28]Chupeng Ma, Christian Alber, Robert Scheichl:
Two-level Restricted Additive Schwarz preconditioner based on Multiscale Spectral Generalized FEM for Heterogeneous Helmholtz Problems. CoRR abs/2409.06533 (2024) - 2023
- [j46]Mikkel Bue Lykkegaard, Tim J. Dodwell, Colin Fox, G. Mingas, Robert Scheichl:
Multilevel Delayed Acceptance MCMC. SIAM/ASA J. Uncertain. Quantification 11(1): 1-30 (2023) - [j45]Chupeng Ma, Christian Alber, Robert Scheichl:
Wavenumber Explicit Convergence of a Multiscale Generalized Finite Element Method for Heterogeneous Helmholtz Problems. SIAM J. Numer. Anal. 61(3): 1546-1584 (2023) - [j44]Peter Bastian, Robert Scheichl, Linus Seelinger, Arne Strehlow:
Multilevel Spectral Domain Decomposition. SIAM J. Sci. Comput. 45(3): S1-S26 (2023) - [j43]Alexey Kazarnikov, Robert Scheichl, Heikki Haario, Anna K. Marciniak-Czochra:
A Bayesian Approach to Modeling Biological Pattern Formation with Limited Data. SIAM J. Sci. Comput. 45(5): 673- (2023) - [i27]Tiangang Cui, Hans De Sterck, Alexander D. Gilbert, Stanislav Polishchuk, Robert Scheichl:
Multilevel Monte Carlo methods for stochastic convection-diffusion eigenvalue problems. CoRR abs/2303.03673 (2023) - [i26]Linus Seelinger, Anne Reinarz, Jean Bénézech, Mikkel Bue Lykkegaard, Lorenzo Tamellini, Robert Scheichl:
Lowering the Entry Bar to HPC-Scale Uncertainty Quantification. CoRR abs/2304.14087 (2023) - [i25]Nils Friess, Alexander D. Gilbert, Robert Scheichl:
A complex-projected Rayleigh quotient iteration for targeting interior eigenvalues. CoRR abs/2312.02847 (2023) - 2022
- [j42]Paul B. Rohrbach, Sergey Dolgov, Lars Grasedyck, Robert Scheichl:
Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format. SIAM/ASA J. Uncertain. Quantification 10(1): 1191-1224 (2022) - [j41]Chupeng Ma, Robert Scheichl:
Error estimates for discrete generalized FEMs with locally optimal spectral approximations. Math. Comput. 91(338): 2539-2569 (2022) - [j40]Chupeng Ma, Robert Scheichl, Tim J. Dodwell:
Novel Design and Analysis of Generalized Finite Element Methods Based on Locally Optimal Spectral Approximations. SIAM J. Numer. Anal. 60(1): 244-273 (2022) - [i24]Daniel Elfverson, Robert Scheichl, Simon Weissmann, Francisco Alejandro DiazDelaO:
Adaptive multilevel subset simulation with selective refinement. CoRR abs/2208.05392 (2022) - [i23]Tiangang Cui, Sergey Dolgov, Robert Scheichl:
Deep importance sampling using tensor-trains with application to a priori and a posteriori rare event estimation. CoRR abs/2209.01941 (2022) - [i22]Jean Bénézech, Linus Seelinger, Peter Bastian, Richard Butler, Timothy Dodwell, Chupeng Ma, Robert Scheichl:
Scalable multiscale-spectral GFEM for composite aero-structures. CoRR abs/2211.13893 (2022) - 2021
- [c5]Jakob Kruse, Gianluca Detommaso, Ullrich Köthe, Robert Scheichl:
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference. AAAI 2021: 8191-8199 - [c4]Linus Seelinger, Anne Reinarz, Leonhard Rannabauer, Michael Bader, Peter Bastian, Robert Scheichl:
High performance uncertainty quantification with parallelized multilevel Markov chain Monte Carlo. SC 2021: 75 - [i21]Alexander D. Gilbert, Robert Scheichl:
Multilevel quasi-Monte Carlo for random elliptic eigenvalue problems II: Efficient algorithms and numerical results. CoRR abs/2103.03407 (2021) - [i20]Chupeng Ma, Robert Scheichl, Tim J. Dodwell:
Novel design and analysis of generalized FE methods based on locally optimal spectral approximations. CoRR abs/2103.09545 (2021) - [i19]Niall Bootland, Victorita Dolean, Ivan G. Graham, Chupeng Ma, Robert Scheichl:
GenEO coarse spaces for heterogeneous indefinite elliptic problems. CoRR abs/2103.16703 (2021) - [i18]Peter Bastian, Robert Scheichl, Linus Seelinger, Arne Strehlow:
Multilevel Spectral Domain Decomposition. CoRR abs/2106.06404 (2021) - [i17]Chupeng Ma, Robert Scheichl:
Error estimates for fully discrete generalized FEMs with locally optimal spectral approximations. CoRR abs/2107.09988 (2021) - [i16]Linus Seelinger, Anne Reinarz, Leonhard Rannabauer, Michael Bader, Peter Bastian, Robert Scheichl:
High Performance Uncertainty Quantification with Parallelized Multilevel Markov Chain Monte Carlo. CoRR abs/2107.14552 (2021) - [i15]Niall Bootland, Victorita Dolean, Ivan G. Graham, Chupeng Ma, Robert Scheichl:
Overlapping Schwarz methods with GenEO coarse spaces for indefinite and non-self-adjoint problems. CoRR abs/2110.13537 (2021) - [i14]Chupeng Ma, Christian Alber, Robert Scheichl:
Wavenumber explicit convergence of a multiscale GFEM for heterogeneous Helmholtz problems. CoRR abs/2112.10544 (2021) - 2020
- [j39]Richard Butler, Tim J. Dodwell, Anne Reinarz, A. Sandhu, Robert Scheichl, Linus Seelinger:
High-performance dune modules for solving large-scale, strongly anisotropic elliptic problems with applications to aerospace composites. Comput. Phys. Commun. 249: 106997 (2020) - [j38]Jens Lang, Robert Scheichl, David J. Silvester:
A fully adaptive multilevel stochastic collocation strategy for solving elliptic PDEs with random data. J. Comput. Phys. 419: 109692 (2020) - [j37]Sergey Dolgov, Karim Anaya-Izquierdo, Colin Fox, Robert Scheichl:
Approximation and sampling of multivariate probability distributions in the tensor train decomposition. Stat. Comput. 30(3): 603-625 (2020) - [j36]Markus Bachmayr, Ivan G. Graham, Van Kien Nguyen, Robert Scheichl:
Unified Analysis of Periodization-Based Sampling Methods for Matérn Covariances. SIAM J. Numer. Anal. 58(5): 2953-2980 (2020) - [i13]Paul B. Rohrbach, Sergey Dolgov, Lars Grasedyck, Robert Scheichl:
Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format. CoRR abs/2001.08187 (2020) - [i12]Karl Jansen, Eike Hermann Müller, Robert Scheichl:
Multilevel Monte Carlo for quantum mechanics on a lattice. CoRR abs/2008.03090 (2020) - [i11]Alexander D. Gilbert, Robert Scheichl:
Multilevel quasi-Monte Carlo for random elliptic eigenvalue problems I: Regularity and error analysis. CoRR abs/2010.01044 (2020)
2010 – 2019
- 2019
- [j35]Gianluca Detommaso, Tim J. Dodwell, Robert Scheichl:
Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies. SIAM/ASA J. Uncertain. Quantification 7(1): 93-116 (2019) - [j34]Sergey Dolgov, Robert Scheichl:
A Hybrid Alternating Least Squares-TT-Cross Algorithm for Parametric PDEs. SIAM/ASA J. Uncertain. Quantification 7(1): 260-291 (2019) - [j33]Tim J. Dodwell, Christian Ketelsen, Robert Scheichl, Aretha L. Teckentrup:
ERRATUM: A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow. SIAM/ASA J. Uncertain. Quantification 7(4): 1398-1399 (2019) - [j32]Alexander D. Gilbert, Ivan G. Graham, Frances Y. Kuo, Robert Scheichl, Ian H. Sloan:
Analysis of quasi-Monte Carlo methods for elliptic eigenvalue problems with stochastic coefficients. Numerische Mathematik 142(4): 863-915 (2019) - [j31]Tim J. Dodwell, Christian Ketelsen, Robert Scheichl, Aretha L. Teckentrup:
Multilevel Markov Chain Monte Carlo. SIAM Rev. 61(3): 509-545 (2019) - [c3]Linus Seelinger, Anne Reinarz, Robert Scheichl:
A High-Performance Implementation of a Robust Preconditioner for Heterogeneous Problems. PPAM (1) 2019: 117-128 - [i10]Gianluca Detommaso, Jakob Kruse, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Robert Scheichl:
HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference. CoRR abs/1905.10687 (2019) - [i9]Linus Seelinger, Anne Reinarz, Robert Scheichl:
A High-Performance Implementation of a Robust Preconditioner for Heterogeneous Problems. CoRR abs/1906.10944 (2019) - [i8]Tim J. Dodwell, S. Kinston, Richard Butler, Raphael T. Haftka, Nam H. Kim, Robert Scheichl:
Multilevel Monte Carlo Simulations of Composite Structures with Uncertain Manufacturing Defects. CoRR abs/1907.10271 (2019) - [i7]Tiangang Cui, Gianluca Detommaso, Robert Scheichl:
Multilevel Dimension-Independent Likelihood-Informed MCMC for Large-Scale Inverse Problems. CoRR abs/1910.12431 (2019) - 2018
- [j30]Grigoris Katsiolides, Eike Hermann Müller, Robert Scheichl, Tony Shardlow, Michael B. Giles, David J. Thomson:
Multilevel Monte Carlo and improved timestepping methods in atmospheric dispersion modelling. J. Comput. Phys. 354: 320-343 (2018) - [j29]Ivan G. Graham, Frances Y. Kuo, Dirk Nuyens, Robert Scheichl, Ian H. Sloan:
Circulant embedding with QMC: analysis for elliptic PDE with lognormal coefficients. Numerische Mathematik 140(2): 479-511 (2018) - [j28]Ivan G. Graham, Frances Y. Kuo, Dirk Nuyens, Robert Scheichl, Ian H. Sloan:
Analysis of Circulant Embedding Methods for Sampling Stationary Random Fields. SIAM J. Numer. Anal. 56(3): 1871-1895 (2018) - [c2]Gianluca Detommaso, Tiangang Cui, Youssef M. Marzouk, Alessio Spantini, Robert Scheichl:
A Stein variational Newton method. NeurIPS 2018: 9187-9197 - [i6]Gianluca Detommaso, Tiangang Cui, Youssef M. Marzouk, Robert Scheichl, Alessio Spantini:
A Stein variational Newton method. CoRR abs/1806.03085 (2018) - 2017
- [j27]Robert Scheichl, Andrew M. Stuart, Aretha L. Teckentrup:
Quasi-Monte Carlo and Multilevel Monte Carlo Methods for Computing Posterior Expectations in Elliptic Inverse Problems. SIAM/ASA J. Uncertain. Quantification 5(1): 493-518 (2017) - [j26]Frances Y. Kuo, Robert Scheichl, Christoph Schwab, Ian H. Sloan, Elisabeth Ullmann:
Multilevel Quasi-Monte Carlo methods for lognormal diffusion problems. Math. Comput. 86(308): 2827-2860 (2017) - [j25]Daniel Drzisga, Björn Gmeiner, Ulrich Rüde, Robert Scheichl, Barbara I. Wohlmuth:
Scheduling Massively Parallel Multigrid for Multilevel Monte Carlo Methods. SIAM J. Sci. Comput. 39(5) (2017) - 2016
- [j24]Daniel Peterseim, Robert Scheichl:
Robust Numerical Upscaling of Elliptic Multiscale Problems at High Contrast. Comput. Methods Appl. Math. 16(4): 579-603 (2016) - [j23]Albert Ferreiro-Castilla, Andreas E. Kyprianou, Robert Scheichl:
An Euler-Poisson scheme for Lévy driven stochastic differential equations. J. Appl. Probab. 53(1): 262-278 (2016) - [i5]Björn Gmeiner, Daniel Drzisga, Ulrich Rüde, Robert Scheichl, Barbara I. Wohlmuth:
Scheduling massively parallel multigrid for multilevel Monte Carlo methods. CoRR abs/1607.03252 (2016) - 2015
- [j22]Tim J. Dodwell, Christian Ketelsen, Robert Scheichl, Aretha L. Teckentrup:
A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow. SIAM/ASA J. Uncertain. Quantification 3(1): 1075-1108 (2015) - [j21]Ivan G. Graham, Frances Y. Kuo, James A. Nichols, Robert Scheichl, Christoph Schwab, Ian H. Sloan:
Quasi-Monte Carlo finite element methods for elliptic PDEs with lognormal random coefficients. Numerische Mathematik 131(2): 329-368 (2015) - [j20]Eike Hermann Müller, Robert Scheichl, Eero Vainikko:
Petascale solvers for anisotropic PDEs in atmospheric modelling on GPU clusters. Parallel Comput. 50: 53-69 (2015) - [j19]Sébastien Loisel, Hieu Nguyen, Robert Scheichl:
Optimized Schwarz and 2-Lagrange Multiplier Methods for Multiscale Elliptic PDEs. SIAM J. Sci. Comput. 37(6) (2015) - 2014
- [j18]Nicole Spillane, Victorita Dolean, Patrice Hauret, Frédéric Nataf, Clemens Pechstein, Robert Scheichl:
Abstract robust coarse spaces for systems of PDEs via generalized eigenproblems in the overlaps. Numerische Mathematik 126(4): 741-770 (2014) - [i4]Eike Hermann Müller, Robert Scheichl, Benson Muite, Eero Vainikko:
Petascale elliptic solvers for anisotropic PDEs on GPU clusters. CoRR abs/1402.3545 (2014) - [i3]Andreas Dedner, Eike Hermann Müller, Robert Scheichl:
Efficient Multigrid Preconditioners for Anisotropic Problems in Geophysical Modelling. CoRR abs/1408.2981 (2014) - 2013
- [j17]Eike Hermann Müller, Xu Guo, Robert Scheichl, Sinan Shi:
Matrix-free GPU implementation of a preconditioned conjugate gradient solver for anisotropic elliptic PDEs. Comput. Vis. Sci. 16(2): 41-58 (2013) - [j16]Aretha L. Teckentrup, Robert Scheichl, Michael B. Giles, Elisabeth Ullmann:
Further analysis of multilevel Monte Carlo methods for elliptic PDEs with random coefficients. Numerische Mathematik 125(3): 569-600 (2013) - [j15]Julia Charrier, Robert Scheichl, Aretha L. Teckentrup:
Finite Element Error Analysis of Elliptic PDEs with Random Coefficients and Its Application to Multilevel Monte Carlo Methods. SIAM J. Numer. Anal. 51(1): 322-352 (2013) - [p3]Robert Scheichl:
Robust Coarsening in Multiscale PDEs. Domain Decomposition Methods in Science and Engineering XX 2013: 51-62 - [p2]Victorita Dolean, Frédéric Nataf, Robert Scheichl, Nicole Spillane:
A Two-Level Schwarz Preconditioner for Heterogeneous Problems. Domain Decomposition Methods in Science and Engineering XX 2013: 87-94 - [p1]Clemens Pechstein, Marcus Sarkis, Robert Scheichl:
New Theoretical Coefficient Robustness Results for FETI-DP. Domain Decomposition Methods in Science and Engineering XX 2013: 313-320 - [i2]Eike Hermann Müller, Xu Guo, Robert Scheichl, Sinan Shi:
Matrix-free GPU implementation of a preconditioned conjugate gradient solver for anisotropic elliptic PDEs. CoRR abs/1302.7193 (2013) - [i1]Eike Hermann Müller, Robert Scheichl:
Massively parallel solvers for elliptic PDEs in Numerical Weather- and Climate Prediction. CoRR abs/1307.2036 (2013) - 2012
- [j14]Victorita Dolean, Frédéric Nataf, Robert Scheichl, Nicole Spillane:
Analysis of a Two-level Schwarz Method with Coarse Spaces Based on Local Dirichlet-to-Neumann Maps. Comput. Methods Appl. Math. 12(4): 391-414 (2012) - [j13]Peter Bastian, Markus Blatt, Robert Scheichl:
Algebraic multigrid for discontinuous Galerkin discretizations of heterogeneous elliptic problems. Numer. Linear Algebra Appl. 19(2): 367-388 (2012) - [j12]Robert Scheichl, Panayot S. Vassilevski, Ludmil T. Zikatanov:
Multilevel Methods for Elliptic Problems with Highly Varying Coefficients on Nonaligned Coarse Grids. SIAM J. Numer. Anal. 50(3): 1675-1694 (2012) - 2011
- [j11]K. Andrew Cliffe, Mike B. Giles, Robert Scheichl, Aretha L. Teckentrup:
Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients. Comput. Vis. Sci. 14(1): 3-15 (2011) - [j10]Ivan G. Graham, Frances Y. Kuo, Dirk Nuyens, Robert Scheichl, Ian H. Sloan:
Quasi-Monte Carlo methods for elliptic PDEs with random coefficients and applications. J. Comput. Phys. 230(10): 3668-3694 (2011) - [j9]Robert Scheichl, Panayot S. Vassilevski, Ludmil T. Zikatanov:
Weak Approximation Properties of Elliptic Projections with Functional Constraints. Multiscale Model. Simul. 9(4): 1677-1699 (2011) - [j8]Clemens Pechstein, Robert Scheichl:
Analysis of FETI methods for multiscale PDEs. Part II: interface variation. Numerische Mathematik 118(3): 485-529 (2011) - 2010
- [j7]Sean Buckeridge, Robert Scheichl:
Parallel geometric multigrid for global weather prediction. Numer. Linear Algebra Appl. 17(2-3): 325-342 (2010) - [j6]Richard Norton, Robert Scheichl:
Convergence Analysis of Planewave Expansion Methods for 2D Schrödinger Operators with Discontinuous Periodic Potentials. SIAM J. Numer. Anal. 47(6): 4356-4380 (2010)
2000 – 2009
- 2009
- [j5]Jan Van Lent, Robert Scheichl, Ivan G. Graham:
Energy-minimizing coarse spaces for two-level Schwarz methods for multiscale PDEs. Numer. Linear Algebra Appl. 16(10): 775-799 (2009) - 2008
- [j4]Clemens Pechstein, Robert Scheichl:
Analysis of FETI methods for multiscale PDEs. Numerische Mathematik 111(2): 293-333 (2008) - 2007
- [j3]Robert Scheichl, Eero Vainikko:
Additive Schwarz with aggregation-based coarsening for elliptic problems with highly variable coefficients. Computing 80(4): 319-343 (2007) - [j2]Ivan G. Graham, Patrick O. Lechner, Robert Scheichl:
Domain decomposition for multiscale PDEs. Numerische Mathematik 106(4): 589-626 (2007) - 2003
- [c1]Roland Masson, Philippe Quandalle, Stéphane Requena, Robert Scheichl:
Parallel Preconditioning for Sedimentary Basin Simulations. LSSC 2003: 93-102 - 2002
- [j1]Robert Scheichl:
Decoupling Three-Dimensional Mixed Problems Using Divergence-Free Finite Elements. SIAM J. Sci. Comput. 23(5): 1752-1776 (2002)
Coauthor Index
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