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2020 – today
- 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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