Derivative-Informed Neural Operator: An efficient framework for high-dimensional parametric derivative learning
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| Vydáno v: | Journal of computational physics Ročník 496; číslo C; s. 112555 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
Elsevier
01.01.2024
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| ISSN: | 0021-9991 |
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| ArticleNumber | 112555 |
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| Author | O'Leary-Roseberry, Thomas Ghattas, Omar Chen, Peng Villa, Umberto |
| Author_xml | – sequence: 1 givenname: Thomas orcidid: 0000-0002-8938-7074 surname: O'Leary-Roseberry fullname: O'Leary-Roseberry, Thomas – sequence: 2 givenname: Peng surname: Chen fullname: Chen, Peng – sequence: 3 givenname: Umberto surname: Villa fullname: Villa, Umberto – sequence: 4 givenname: Omar surname: Ghattas fullname: Ghattas, Omar |
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| Cites_doi | 10.1016/j.jcp.2018.10.045 10.1016/j.cma.2022.114778 10.1016/j.jbiomech.2015.10.007 10.1016/j.jcp.2016.12.041 10.1016/j.cma.2022.114823 10.1137/130933381 10.1137/18M1221837 10.1137/21M1466542 10.1016/j.jcp.2015.10.008 10.1137/110845598 10.1017/S0962492921000064 10.1038/s42256-021-00302-5 10.1088/0266-5611/24/4/045010 10.1137/20M131936X 10.1615/Int.J.UncertaintyQuantification.2019028753 10.1016/j.cma.2021.114181 10.1137/20M133957X 10.1137/120894877 10.1007/s10915-023-02145-1 10.1137/21M1466499 10.1002/nme.2100 10.1137/130934805 10.1137/12089586X 10.1137/090771806 10.1137/130916138 10.1111/j.1467-9868.2011.00777.x 10.1016/j.jcp.2023.112104 10.1145/3428447 10.1016/j.jcp.2019.01.047 10.1137/090780717 10.1016/j.cma.2010.12.018 10.1145/3580278 10.1016/j.jcp.2021.110114 10.1016/j.ijmecsci.2018.03.004 10.3934/ipi.2013.7.1139 10.1088/1361-6420/aa6d8e 10.1137/16M106306X 10.5802/smai-jcm.74 10.1137/120873558 10.21105/joss.00940 10.1017/S0962492920000021 10.1016/j.cma.2017.08.016 10.3934/ipi.2015.9.27 10.1016/j.jcp.2015.04.047 10.1137/21M140078X 10.1137/20M1381381 10.1137/140992564 |
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| References | Cui (10.1016/j.jcp.2023.112555_br0480) 2016; 304 Abadi (10.1016/j.jcp.2023.112555_br0620) Lu (10.1016/j.jcp.2023.112555_br0430) 2022; 393 Cao (10.1016/j.jcp.2023.112555_br0550) 2023; 486 Kingma (10.1016/j.jcp.2023.112555_br0610) 2014 Wu (10.1016/j.jcp.2023.112555_br0350) 2023; 11 Nelsen (10.1016/j.jcp.2023.112555_br0410) 2021; 43 Lindgren (10.1016/j.jcp.2023.112555_br0540) 2011; 73 Baptista (10.1016/j.jcp.2023.112555_br0520) Flath (10.1016/j.jcp.2023.112555_br0270) 2011; 33 Isaac (10.1016/j.jcp.2023.112555_br0280) 2015; 296 Martin (10.1016/j.jcp.2023.112555_br0290) 2012; 34 Zahm (10.1016/j.jcp.2023.112555_br0490) O'Leary-Roseberry (10.1016/j.jcp.2023.112555_br0530) Mei (10.1016/j.jcp.2023.112555_br0590) 2018; 140 Bhattacharya (10.1016/j.jcp.2023.112555_br0010) 2021; 7 Fresca (10.1016/j.jcp.2023.112555_br0020) 2022; 388 Petra (10.1016/j.jcp.2023.112555_br0300) 2014; 36 Constantine (10.1016/j.jcp.2023.112555_br0510) 2014; 36 Yu (10.1016/j.jcp.2023.112555_br0440) 2022; 393 Bui-Thanh (10.1016/j.jcp.2023.112555_br0180) 2012 Wu (10.1016/j.jcp.2023.112555_br0360) 2023; 45 Ghattas (10.1016/j.jcp.2023.112555_br0140) 2021; 30 Bui-Thanh (10.1016/j.jcp.2023.112555_br0700) 2013; 35 Raissi (10.1016/j.jcp.2023.112555_br0420) 2019; 378 Gonzalez (10.1016/j.jcp.2023.112555_br0600) 2008 Gokhale (10.1016/j.jcp.2023.112555_br0580) 2008; 24 Affagard (10.1016/j.jcp.2023.112555_br0560) 2015; 48 Chen (10.1016/j.jcp.2023.112555_br0170) 2019; 9 Alnæs (10.1016/j.jcp.2023.112555_br0670) 2015; 3 Li (10.1016/j.jcp.2023.112555_br0040) 2021 O'Leary-Roseberry (10.1016/j.jcp.2023.112555_br0080) 2022; 402 Alger (10.1016/j.jcp.2023.112555_br0150) 2020; 42 Wu (10.1016/j.jcp.2023.112555_br0370) 2023; 95 Lu (10.1016/j.jcp.2023.112555_br0060) 2021 Crestel (10.1016/j.jcp.2023.112555_br0340) 2017; 33 Chen (10.1016/j.jcp.2023.112555_br0130) 2019; 385 Brennan (10.1016/j.jcp.2023.112555_br0460) 2020; 33 Kim (10.1016/j.jcp.2023.112555_br0630) 2023 Alexanderian (10.1016/j.jcp.2023.112555_br0330) 2016; 38 Kovachki (10.1016/j.jcp.2023.112555_br0030) 2023; 24 Bashir (10.1016/j.jcp.2023.112555_br0160) 2008; 73 Martinsson (10.1016/j.jcp.2023.112555_br0690) 2020; 29 Baydin (10.1016/j.jcp.2023.112555_br0450) 2018; 18 Chen (10.1016/j.jcp.2023.112555_br0250) 2017; 327 Bui-Thanh (10.1016/j.jcp.2023.112555_br0190) 2012; 28 Balay (10.1016/j.jcp.2023.112555_br0680) 2015 Bigoni (10.1016/j.jcp.2023.112555_br0400) Zahm (10.1016/j.jcp.2023.112555_br0500) 2020; 42 Czarnecki (10.1016/j.jcp.2023.112555_br0390) 2017; 30 Villa (10.1016/j.jcp.2023.112555_br0660) 2021; 47 Halko (10.1016/j.jcp.2023.112555_br0380) 2011; 53 Goenezen (10.1016/j.jcp.2023.112555_br0570) 2011; 200 Alexanderian (10.1016/j.jcp.2023.112555_br0110) 2017; 5 Bui-Thanh (10.1016/j.jcp.2023.112555_br0470) 2014; 2 Zhang (10.1016/j.jcp.2023.112555_br0720) 2022; 44 Chen (10.1016/j.jcp.2023.112555_br0310) 2021; 431 Villa (10.1016/j.jcp.2023.112555_br0650) 2018; 3 Chen (10.1016/j.jcp.2023.112555_br0120) 2021; 9 Beskos (10.1016/j.jcp.2023.112555_br0090) 2017; 335 Bui-Thanh (10.1016/j.jcp.2023.112555_br0230) 2013; 35 Li (10.1016/j.jcp.2023.112555_br0050) 2020 Chen (10.1016/j.jcp.2023.112555_br0260) 2019 Martin (10.1016/j.jcp.2023.112555_br0100) 2012; 34 O'Leary-Roseberry (10.1016/j.jcp.2023.112555_br0070) 2022; 388 Bui-Thanh (10.1016/j.jcp.2023.112555_br0220) 2015; 9 Alexanderian (10.1016/j.jcp.2023.112555_br0320) 2014; 36 Farrell (10.1016/j.jcp.2023.112555_br0710) 2013; 35 Bui-Thanh (10.1016/j.jcp.2023.112555_br0210) 2013; 7 Chen (10.1016/j.jcp.2023.112555_br0240) 2020 O'Leary-Roseberry (10.1016/j.jcp.2023.112555_br0640) Bui-Thanh (10.1016/j.jcp.2023.112555_br0200) 2012; 28 |
| References_xml | – volume: 378 start-page: 686 year: 2019 ident: 10.1016/j.jcp.2023.112555_br0420 article-title: Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations publication-title: J. Comput. Phys. doi: 10.1016/j.jcp.2018.10.045 – volume: 393 year: 2022 ident: 10.1016/j.jcp.2023.112555_br0430 article-title: A comprehensive and fair comparison of two neural operators (with practical extensions) based on fair data publication-title: Comput. Methods Appl. Mech. Eng. doi: 10.1016/j.cma.2022.114778 – volume: 48 start-page: 4081 issue: 15 year: 2015 ident: 10.1016/j.jcp.2023.112555_br0560 article-title: Identification of hyperelastic properties of passive thigh muscle under compression with an inverse method from a displacement field measurement publication-title: J. Biomech. doi: 10.1016/j.jbiomech.2015.10.007 – volume: 24 start-page: 1 issue: 89 year: 2023 ident: 10.1016/j.jcp.2023.112555_br0030 article-title: Neural operator: learning maps between function spaces with applications to pdes publication-title: J. Mach. Learn. Res. – volume: 18 start-page: 1 year: 2018 ident: 10.1016/j.jcp.2023.112555_br0450 article-title: Automatic differentiation in machine learning: A survey publication-title: J. Mach. Learn. Res. – year: 2014 ident: 10.1016/j.jcp.2023.112555_br0610 article-title: Adam: a method for stochastic optimization – ident: 10.1016/j.jcp.2023.112555_br0640 – volume: 335 start-page: 327 year: 2017 ident: 10.1016/j.jcp.2023.112555_br0090 article-title: Geometric MCMC for infinite-dimensional inverse problems publication-title: J. Comput. Phys. doi: 10.1016/j.jcp.2016.12.041 – volume: 393 year: 2022 ident: 10.1016/j.jcp.2023.112555_br0440 article-title: Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems publication-title: Comput. Methods Appl. Mech. Eng. doi: 10.1016/j.cma.2022.114823 – volume: 36 start-page: A2122 issue: 5 year: 2014 ident: 10.1016/j.jcp.2023.112555_br0320 article-title: A-optimal design of experiments for infinite-dimensional Bayesian linear inverse problems with regularized ℓ0-sparsification publication-title: SIAM J. Sci. Comput. doi: 10.1137/130933381 – volume: 42 start-page: A534 issue: 1 year: 2020 ident: 10.1016/j.jcp.2023.112555_br0500 article-title: Gradient-based dimension reduction of multivariate vector-valued functions publication-title: SIAM J. Sci. Comput. doi: 10.1137/18M1221837 – volume: 45 start-page: B57 issue: 1 year: 2023 ident: 10.1016/j.jcp.2023.112555_br0360 article-title: An efficient method for goal-oriented linear Bayesian optimal experimental design: application to optimal sensor placement publication-title: SIAM J. Sci. Comput. doi: 10.1137/21M1466542 – volume: 304 start-page: 109 year: 2016 ident: 10.1016/j.jcp.2023.112555_br0480 article-title: Dimension-independent likelihood-informed MCMC publication-title: J. Comput. Phys. doi: 10.1016/j.jcp.2015.10.008 – volume: 34 start-page: A1460 issue: 3 year: 2012 ident: 10.1016/j.jcp.2023.112555_br0290 article-title: A stochastic Newton MCMC method for large-scale statistical inverse problems with application to seismic inversion publication-title: SIAM J. Sci. Comput. doi: 10.1137/110845598 – volume: 30 start-page: 445 year: 2021 ident: 10.1016/j.jcp.2023.112555_br0140 article-title: Learning physics-based models from data: perspectives from inverse problems and model reduction publication-title: Acta Numer. doi: 10.1017/S0962492921000064 – year: 2020 ident: 10.1016/j.jcp.2023.112555_br0240 article-title: Projected Stein variational gradient descent – year: 2015 ident: 10.1016/j.jcp.2023.112555_br0680 – volume: 402 year: 2022 ident: 10.1016/j.jcp.2023.112555_br0080 article-title: Learning high-dimensional parametric maps via reduced basis adaptive residual networks publication-title: Comput. Methods Appl. Mech. Eng. – year: 2021 ident: 10.1016/j.jcp.2023.112555_br0060 article-title: DeepONet: learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators publication-title: Nat. Mach. Intell. doi: 10.1038/s42256-021-00302-5 – volume: 388 year: 2022 ident: 10.1016/j.jcp.2023.112555_br0070 article-title: Derivative-informed projected neural networks for high-dimensional parametric maps governed by PDEs publication-title: Comput. Methods Appl. Mech. Eng. – volume: 24 issue: 4 year: 2008 ident: 10.1016/j.jcp.2023.112555_br0580 article-title: Solution of the nonlinear elasticity imaging inverse problem: the compressible case publication-title: Inverse Probl. doi: 10.1088/0266-5611/24/4/045010 – volume: 42 start-page: A3516 issue: 5 year: 2020 ident: 10.1016/j.jcp.2023.112555_br0150 article-title: Tensor train construction from tensor actions, with application to compression of large high order derivative tensors publication-title: SIAM J. Sci. Comput. doi: 10.1137/20M131936X – volume: 9 issue: 2 year: 2019 ident: 10.1016/j.jcp.2023.112555_br0170 article-title: Hessian-based sampling for high-dimensional model reduction publication-title: Int. J. Uncertain. Quantificat. doi: 10.1615/Int.J.UncertaintyQuantification.2019028753 – ident: 10.1016/j.jcp.2023.112555_br0620 – volume: 388 year: 2022 ident: 10.1016/j.jcp.2023.112555_br0020 article-title: POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition publication-title: Comput. Methods Appl. Mech. Eng. doi: 10.1016/j.cma.2021.114181 – volume: 43 start-page: A3212 issue: 5 year: 2021 ident: 10.1016/j.jcp.2023.112555_br0410 article-title: The random feature model for input-output maps between Banach spaces publication-title: SIAM J. Sci. Comput. doi: 10.1137/20M133957X – volume: 2 start-page: 203 issue: 1 year: 2014 ident: 10.1016/j.jcp.2023.112555_br0470 article-title: An analysis of infinite dimensional Bayesian inverse shape acoustic scattering and its numerical approximation publication-title: SIAM/ASA J. Uncertain. Quantificat. doi: 10.1137/120894877 – volume: 95 start-page: 30 year: 2023 ident: 10.1016/j.jcp.2023.112555_br0370 article-title: Derivative-informed projected neural network for large-scale Bayesian optimal experimental design publication-title: J. Sci. Comput. doi: 10.1007/s10915-023-02145-1 – volume: 11 start-page: 235 issue: 1 year: 2023 ident: 10.1016/j.jcp.2023.112555_br0350 article-title: A fast and scalable computational framework for large-scale and high-dimensional Bayesian optimal experimental design publication-title: SIAM/ASA J. Uncertain. Quantificat. doi: 10.1137/21M1466499 – ident: 10.1016/j.jcp.2023.112555_br0520 – volume: 73 start-page: 844 year: 2008 ident: 10.1016/j.jcp.2023.112555_br0160 article-title: Hessian-based model reduction for large-scale systems with initial condition inputs publication-title: Int. J. Numer. Methods Eng. doi: 10.1002/nme.2100 – volume: 36 start-page: A1525 issue: 4 year: 2014 ident: 10.1016/j.jcp.2023.112555_br0300 article-title: A computational framework for infinite-dimensional Bayesian inverse problems, part ii: stochastic Newton MCMC with application to ice sheet flow inverse problems publication-title: SIAM J. Sci. Comput. doi: 10.1137/130934805 – volume: 35 start-page: A2494 issue: 6 year: 2013 ident: 10.1016/j.jcp.2023.112555_br0700 article-title: A computational framework for infinite-dimensional Bayesian inverse problems part I: the linearized case, with application to global seismic inversion publication-title: SIAM J. Sci. Comput. doi: 10.1137/12089586X – volume: 53 start-page: 217 issue: 2 year: 2011 ident: 10.1016/j.jcp.2023.112555_br0380 article-title: Finding structure with randomness: probabilistic algorithms for constructing approximate matrix decompositions publication-title: SIAM Rev. doi: 10.1137/090771806 – volume: 36 start-page: A1500 issue: 4 year: 2014 ident: 10.1016/j.jcp.2023.112555_br0510 article-title: Active subspace methods in theory and practice: applications to Kriging surfaces publication-title: SIAM J. Sci. Comput. doi: 10.1137/130916138 – ident: 10.1016/j.jcp.2023.112555_br0490 – volume: 73 start-page: 423 issue: 4 year: 2011 ident: 10.1016/j.jcp.2023.112555_br0540 article-title: An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach publication-title: J. R. Stat. Soc., Ser. B, Stat. Methodol. doi: 10.1111/j.1467-9868.2011.00777.x – volume: 33 year: 2020 ident: 10.1016/j.jcp.2023.112555_br0460 article-title: Greedy inference with structure-exploiting lazy maps publication-title: Adv. Neural Inf. Process. Syst. – volume: 486 year: 2023 ident: 10.1016/j.jcp.2023.112555_br0550 article-title: Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems publication-title: J. Comput. Phys. doi: 10.1016/j.jcp.2023.112104 – year: 2020 ident: 10.1016/j.jcp.2023.112555_br0050 article-title: Multipole graph neural operator for parametric partial differential equations publication-title: Neural Inf. Process. Syst. – ident: 10.1016/j.jcp.2023.112555_br0400 – volume: 47 start-page: 1 issue: 2 year: 2021 ident: 10.1016/j.jcp.2023.112555_br0660 article-title: hIPPYlib: an extensible software framework for large-scale inverse problems governed by PDEs; part I: deterministic inversion and linearized Bayesian inference publication-title: ACM Trans. Math. Softw. doi: 10.1145/3428447 – volume: 35 start-page: A2494 issue: 6 year: 2013 ident: 10.1016/j.jcp.2023.112555_br0230 article-title: A computational framework for infinite-dimensional Bayesian inverse problems part I: the linearized case, with application to global seismic inversion publication-title: SIAM J. Sci. Comput. doi: 10.1137/12089586X – volume: 3 issue: 100 year: 2015 ident: 10.1016/j.jcp.2023.112555_br0670 article-title: The fenics project version 1.5 publication-title: Arch. Numer. Softw. – volume: 30 year: 2017 ident: 10.1016/j.jcp.2023.112555_br0390 article-title: Sobolev training for neural networks publication-title: Adv. Neural Inf. Process. Syst. – year: 2008 ident: 10.1016/j.jcp.2023.112555_br0600 article-title: A First Course in Continuum Mechanics – volume: 385 start-page: 163 year: 2019 ident: 10.1016/j.jcp.2023.112555_br0130 article-title: Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty publication-title: J. Comput. Phys. doi: 10.1016/j.jcp.2019.01.047 – volume: 33 start-page: 407 issue: 1 year: 2011 ident: 10.1016/j.jcp.2023.112555_br0270 article-title: Fast algorithms for Bayesian uncertainty quantification in large-scale linear inverse problems based on low-rank partial Hessian approximations publication-title: SIAM J. Sci. Comput. doi: 10.1137/090780717 – volume: 200 start-page: 1406 issue: 13 year: 2011 ident: 10.1016/j.jcp.2023.112555_br0570 article-title: Solution of the nonlinear elasticity imaging inverse problem: the incompressible case publication-title: Comput. Methods Appl. Mech. Eng. doi: 10.1016/j.cma.2010.12.018 – year: 2023 ident: 10.1016/j.jcp.2023.112555_br0630 article-title: hIPPYlib-MUQ: a Bayesian inference software framework for integration of data with complex predictive models under uncertainty publication-title: ACM Trans. Math. Softw. doi: 10.1145/3580278 – volume: 431 year: 2021 ident: 10.1016/j.jcp.2023.112555_br0310 article-title: Optimal design of acoustic metamaterial cloaks under uncertainty publication-title: J. Comput. Phys. doi: 10.1016/j.jcp.2021.110114 – volume: 140 start-page: 446 year: 2018 ident: 10.1016/j.jcp.2023.112555_br0590 article-title: A comparative study of two constitutive models within an inverse approach to determine the spatial stiffness distribution in soft materials publication-title: Int. J. Mech. Sci. doi: 10.1016/j.ijmecsci.2018.03.004 – volume: 7 start-page: 1139 issue: 4 year: 2013 ident: 10.1016/j.jcp.2023.112555_br0210 article-title: Analysis of the Hessian for inverse scattering problems. Part III: inverse medium scattering of electromagnetic waves publication-title: Inverse Probl. Imaging doi: 10.3934/ipi.2013.7.1139 – volume: 33 issue: 7 year: 2017 ident: 10.1016/j.jcp.2023.112555_br0340 article-title: A-optimal encoding weights for nonlinear inverse problems, with application to the Helmholtz inverse problem publication-title: Inverse Probl. doi: 10.1088/1361-6420/aa6d8e – volume: 5 start-page: 1166 issue: 1 year: 2017 ident: 10.1016/j.jcp.2023.112555_br0110 article-title: Mean-variance risk-averse optimal control of systems governed by PDEs with random parameter fields using quadratic approximations publication-title: SIAM/ASA J. Uncertain. Quantificat. doi: 10.1137/16M106306X – volume: 28 issue: 5 year: 2012 ident: 10.1016/j.jcp.2023.112555_br0190 article-title: Analysis of the Hessian for inverse scattering problems. Part I: inverse shape scattering of acoustic waves publication-title: Inverse Probl. – volume: 7 year: 2021 ident: 10.1016/j.jcp.2023.112555_br0010 article-title: Model reduction and neural networks for parametric PDEs publication-title: SMAI J. Comput. Math. doi: 10.5802/smai-jcm.74 – ident: 10.1016/j.jcp.2023.112555_br0530 – volume: 35 start-page: C369 issue: 4 year: 2013 ident: 10.1016/j.jcp.2023.112555_br0710 article-title: Automated derivation of the adjoint of high-level transient finite element programs publication-title: SIAM J. Sci. Comput. doi: 10.1137/120873558 – volume: 3 start-page: 940 year: 2018 ident: 10.1016/j.jcp.2023.112555_br0650 article-title: hIPPYlib: an extensible software framework for large-scale inverse problems publication-title: J. Open Sour. Softw. doi: 10.21105/joss.00940 – volume: 28 issue: 5 year: 2012 ident: 10.1016/j.jcp.2023.112555_br0200 article-title: Analysis of the Hessian for inverse scattering problems. Part II: inverse medium scattering of acoustic waves publication-title: Inverse Probl. – volume: 29 start-page: 403 year: 2020 ident: 10.1016/j.jcp.2023.112555_br0690 article-title: Randomized numerical linear algebra: foundations and algorithms publication-title: Acta Numer. doi: 10.1017/S0962492920000021 – volume: 327 start-page: 147 year: 2017 ident: 10.1016/j.jcp.2023.112555_br0250 article-title: Hessian-based adaptive sparse quadrature for infinite-dimensional Bayesian inverse problems publication-title: Comput. Methods Appl. Mech. Eng. doi: 10.1016/j.cma.2017.08.016 – volume: 34 start-page: A1460 issue: 3 year: 2012 ident: 10.1016/j.jcp.2023.112555_br0100 article-title: A stochastic Newton mcmc method for large-scale statistical inverse problems with application to seismic inversion publication-title: SIAM J. Sci. Comput. doi: 10.1137/110845598 – volume: 9 start-page: 27 issue: 1 year: 2015 ident: 10.1016/j.jcp.2023.112555_br0220 article-title: A scalable algorithm for MAP estimators in Bayesian inverse problems with Besov priors publication-title: Inverse Probl. Imaging doi: 10.3934/ipi.2015.9.27 – volume: 296 start-page: 348 year: 2015 ident: 10.1016/j.jcp.2023.112555_br0280 article-title: Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet publication-title: J. Comput. Phys. doi: 10.1016/j.jcp.2015.04.047 – year: 2012 ident: 10.1016/j.jcp.2023.112555_br0180 article-title: Extreme-scale UQ for Bayesian inverse problems governed by PDEs – year: 2019 ident: 10.1016/j.jcp.2023.112555_br0260 article-title: Projected Stein variational Newton: a fast and scalable Bayesian inference method in high dimensions publication-title: Adv. Neural Inf. Process. Syst. – volume: 44 start-page: C1 issue: 1 year: 2022 ident: 10.1016/j.jcp.2023.112555_br0720 article-title: PETSc TSAdjoint: a discrete adjoint ode solver for first-order and second-order sensitivity analysis publication-title: SIAM J. Sci. Comput. doi: 10.1137/21M140078X – year: 2021 ident: 10.1016/j.jcp.2023.112555_br0040 article-title: Fourier neural operator for parametric partial differential equations – volume: 9 start-page: 1381 issue: 4 year: 2021 ident: 10.1016/j.jcp.2023.112555_br0120 article-title: Taylor approximation for chance constrained optimization problems governed by partial differential equations with high-dimensional random parameters publication-title: SIAM/ASA J. Uncertain. Quantificat. doi: 10.1137/20M1381381 – volume: 38 start-page: A243 issue: 1 year: 2016 ident: 10.1016/j.jcp.2023.112555_br0330 article-title: A fast and scalable method for A-optimal design of experiments for infinite-dimensional Bayesian nonlinear inverse problems publication-title: SIAM J. Sci. Comput. doi: 10.1137/140992564 |
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