Goal-oriented real-time Bayesian inference for linear autonomous dynamical systems with application to digital twins for tsunami early warning.

Omar Ghattas University of Texas at Austin, USA http://users.ices.utexas.edu/~omar/ https://scholar.google.com/citations?user=A5vhsIYAAAAJ https://en.wikipedia.org/wiki/Omar_Ghattas https://www.wikidata.org/entity/Q39163797

Stefan Henneking Sreeram Venkat Omar Ghattas Goal-oriented real-time Bayesian inference for linear autonomous dynamical systems with application to digital twins for tsunami early warning. 2026 114682 552 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2026.114682 db/journals/jcphy/jcphy552.html#HennekingVG26 streams/journals/jcphy

Lianghao Cao Joshua Chen Michael Brennan Thomas O'Leary-Roseberry Youssef Marzouk 0001 Omar Ghattas LazyDINO: Fast, Scalable, and Efficiently Amortized Bayesian Inversion via Structure-Exploiting and Surrogate-Driven Measure Transport. 24:1-24:71 2026 27 J. Mach. Learn. Res. https://jmlr.org/papers/v27/25-0858.html db/journals/jmlr/jmlr27.html#CaoCBOMG26

Xindi Gong Dingcheng Luo Thomas O'Leary-Roseberry Ruanui Nicholson Omar Ghattas Shape Derivative-Informed Neural Operators with Application to Risk-Averse Shape Optimization. 2026 March abs/2603.03211 CoRR https://doi.org/10.48550/arXiv.2603.03211 db/journals/corr/corr2603.html#abs-2603-03211 streams/journals/corr

Jiqun Tu Ian Karlin John Camier Veselin Dobrev Tzanio V. Kolev Stefan Henneking Omar Ghattas Accelerating High-Order Finite Element Simulations at Extreme Scale with FP64 Tensor Cores. 2026 March abs/2603.09038 CoRR https://doi.org/10.48550/arXiv.2603.09038 db/journals/corr/corr2603.html#abs-2603-09038 streams/journals/corr

Stefan Henneking Fabian Kutschera Sreeram Venkat Alice-Agnes Gabriel Omar Ghattas Real-time probabilistic tsunami forecasting in Cascadia from sparse offshore pressure observations. 2026 March abs/2603.14966 CoRR https://doi.org/10.48550/arXiv.2603.14966 db/journals/corr/corr2603.html#abs-2603-14966 streams/journals/corr

Nick Alger Blake Christierson Peng Chen 0024 Omar Ghattas Tucker Tensor Train Taylor Series. 2026 March abs/2603.21141 CoRR https://doi.org/10.48550/arXiv.2603.21141 db/journals/corr/corr2603.html#abs-2603-21141 streams/journals/corr

Sreeram Venkat Stefan Henneking Omar Ghattas Sensor Placement for Tsunami Early Warning via Large-Scale Bayesian Optimal Experimental Design. 2026 April abs/2604.08812 CoRR https://doi.org/10.48550/arXiv.2604.08812 db/journals/corr/corr2604.html#abs-2604-08812 streams/journals/corr

Lianghao Cao Thomas O'Leary-Roseberry Omar Ghattas Derivative-Informed Neural Operator Acceleration of Geometric MCMC for Infinite-Dimensional Bayesian Inverse Problems. 78:1-78:68 2025 26 J. Mach. Learn. Res. https://jmlr.org/papers/v26/24-0745.html db/journals/jmlr/jmlr26.html#CaoOG25

Dingcheng Luo Thomas O'Leary-Roseberry Peng Chen 0024 Omar Ghattas Efficient PDE-Constrained Optimization Under High-Dimensional Uncertainty Using Derivative-Informed Neural Operators. 899- 2025 47 SIAM J. Sci. Comput. 4 https://doi.org/10.1137/23m157956x db/journals/siamsc/siamsc47.html#LuoOCG25 streams/journals/siamsc

Sreeram Venkat Milinda Fernando Stefan Henneking Omar Ghattas Fast and Scalable FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices with Application to Linear Inverse Problems Governed by Autonomous Dynamical Systems. 1201- 2025 47 SIAM J. Sci. Comput. 5 https://doi.org/10.1137/24m1683172 db/journals/siamsc/siamsc47.html#VenkatFHG25 streams/journals/siamsc

Stefan Henneking Sreeram Venkat Veselin Dobrev John Camier Tzanio V. Kolev Milinda Fernando Alice-Agnes Gabriel Omar Ghattas Real-Time Bayesian Inference at Extreme Scale: A Digital Twin for Tsunami Early Warning Applied to the Cascadia Subduction Zone. 60-71 2025 SC https://doi.org/10.1145/3712285.3771787 conf/sc/2025 db/conf/sc/sc2025.html#HennekingVDCKFG25 Sreeram Venkat Kasia Swirydowicz Noah Wolfe Omar Ghattas Mixed-Precision Performance Portability of FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices. 1133-1146 2025 SC Workshops https://doi.org/10.1145/3731599.3767490 conf/sc/2025w db/conf/sc/sc2025w.html#VenkatSWG25

Stefan Henneking Sreeram Venkat Omar Ghattas Goal-Oriented Real-Time Bayesian Inference for Linear Autonomous Dynamical Systems With Application to Digital Twins for Tsunami Early Warning. 2025 January abs/2501.14911 CoRR https://doi.org/10.48550/arXiv.2501.14911 db/journals/corr/corr2501.html#abs-2501-14911 streams/journals/corr

Dingcheng Luo Thomas O'Leary-Roseberry Peng Chen 0024 Omar Ghattas Dimension reduction for derivative-informed operator learning: An analysis of approximation errors. 2025 April abs/2504.08730 CoRR https://doi.org/10.48550/arXiv.2504.08730 db/journals/corr/corr2504.html#abs-2504-08730 streams/journals/corr

Stefan Henneking Sreeram Venkat Veselin Dobrev John Camier Tzanio V. Kolev Milinda Fernando Alice-Agnes Gabriel Omar Ghattas Real-time Bayesian inference at extreme scale: A digital twin for tsunami early warning applied to the Cascadia subduction zone. 2025 April abs/2504.16344 CoRR https://doi.org/10.48550/arXiv.2504.16344 db/journals/corr/corr2504.html#abs-2504-16344 streams/journals/corr

Mathew Hu Nick Alger Rami Nammour Omar Ghattas Accelerating seismic inversion and uncertainty quantification with efficient high-rank Hessian approximations. 2025 July abs/2507.10804 CoRR https://doi.org/10.48550/arXiv.2507.10804 db/journals/corr/corr2507.html#abs-2507-10804 streams/journals/corr

Sreeram Venkat Kasia Swirydowicz Noah Wolfe Omar Ghattas Mixed-Precision Performance Portability of FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices. 2025 August abs/2508.10202 CoRR https://doi.org/10.48550/arXiv.2508.10202 db/journals/corr/corr2508.html#abs-2508-10202 streams/journals/corr

Boyuan Yao Dingcheng Luo Lianghao Cao Nikola B. Kovachki Thomas O'Leary-Roseberry Omar Ghattas Derivative-Informed Fourier Neural Operator: Universal Approximation and Applications to PDE-Constrained Optimization. 2025 December abs/2512.14086 CoRR https://doi.org/10.48550/arXiv.2512.14086 db/journals/corr/corr2512.html#abs-2512-14086 streams/journals/corr

Thomas O'Leary-Roseberry Peng Chen 0024 Umberto Villa Omar Ghattas Derivative-Informed Neural Operator: An efficient framework for high-dimensional parametric derivative learning. 112555 2024 January 496 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2023.112555 db/journals/jcphy/jcphy496.html#OLearyRoseberryCVG24

Ricardo Baptista Lianghao Cao Joshua Chen Omar Ghattas Fengyi Li Youssef M. Marzouk J. Tinsley Oden Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport. 112844 2024 503 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2024.112844 db/journals/jcphy/jcphy503.html#BaptistaCCGLMO24

Dingcheng Luo Peng Chen 0024 Thomas O'Leary-Roseberry Umberto Villa Omar Ghattas SOUPy: Stochastic PDE-constrained optimization under high-dimensional uncertainty in Python. 6101 2024 9 J. Open Source Softw. 99 https://doi.org/10.21105/joss.06101 db/journals/jossw/jossw9.html#LuoCOVG24 streams/journals/jossw

Nick Alger Tucker Hartland Noemi Petra Omar Ghattas Point Spread Function Approximation of High-Rank Hessians with Locally Supported Nonnegative Integral Kernels. 1658- 2024 46 SIAM J. Sci. Comput. 3 https://doi.org/10.1137/23m1584745 db/journals/siamsc/siamsc46.html#AlgerHPG24

Lianghao Cao Thomas O'Leary-Roseberry Omar Ghattas Efficient geometric Markov chain Monte Carlo for nonlinear Bayesian inversion enabled by derivative-informed neural operators. 2024 abs/2403.08220 CoRR https://doi.org/10.48550/arXiv.2403.08220 db/journals/corr/corr2403.html#abs-2403-08220

Sreeram Venkat Milinda Fernando Stefan Henneking Omar Ghattas Fast and Scalable FFT-Based GPU-Accelerated Algorithms for Hessian Actions Arising in Linear Inverse Problems Governed by Autonomous Dynamical Systems. 2024 abs/2407.13066 CoRR https://doi.org/10.48550/arXiv.2407.13066 db/journals/corr/corr2407.html#abs-2407-13066 streams/journals/corr

Dingcheng Luo Joshua Chen Peng Chen 0024 Omar Ghattas Gaussian mixture Taylor approximations of risk measures constrained by PDEs with Gaussian random field inputs. 2024 abs/2408.06615 CoRR https://doi.org/10.48550/arXiv.2408.06615 db/journals/corr/corr2408.html#abs-2408-06615 streams/journals/corr

Joseph Kirchhoff Dingcheng Luo Thomas O'Leary-Roseberry Omar Ghattas Inference of Heterogeneous Material Properties via Infinite-Dimensional Integrated DIC. 2024 abs/2408.10217 CoRR https://doi.org/10.48550/arXiv.2408.10217 db/journals/corr/corr2408.html#abs-2408-10217 streams/journals/corr

Julie Pham Omar Ghattas Noel Clemens Karen Willcox Real-time aerodynamic load estimation for hypersonics via strain-based inverse maps. 2024 abs/2408.15286 CoRR https://doi.org/10.48550/arXiv.2408.15286 db/journals/corr/corr2408.html#abs-2408-15286 streams/journals/corr

Lianghao Cao Joshua Chen Michael Brennan Thomas O'Leary-Roseberry Youssef M. Marzouk Omar Ghattas LazyDINO: Fast, scalable, and efficiently amortized Bayesian inversion via structure-exploiting and surrogate-driven measure transport. 2024 abs/2411.12726 CoRR https://doi.org/10.48550/arXiv.2411.12726 db/journals/corr/corr2411.html#abs-2411-12726 streams/journals/corr

Jeonghun J. Lee Omar Ghattas Interior over-penalized enriched Galerkin methods for second order elliptic equations. 102-111 2023 December 152 Comput. Math. Appl. https://doi.org/10.1016/j.camwa.2023.09.049 db/journals/cma/cma152.html#LeeG23

Dingcheng Luo Lianghao Cao Peng Chen 0024 Omar Ghattas J. Tinsley Oden Optimal design of chemoepitaxial guideposts for the directed self-assembly of block copolymer systems using an inexact Newton algorithm. 112101 2023 485 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2023.112101 db/journals/jcphy/jcphy485.html#LuoC0GO23

Lianghao Cao Thomas O'Leary-Roseberry Prashant K. Jha J. Tinsley Oden Omar Ghattas Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems. 112104 2023 486 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2023.112104 db/journals/jcphy/jcphy486.html#CaoOJOG23

Keyi Wu Thomas O'Leary-Roseberry Peng Chen 0024 Omar Ghattas Large-Scale Bayesian Optimal Experimental Design with Derivative-Informed Projected Neural Network. 30 2023 April 95 J. Sci. Comput. 1 https://doi.org/10.1007/s10915-023-02145-1 db/journals/jscic/jscic95.html#WuOCG23

Keyi Wu Peng Chen 0024 Omar Ghattas A Fast and Scalable Computational Framework for Large-Scale High-Dimensional Bayesian Optimal Experimental Design. 235-261 2023 March 11 SIAM/ASA J. Uncertain. Quantification 1 https://doi.org/10.1137/21m1466499 db/journals/juq/juq11.html#WuCG23

Keyi Wu Peng Chen 0024 Omar Ghattas An Offline-Online Decomposition Method for Efficient Linear Bayesian Goal-Oriented Optimal Experimental Design: Application to Optimal Sensor Placement. 57- 2023 February 45 SIAM J. Sci. Comput. 1 https://doi.org/10.1137/21m1466542 db/journals/siamsc/siamsc45.html#WuCG23

Ki-Tae Kim Umberto Villa Matthew D. Parno Youssef M. Marzouk Omar Ghattas Noemi Petra hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty. 17:1-17:31 2023 June 49 ACM Trans. Math. Softw. 2 https://doi.org/10.1145/3580278 https://www.wikidata.org/entity/Q123143237 db/journals/toms/toms49.html#KimVPMGP23

Dingcheng Luo Thomas O'Leary-Roseberry Peng Chen 0024 Omar Ghattas Efficient PDE-Constrained optimization under high-dimensional uncertainty using derivative-informed neural operators. 2023 abs/2305.20053 CoRR https://doi.org/10.48550/arXiv.2305.20053 db/journals/corr/corr2305.html#abs-2305-20053

Lianghao Cao Keyi Wu J. Tinsley Oden Peng Chen 0024 Omar Ghattas Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data. 2023 abs/2306.05398 CoRR https://doi.org/10.48550/arXiv.2306.05398 db/journals/corr/corr2306.html#abs-2306-05398

Nick Alger Tucker Hartland Noemi Petra Omar Ghattas Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels. 2023 abs/2307.03349 CoRR https://doi.org/10.48550/arXiv.2307.03349 db/journals/corr/corr2307.html#abs-2307-03349

Jeonghun J. Lee Tan Bui-Thanh Umberto Villa Omar Ghattas Forward and inverse modeling of fault transmissibility in subsurface flows. 354-367 2022 128 Comput. Math. Appl. https://doi.org/10.1016/j.camwa.2022.09.013 db/journals/cma/cma128.html#LeeBVG22

Lianghao Cao Omar Ghattas J. Tinsley Oden A Globally Convergent Modified Newton Method for the Direct Minimization of the Ohta-Kawasaki Energy with Application to the Directed Self-Assembly of Diblock Copolymers. 51- 2022 44 SIAM J. Sci. Comput. 1 https://doi.org/10.1137/20m1378119 db/journals/siamsc/siamsc44.html#CaoGO22

Milinda Fernando David Neilsen Eric W. Hirschmann Yosef Zlochower Hari Sundar Omar Ghattas George Biros A GPU-Accelerated AMR Solver for Gravitational Wave Propagation. 75:1-75:15 2022 SC https://doi.org/10.1109/SC41404.2022.00080 https://dl.acm.org/doi/10.5555/3571885.3571984 conf/sc/2022 db/conf/sc/sc2022.html#FernandoNHZSGB22

Keyi Wu Thomas O'Leary-Roseberry Peng Chen 0024 Omar Ghattas Derivative-informed projected neural network for large-scale Bayesian optimal experimental design. 2022 abs/2201.07925 CoRR https://arxiv.org/abs/2201.07925 db/journals/corr/corr2201.html#abs-2201-07925

Alex Leviyev Joshua Chen Yifei Wang 0005 Omar Ghattas Aaron Zimmerman A stochastic Stein Variational Newton method. 2022 abs/2204.09039 CoRR https://doi.org/10.48550/arXiv.2204.09039 db/journals/corr/corr2204.html#abs-2204-09039

Thomas O'Leary-Roseberry Peng Chen 0024 Umberto Villa Omar Ghattas Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning. 2022 abs/2206.10745 CoRR https://doi.org/10.48550/arXiv.2206.10745 db/journals/corr/corr2206.html#abs-2206-10745

Dingcheng Luo Lianghao Cao Peng Chen 0024 Omar Ghattas J. Tinsley Oden Optimal design of chemoepitaxial guideposts for directed self-assembly of block copolymer systems using an inexact-Newton algorithm. 2022 abs/2208.01193 CoRR https://doi.org/10.48550/arXiv.2208.01193 db/journals/corr/corr2208.html#abs-2208-01193

Jeonghun J. Lee Omar Ghattas Interior over-stabilized enriched Galerkin methods for second order elliptic equations. 2022 abs/2208.09969 CoRR https://doi.org/10.48550/arXiv.2208.09969 db/journals/corr/corr2208.html#abs-2208-09969

Lianghao Cao Thomas O'Leary-Roseberry Prashant K. Jha J. Tinsley Oden Omar Ghattas Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems. 2022 abs/2210.03008 CoRR https://doi.org/10.48550/arXiv.2210.03008 db/journals/corr/corr2210.html#abs-2210-03008

Omar Ghattas Karen Willcox Learning physics-based models from data: perspectives from inverse problems and model reduction. 445-554 2021 May 30 Acta Numer. https://doi.org/10.1017/S0962492921000064 db/journals/actanum/actanum30.html#GhattasW21

Peng Chen 0024 Michael R. Haberman Omar Ghattas Optimal design of acoustic metamaterial cloaks under uncertainty. 110114 2021 431 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2021.110114 db/journals/jcphy/jcphy431.html#ChenHG21

Peng Chen 0024 Omar Ghattas Taylor Approximation for Chance Constrained Optimization Problems Governed by Partial Differential Equations with High-Dimensional Random Parameters. 1381-1410 2021 9 SIAM/ASA J. Uncertain. Quantification 4 https://doi.org/10.1137/20M1381381 https://www.wikidata.org/entity/Q115246871 db/journals/juq/juq9.html#ChenG21

Karen E. Willcox Omar Ghattas Patrick Heimbach The imperative of physics-based modeling and inverse theory in computational science. 166-168 2021 1 Nat. Comput. Sci. 3 https://doi.org/10.1038/s43588-021-00040-z db/journals/ncs/ncs1.html#WillcoxGH21

Peng Chen 0024 Omar Ghattas Stein Variational Reduced Basis Bayesian Inversion. A1163-A1193 2021 43 SIAM J. Sci. Comput. 2 https://doi.org/10.1137/20M1321589 db/journals/siamsc/siamsc43.html#ChenG21

Umberto Villa Noemi Petra Omar Ghattas hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs: Part I: Deterministic Inversion and Linearized Bayesian Inference. 16:1-16:34 2021 47 ACM Trans. Math. Softw. 2 https://doi.org/10.1145/3428447 https://www.wikidata.org/entity/Q113309897 db/journals/toms/toms47.html#VillaPG21

Amal Alghamdi Marc Andre Hesse Jingyi Chen Umberto Villa Omar Ghattas Bayesian Poroelastic Aquifer Characterization from InSAR Surface Deformation Data Part II: Quantifying the Uncertainty. 2021 abs/2102.04577 CoRR https://arxiv.org/abs/2102.04577 db/journals/corr/corr2102.html#abs-2102-04577

Keyi Wu Peng Chen 0024 Omar Ghattas A fast and scalable computational framework for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placement. 2021 abs/2102.06627 CoRR https://arxiv.org/abs/2102.06627 db/journals/corr/corr2102.html#abs-2102-06627

Ki-Tae Kim Umberto Villa Matthew D. Parno Youssef M. Marzouk Omar Ghattas Noemi Petra hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty. 2021 abs/2112.00713 CoRR https://arxiv.org/abs/2112.00713 db/journals/corr/corr2112.html#abs-2112-00713

Thomas O'Leary-Roseberry Xiaosong Du Anirban Chaudhuri Joaquim R. R. A. Martins Karen Willcox Omar Ghattas Adaptive Projected Residual Networks for Learning Parametric Maps from Sparse Data. 2021 abs/2112.07096 CoRR https://arxiv.org/abs/2112.07096 db/journals/corr/corr2112.html#abs-2112-07096

Ilona Ambartsumyan Wajih Halim Boukaram Tan Bui-Thanh Omar Ghattas David E. Keyes Georg Stadler George Turkiyyah Stefano Zampini Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs. A3397-A3426 2020 42 SIAM J. Sci. Comput. 5 https://doi.org/10.1137/19M1270367 https://www.wikidata.org/entity/Q114074247 db/journals/siamsc/siamsc42.html#AmbartsumyanBBG20

Nick Alger Peng Chen 0024 Omar Ghattas Tensor Train Construction From Tensor Actions, With Application to Compression of Large High Order Derivative Tensors. A3516-A3539 2020 42 SIAM J. Sci. Comput. 5 https://doi.org/10.1137/20M131936X https://www.wikidata.org/entity/Q114074213 db/journals/siamsc/siamsc42.html#AlgerCG20

Peng Chen 0024 Omar Ghattas Projected Stein Variational Gradient Descent. 2020 NeurIPS https://proceedings.neurips.cc/paper/2020/hash/14faf969228fc18fcd4fcf59437b0c97-Abstract.html conf/nips/2020 db/conf/nips/neurips2020.html#0024G20 Dan Stanzione John West 0001 R. Todd Evans Tommy Minyard Omar Ghattas Dhabaleswar K. Panda 0001 Frontera: The Evolution of Leadership Computing at the National Science Foundation. 106-111 2020 PEARC https://doi.org/10.1145/3311790.3396656 conf/xsede/2020 db/conf/xsede/pearc2020.html#StanzioneWEMGP20

Thomas O'Leary-Roseberry Nick Alger Omar Ghattas Low Rank Saddle Free Newton: Algorithm and Analysis. 2020 abs/2002.02881 CoRR https://arxiv.org/abs/2002.02881 db/journals/corr/corr2002.html#abs-2002-02881

Thomas O'Leary-Roseberry Omar Ghattas Ill-Posedness and Optimization Geometry for Nonlinear Neural Network Training. 2020 abs/2002.02882 CoRR https://arxiv.org/abs/2002.02882 db/journals/corr/corr2002.html#abs-2002-02882

Peng Chen 0024 Omar Ghattas Projected Stein Variational Gradient Descent. 2020 abs/2002.03469 CoRR https://arxiv.org/abs/2002.03469 db/journals/corr/corr2002.html#abs-2002-03469

Nick Alger Peng Chen 0024 Omar Ghattas Tensor train construction from tensor actions, with application to compression of large high order derivative tensors. 2020 abs/2002.06244 CoRR https://arxiv.org/abs/2002.06244 db/journals/corr/corr2002.html#abs-2002-06244

Amal Alghamdi Marc Andre Hesse Jingyi Chen Omar Ghattas Bayesian Poroelastic Aquifer Characterization from InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate. 2020 abs/2002.10706 CoRR https://arxiv.org/abs/2002.10706 db/journals/corr/corr2002.html#abs-2002-10706

Peng Chen 0024 Omar Ghattas Stein variational reduced basis Bayesian inversion. 2020 abs/2002.10924 CoRR https://arxiv.org/abs/2002.10924 db/journals/corr/corr2002.html#abs-2002-10924

Ilona Ambartsumyan Wajih Bou Karam Tan Bui-Thanh Omar Ghattas David E. Keyes Georg Stadler George Turkiyyah Stefano Zampini Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs. 2020 abs/2003.10173 CoRR https://arxiv.org/abs/2003.10173 db/journals/corr/corr2003.html#abs-2003-10173

Keyi Wu Peng Chen 0024 Omar Ghattas A fast and scalable computational framework for large-scale and high-dimensional Bayesian optimal experimental design. 2020 abs/2010.15196 CoRR https://arxiv.org/abs/2010.15196 db/journals/corr/corr2010.html#abs-2010-15196

Lianghao Cao Omar Ghattas J. Tinsley Oden A globally convergent modified Newton method for the direct minimization of the Ohta-Kawasaki energy with application to the directed self-assembly of diblock copolymers. 2020 abs/2010.15271 CoRR https://arxiv.org/abs/2010.15271 db/journals/corr/corr2010.html#abs-2010-15271

Thomas O'Leary-Roseberry Umberto Villa Peng Chen 0024 Omar Ghattas Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs. 2020 abs/2011.15110 CoRR https://arxiv.org/abs/2011.15110 db/journals/corr/corr2011.html#abs-2011-15110

Longfei Gao Omar Ghattas David E. Keyes Energy-conserving 3D elastic wave simulation with finite difference discretization on staggered grids with nonconforming interfaces. 2020 abs/2012.13863 CoRR https://arxiv.org/abs/2012.13863 db/journals/corr/corr2012.html#abs-2012-13863

Peng Chen 0024 Umberto Villa Omar Ghattas Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty. 163-186 2019 385 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2019.01.047 https://www.wikidata.org/entity/Q128324838 db/journals/jcphy/jcphy385.html#ChenVG19

Nick Alger Vishwas Rao Aaron Myers Tan Bui-Thanh Omar Ghattas Scalable Matrix-Free Adaptive Product-Convolution Approximation for Locally Translation-Invariant Operators. A2296-A2328 2019 41 SIAM J. Sci. Comput. 4 https://doi.org/10.1137/18M1189324 https://www.wikidata.org/entity/Q127459963 db/journals/siamsc/siamsc41.html#AlgerRMBG19

Amir Dezfouli Hassan Ashtiani Omar Ghattas Richard Nock Peter Dayan Cheng Soon Ong Disentangled behavioural representations. 2251-2260 2019 NeurIPS https://proceedings.neurips.cc/paper/2019/hash/e077e1a544eec4f0307cf5c3c721d944-Abstract.html http://papers.nips.cc/paper/8497-disentangled-behavioural-representations conf/nips/2019 db/conf/nips/nips2019.html#DezfouliAGNDO19 Peng Chen 0024 Keyi Wu Joshua Chen Tom O'Leary-Roseberry Omar Ghattas Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions. 15104-15113 2019 NeurIPS https://proceedings.neurips.cc/paper/2019/hash/eea5d933e9dce59c7dd0f6532f9ea81b-Abstract.html http://papers.nips.cc/paper/9649-projected-stein-variational-newton-a-fast-and-scalable-bayesian-inference-method-in-high-dimensions conf/nips/2019 db/conf/nips/nips2019.html#0024WCOG19

Umberto Villa Noemi Petra Omar Ghattas hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs; Part I: Deterministic Inversion and Linearized Bayesian Inference. 2019 abs/1909.03948 CoRR http://arxiv.org/abs/1909.03948 db/journals/corr/corr1909.html#abs-1909-03948

Umberto Villa Noemi Petra Omar Ghattas hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems. 940 2018 3 J. Open Source Softw. 30 https://doi.org/10.21105/joss.00940 https://www.wikidata.org/entity/Q113308054 db/journals/jossw/jossw3.html#VillaPG18

Kainan Wang Tan Bui-Thanh Omar Ghattas A Randomized Maximum A Posteriori Method for Posterior Sampling of High Dimensional Nonlinear Bayesian Inverse Problems. 2018 40 SIAM J. Sci. Comput. 1 https://doi.org/10.1137/16M1060625 db/journals/siamsc/siamsc40.html#WangBG18

Alen Alexanderian Noemi Petra Georg Stadler Omar Ghattas Mean-Variance Risk-Averse Optimal Control of Systems Governed by PDEs with Random Parameter Fields Using Quadratic Approximations. 1166-1192 2017 5 SIAM/ASA J. Uncertain. Quantification 1 https://doi.org/10.1137/16M106306X db/journals/juq/juq5.html#AlexanderianPSG17

Nick Alger Umberto Villa Tan Bui-Thanh Omar Ghattas A Data Scalable Augmented Lagrangian KKT Preconditioner for Large-Scale Inverse Problems. 2017 39 SIAM J. Sci. Comput. 5 https://doi.org/10.1137/16M1084365 db/journals/siamsc/siamsc39.html#AlgerVBG17

Johann Rudi Georg Stadler Omar Ghattas Weighted BFBT Preconditioner for Stokes Flow Problems with Highly Heterogeneous Viscosity. 2017 39 SIAM J. Sci. Comput. 5 https://doi.org/10.1137/16M108450X db/journals/siamsc/siamsc39.html#RudiSG17

Alen Alexanderian Noemi Petra Georg Stadler Omar Ghattas A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems. 2016 38 SIAM J. Sci. Comput. 1 https://doi.org/10.1137/140992564 https://www.wikidata.org/entity/Q57434692 db/journals/siamsc/siamsc38.html#AlexanderianPSG16

Omar Ghattas Tobin Isaac Noémi Petra Georg Stadler Scalable Algorithms for Bayesian Inference of Large-Scale Models from Large-Scale Data. 3-6 2016 VECPAR https://doi.org/10.1007/978-3-319-61982-8_1 conf/vecpar/2016 db/conf/vecpar/vecpar2016.html#GhattasIPS16

Johann Rudi Georg Stadler Omar Ghattas Weighted BFBT Preconditioner for Stokes Flow Problems with Highly Heterogeneous Viscosity. 2016 abs/1607.03936 CoRR http://arxiv.org/abs/1607.03936 db/journals/corr/corr1607.html#RudiSG16

Ulrich Rüde Karen Willcox Lois Curfman McInnes Hans De Sterck George Biros Hans-Joachim Bungartz James Corones Evin Cramer James Crowley Omar Ghattas Max D. Gunzburger Michael Hanke 0001 Robert J. Harrison Michael A. Heroux Jan S. Hesthaven Peter K. Jimack Chris Johnson Kirk E. Jordan David E. Keyes Rolf H. Krause Vipin Kumar Stefan Mayer Juan Meza Knut Martin Mørken J. Tinsley Oden Linda R. Petzold Padma Raghavan Suzanne M. Shontz Anne E. Trefethen Peter R. Turner Vladimir V. Voevodin Barbara I. Wohlmuth Carol S. Woodward Research and Education in Computational Science and Engineering. 2016 abs/1610.02608 CoRR http://arxiv.org/abs/1610.02608 db/journals/corr/corr1610.html#RudeWMSBBCCCGGH16

Tobin Isaac Noemi Petra Georg Stadler Omar Ghattas 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. 348-368 2015 296 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2015.04.047 db/journals/jcphy/jcphy296.html#IsaacPSG15

Lucas C. Wilcox Georg Stadler Tan Bui-Thanh Omar Ghattas Discretely Exact Derivatives for Hyperbolic PDE-Constrained Optimization Problems Discretized by the Discontinuous Galerkin Method. 138-162 2015 63 J. Sci. Comput. 1 https://doi.org/10.1007/s10915-014-9890-5 db/journals/jscic/jscic63.html#WilcoxSBG15

Tobin Isaac Carsten Burstedde Lucas C. Wilcox Omar Ghattas Recursive Algorithms for Distributed Forests of Octrees. 2015 37 SIAM J. Sci. Comput. 5 https://doi.org/10.1137/140970963 db/journals/siamsc/siamsc37.html#IsaacBWG15

Tobin Isaac Georg Stadler Omar Ghattas Solution of Nonlinear Stokes Equations Discretized By High-Order Finite Elements on Nonconforming and Anisotropic Meshes, with Application to Ice Sheet Dynamics. 2015 37 SIAM J. Sci. Comput. 6 https://doi.org/10.1137/140974407 db/journals/siamsc/siamsc37.html#IsaacSG15

Hari Sundar Omar Ghattas A Nested Partitioning Algorithm for Adaptive Meshes on Heterogeneous Clusters. 319-328 2015 ICS https://doi.org/10.1145/2751205.2751246 conf/ics/2015 db/conf/ics/ics2015.html#SundarG15 Johann Rudi A. Cristiano I. Malossi Tobin Isaac Georg Stadler Michael Gurnis Peter W. J. Staar Yves Ineichen Costas Bekas Alessandro Curioni Omar Ghattas An extreme-scale implicit solver for complex PDEs: highly heterogeneous flow in earth's mantle. 5:1-5:12 2015 SC https://doi.org/10.1145/2807591.2807675 conf/sc/2015 db/conf/sc/sc2015.html#RudiMISGSIBCG15

Tan Bui-Thanh Omar Ghattas An Analysis of Infinite Dimensional Bayesian Inverse Shape Acoustic Scattering and Its Numerical Approximation. 203-222 2014 2 SIAM/ASA J. Uncertain. Quantification 1 https://doi.org/10.1137/120894877 db/journals/juq/juq2.html#Bui-ThanhG14

Noemi Petra James Martin Georg Stadler Omar Ghattas A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems, Part II: Stochastic Newton MCMC with Application to Ice Sheet Flow Inverse Problems. 2014 36 SIAM J. Sci. Comput. 4 https://doi.org/10.1137/130934805 db/journals/siamsc/siamsc36.html#PetraMSG14

Alen Alexanderian Noemi Petra Georg Stadler Omar Ghattas A-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems with Regularized ℓ<sub>0</sub>-Sparsification. 2014 36 SIAM J. Sci. Comput. 5 https://doi.org/10.1137/130933381 db/journals/siamsc/siamsc36.html#AlexanderianPSG14

Tobin Isaac Carsten Burstedde Lucas C. Wilcox Omar Ghattas Recursive Algorithms for Distributed Forests of Octrees. 2014 abs/1406.0089 CoRR http://arxiv.org/abs/1406.0089 db/journals/corr/corr1406.html#IsaacBWG14

Tobin Isaac Georg Stadler Omar Ghattas Solution of nonlinear Stokes equations discretized by high-order finite elements on nonconforming and anisotropic meshes, with application to ice sheet dynamics. 2014 abs/1406.6573 CoRR http://arxiv.org/abs/1406.6573 db/journals/corr/corr1406.html#IsaacSG14

Tan Bui-Thanh Leszek F. Demkowicz Omar Ghattas Constructively well-posed approximation methods with unity inf-sup and continuity constants for partial differential equations. 2013 82 Math. Comput. 284 https://doi.org/10.1090/S0025-5718-2013-02697-X db/journals/moc/moc82.html#Bui-ThanhDG13 1923-1952

Tan Bui-Thanh Leszek F. Demkowicz Omar Ghattas A Unified Discontinuous Petrov-Galerkin Method and Its Analysis for Friedrichs' Systems. 1933-1958 2013 51 SIAM J. Numer. Anal. 4 https://doi.org/10.1137/110854369 db/journals/siamnum/siamnum51.html#Bui-ThanhDG13

Tan Bui-Thanh Omar Ghattas James Martin Georg Stadler A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems Part I: The Linearized Case, with Application to Global Seismic Inversion. 2013 35 SIAM J. Sci. Comput. 6 https://doi.org/10.1137/12089586X db/journals/siamsc/siamsc35.html#Bui-ThanhGMS13

Jesse Kelly Omar Ghattas Hari Sundar A Nested Partitioning Scheme for Parallel Heterogeneous Clusters. 2013 CoRR http://arxiv.org/abs/1307.4731 abs/1307.4731 db/journals/corr/corr1307.html#KellyGS13

Tan Bui-Thanh Omar Ghattas Analysis of an hp-Nonconforming Discontinuous Galerkin Spectral Element Method for Wave Propagation. 1801-1826 2012 50 SIAM J. Numer. Anal. 3 https://doi.org/10.1137/110828010 db/journals/siamnum/siamnum50.html#Bui-ThanhG12

James Martin Lucas C. Wilcox Carsten Burstedde Omar Ghattas A Stochastic Newton MCMC Method for Large-Scale Statistical Inverse Problems with Application to Seismic Inversion. 2012 34 SIAM J. Sci. Comput. 3 https://doi.org/10.1137/110845598 db/journals/siamsc/siamsc34.html#MartinWBG12

Tan Bui-Thanh Omar Ghattas David Higdon Adaptive Hessian-Based Nonstationary Gaussian Process Response Surface Method for Probability Density Approximation with Application to Bayesian Solution of Large-Scale Inverse Problems. 2012 34 SIAM J. Sci. Comput. 6 https://doi.org/10.1137/110851419 db/journals/siamsc/siamsc34.html#Bui-ThanhGH12

Tobin Isaac Carsten Burstedde Omar Ghattas Low-Cost Parallel Algorithms for 2: 1 Octree Balance. 426-437 2012 IPDPS https://doi.org/10.1109/IPDPS.2012.47 https://doi.ieeecomputersociety.org/10.1109/IPDPS.2012.47 conf/ipps/2012 db/conf/ipps/ipdps2012.html#IsaacBG12 Tan Bui-Thanh Carsten Burstedde Omar Ghattas James Martin Georg Stadler Lucas C. Wilcox Extreme-scale UQ for Bayesian inverse problems governed by PDEs. 3 2012 SC https://doi.org/10.1109/SC.2012.56 https://doi.ieeecomputersociety.org/10.1109/SC.2012.56 http://dl.acm.org/citation.cfm?id=2389000 conf/sc/2012 db/conf/sc/sc2012.html#Bui-ThanhBGMSW12 Hari Sundar George Biros Carsten Burstedde Johann Rudi Omar Ghattas Georg Stadler Parallel geometric-algebraic multigrid on unstructured forests of octrees. 43 2012 SC https://doi.org/10.1109/SC.2012.91 https://doi.ieeecomputersociety.org/10.1109/SC.2012.91 http://dl.acm.org/citation.cfm?id=2389055 conf/sc/2012 db/conf/sc/sc2012.html#SundarBBRGS12 Douglas L. Allaire George Biros J. Chambers Omar Ghattas D. Kordonowy Karen Willcox Dynamic Data Driven Methods for Self-aware Aerospace Vehicles. 1206-1210 2012 conf/iccS/2012 ICCS https://doi.org/10.1016/j.procs.2012.04.130 db/journals/procedia/procedia9.html#AllaireBCGKW12

Shan Yang Georg Stadler Robert D. Moser Omar Ghattas A Shape Hessian-Based Boundary Roughness Analysis of Navier-Stokes Flow. 333-355 2011 71 SIAM J. Appl. Math. 1 https://doi.org/10.1137/100796789 db/journals/siamam/siamam71.html#YangSMG11

H. P. Flath Lucas C. Wilcox Volkan Akcelik Judith C. Hill Bart G. van Bloemen Waanders Omar Ghattas Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations. 407-432 2011 33 SIAM J. Sci. Comput. 1 https://doi.org/10.1137/090780717 db/journals/siamsc/siamsc33.html#FlathWAHWG11

Carsten Burstedde Lucas C. Wilcox Omar Ghattas p4est: Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees. 1103-1133 2011 33 SIAM J. Sci. Comput. 3 https://doi.org/10.1137/100791634 db/journals/siamsc/siamsc33.html#BursteddeWG11

Lucas C. Wilcox Georg Stadler Carsten Burstedde Omar Ghattas A high-order discontinuous Galerkin method for wave propagation through coupled elastic-acoustic media. 9373-9396 2010 229 J. Comput. Phys. 24 https://doi.org/10.1016/j.jcp.2010.09.008 db/journals/jcphy/jcphy229.html#WilcoxSBG10

Chad Lieberman Karen Willcox Omar Ghattas Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems. 2523-2542 2010 32 SIAM J. Sci. Comput. 5 https://doi.org/10.1137/090775622 db/journals/siamsc/siamsc32.html#LiebermanWG10

Isabel N. Figueiredo Pedro N. Figueiredo Georg Stadler Omar Ghattas Adérito Araújo Variational Image Segmentation for Endoscopic Human Colonic Aberrant Crypt Foci. 998-1011 2010 29 IEEE Trans. Medical Imaging 4 https://doi.org/10.1109/TMI.2009.2036258 https://www.wikidata.org/entity/Q51774637 db/journals/tmi/tmi29.html#FigueiredoFSGA10

Carsten Burstedde Omar Ghattas Michael Gurnis Tobin Isaac Georg Stadler Tim Warburton Lucas C. Wilcox Extreme-Scale AMR. 1-12 2010 SC https://doi.org/10.1109/SC.2010.25 https://doi.ieeecomputersociety.org/10.1109/SC.2010.25 http://dl.acm.org/citation.cfm?id=1884645 conf/sc/2010 db/conf/sc/sc2010.html#BursteddeGGISWW10

Tan Bui-Thanh Karen Willcox Omar Ghattas Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space. 3270-3288 2008 30 SIAM J. Sci. Comput. 6 https://doi.org/10.1137/070694855 db/journals/siamsc/siamsc30.html#Bui-ThanhWG08

Carsten Burstedde Omar Ghattas Michael Gurnis Georg Stadler Eh Tan Tiankai Tu Lucas C. Wilcox Shijie Zhong Scalable adaptive mantle convection simulation on petascale supercomputers. 62 2008 SC https://doi.org/10.1109/SC.2008.5214248 https://dl.acm.org/citation.cfm?id=1413434 conf/sc/2008 db/conf/sc/sc2008.html#BursteddeGGSTTWZ08

Tan Bui-Thanh Karen Willcox Omar Ghattas Bart G. van Bloemen Waanders Goal-oriented, model-constrained optimization for reduction of large-scale systems. 880-896 2007 224 J. Comput. Phys. 2 https://doi.org/10.1016/j.jcp.2006.10.026 db/journals/jcphy/jcphy224.html#Bui-ThanhWGW07

Omar Bashir Omar Ghattas Judith C. Hill Bart G. van Bloemen Waanders Karen Willcox Hessian-Based Model Reduction for Large-Scale Data Assimilation Problems. 1010-1017 2007 conf/iccS/2007-1 International Conference on Computational Science (1) https://doi.org/10.1007/978-3-540-72584-8_133 db/conf/iccS/iccS2007-1.html#BashirGHWW07 Volkan Akcelik George Biros Andrei Draganescu Omar Ghattas Judith C. Hill Bart G. van Bloemen Waanders Inversion of Airborne Contaminants in a Regional Model. 481-488 2006 conf/iccS/2006-3 International Conference on Computational Science (3) https://doi.org/10.1007/11758532_64 db/conf/iccS/iccS2006-3.html#AkcelikBDGHW06 Tiankai Tu Hongfeng Yu 0001 Leonardo Ramírez-Guzmán Jacobo Bielak Omar Ghattas Kwan-Liu Ma David R. O'Hallaron Scalable systems software - From mesh generation to scientific visualization: an end-to-end approach to parallel supercomputing. 91 2006 conf/sc/2006 SC https://doi.org/10.1145/1188455.1188551 https://doi.org/10.1109/SC.2006.32 https://doi.ieeecomputersociety.org/10.1109/SC.2006.32 db/conf/sc/sc2006.html#TuYRBGMO06 Tiankai Tu Hongfeng Yu 0001 Jacobo Bielak Omar Ghattas Julio C. López 0001 Kwan-Liu Ma David R. O'Hallaron Leonardo Ramírez-Guzmán Nathan Stone Ricardo Taborda-Rios John Urbanic Analytics challenge - Remote runtime steering of integrated terascale simulation and visualization. 297 2006 conf/sc/2006 SC https://doi.org/10.1145/1188455.1188767 https://www.wikidata.org/entity/Q60699618 db/conf/sc/sc2006.html#TuYBGLMORSTU06 Volkan Akçelik George Biros Omar Ghattas Judith Hill David E. Keyes Bart G. van Bloemen Waanders Parallel Algorithms for PDE-Constrained Optimization. 291-322 2006 Parallel Processing for Scientific Computing https://doi.org/10.1137/1.9780898718133.ch16 books/siam/06/HRS2006 db/books/collections/HRS2006.html#AkcelikBGHKW06

George Biros Omar Ghattas Parallel Lagrange-Newton-Krylov-Schur Methods for PDE-Constrained Optimization. Part I: The Krylov-Schur Solver. 687-713 2005 27 SIAM J. Sci. Comput. 2 https://doi.org/10.1137/S106482750241565X db/journals/siamsc/siamsc27.html#BirosG05

George Biros Omar Ghattas Parallel Lagrange-Newton-Krylov-Schur Methods for PDE-Constrained Optimization. Part II: The Lagrange-Newton Solver and Its Application to Optimal Control of Steady Viscous Flows. 714-739 2005 27 SIAM J. Sci. Comput. 2 https://doi.org/10.1137/S1064827502415661 db/journals/siamsc/siamsc27.html#BirosG05a

Karen Willcox Omar Ghattas Bart G. van Bloemen Waanders Brett W. Bader An Optimization Frame work for Goal-Oriented, Model-Based Reduction of Large-Scale Systems. 2265-2271 2005 CDC/ECC https://doi.org/10.1109/CDC.2005.1582499 conf/cdc/2005 db/conf/cdc/cdc2005.html#WillcoxGWB05 Tiankai Tu David R. O'Hallaron Omar Ghattas Scalable Parallel Octree Meshing for TeraScale Applications. 4 2005 conf/sc/2005 SC https://doi.org/10.1109/SC.2005.61 https://doi.ieeecomputersociety.org/10.1109/SC.2005.61 http://dl.acm.org/citation.cfm?id=1105769 db/conf/sc/sc2005.html#TuOG05 Volkan Akcelik George Biros Andrei Draganescu Judith C. Hill Omar Ghattas Bart G. van Bloemen Waanders Dynamic Data-Driven Inversion For Terascale Simulations: Real-Time Identification Of Airborne Contaminants. 43 2005 conf/sc/2005 SC https://doi.org/10.1109/SC.2005.25 https://doi.ieeecomputersociety.org/10.1109/SC.2005.25 http://dl.acm.org/citation.cfm?id=1105809 db/conf/sc/sc2005.html#AkcelikBDHGW05 Volkan Akcelik Jacobo Bielak George Biros Ioannis Epanomeritakis Omar Ghattas Loukas F. Kallivokas Eui Joong Kim A Framework for Online Inversion-Based 3D Site Characterization. 717-724 https://doi.org/10.1007/978-3-540-24688-6_93 2004 conf/iccS/2004-3 International Conference on Computational Science db/conf/iccS/iccS2004-3.html#AkcelikBBEGKK04 Kwan-Liu Ma Aleksander Stompel Jacobo Bielak Omar Ghattas Eui Joong Kim Visualizing Very Large-Scale Earthquake Simulations. 48 2003 conf/sc/2003 SC https://doi.org/10.1145/1048935.1050198 https://doi.ieeecomputersociety.org/10.1109/SC.2003.10026 db/conf/sc/sc2003.html#MaSBGK03 Volkan Akcelik Jacobo Bielak George Biros Ioannis Epanomeritakis Antonio Fernandez Omar Ghattas Eui Joong Kim Julio C. López 0001 David R. O'Hallaron Tiankai Tu John Urbanic High Resolution Forward And Inverse Earthquake Modeling on Terascale Computers. 52 2003 conf/sc/2003 SC https://doi.org/10.1145/1048935.1050202 https://doi.ieeecomputersociety.org/10.1109/SC.2003.10056 db/conf/sc/sc2003.html#AkcelikBBEFGKLOTU03 Volkan Akcelik George Biros Omar Ghattas Parallel multiscale Gauss-Newton-Krylov methods for inverse wave propagation. 67:1-67:15 2002 conf/sc/2002 SC https://doi.org/10.1109/SC.2002.10002 https://doi.ieeecomputersociety.org/10.1109/SC.2002.10002 http://dl.acm.org/citation.cfm?id=762827 db/conf/sc/sc2002.html#AkcelikBG02

Srinivas Bollapragada Omar Ghattas John N. Hooker Optimal Design of Truss Structures by Logic-Based Branch and Cut. 42-51 2001 49 Oper. Res. 1 https://doi.org/10.1287/opre.49.1.42.11196 db/journals/ior/ior49.html#BollapragadaGH01

James F. Antaki Guy E. Blelloch Omar Ghattas Ivan Malcevic Gary L. Miller Noel Walkington A Parallel Dynamic-Mesh Lagrangian Method for Simulation of Flows with Dynamic Interfaces. 2000 conf/sc/2000 SC https://doi.org/10.1109/SC.2000.10045 https://doi.ieeecomputersociety.org/10.1109/SC.2000.10045 http://dl.acm.org/citation.cfm?id=370394 db/conf/sc/sc2000.html#AntakiBGMMW00 26 George Biros Omar Ghattas Parallel Netwon-Krylov Methods for PDE-Constrained Optimization. 28 1999 SC https://doi.org/10.1145/331532.331560 https://doi.ieeecomputersociety.org/10.1109/SC.1999.10036 conf/sc/1999 db/conf/sc/sc1999.html#BirosG99 R. V. O'Toole III David A. Simon Branislav Jaramaz Omar Ghattas Mike Blackwell Loukas F. Kallivokas F. Morgan Christopher D. Visnic Anthony M. DiGioia Takeo Kanade Towards More Capable and Less Invasive Robotic Surgery in Orthopaedics. 123-130 1995 conf/cvrmed/1995 CVRMed db/conf/cvrmed/cvrmed1995.html#OTooleSJGBKMVDK95 https://doi.org/10.1007/978-3-540-49197-2_14 Christopher D. Visnic Robert H. Reid Omar Ghattas Anthony M. DiGioia Branislav Jaramaz Finite element pre-operative simulation of cementless hip replacement. 856-860 1994 conf/wsc/1994 WSC https://doi.org/10.1109/WSC.1994.717445 http://dl.acm.org/citation.cfm?id=194411 db/conf/wsc/wsc1994.html#VisnicRGDJ94 George Turkiyyah Omar Ghattas Geometric Reasoning for Shape Design. 874-879 1991 conf/aaai/1991-2 AAAI db/conf/aaai/aaai91-2.html#TurkiyyahG91 http://www.aaai.org/Library/AAAI/1991/aaai91-136.php Volkan AkcelikVolkan Akçelik Alen Alexanderian Nick Alger Amal Alghamdi Douglas L. Allaire Ilona Ambartsumyan James F. Antaki Adérito Araújo Hassan Ashtiani Brett W. Bader Ricardo Baptista Omar Bashir Costas Bekas Jacobo Bielak George Biros Mike Blackwell Guy E. Blelloch Srinivas Bollapragada Wajih Halim Boukaram Michael Brennan Tan Bui-Thanh Hans-Joachim Bungartz Carsten Burstedde John Camier Lianghao Cao J. Chambers Anirban Chaudhuri Jingyi Chen Joshua Chen Peng Chen 0024 Blake Christierson Noel Clemens James Corones Evin Cramer James Crowley Alessandro Curioni Peter Dayan Leszek F. Demkowicz Amir Dezfouli Anthony M. DiGioia Veselin Dobrev Andrei Draganescu Xiaosong Du Ioannis Epanomeritakis R. Todd Evans Antonio Fernandez Milinda Fernando Isabel N. Figueiredo Pedro N. Figueiredo H. P. Flath Alice-Agnes Gabriel Longfei Gao Xindi Gong Max D. Gunzburger Michael Gurnis Michael R. Haberman Michael Hanke 0001 Robert J. Harrison Tucker Hartland Patrick Heimbach Stefan Henneking Michael A. Heroux Marc Andre Hesse Jan S. Hesthaven David Higdon Judith Hill Judith C. Hill Eric W. Hirschmann John N. Hooker Mathew Hu Yves Ineichen Tobin Isaac Branislav Jaramaz Prashant K. Jha Peter K. Jimack Chris Johnson Kirk E. Jordan Loukas F. Kallivokas Takeo Kanade Wajih Bou Karam Ian Karlin Jesse Kelly David E. Keyes Eui Joong Kim Kitae KimKi-Tae Kim Joseph Kirchhoff Tzanio V. Kolev D. Kordonowy Nikola B. Kovachki Rolf KrauseRolf H. Krause Vipin Kumar Fabian Kutschera Jeonghun J. Lee Alex Leviyev Fengyi Li Chad Lieberman Julio C. López 0001 Dingcheng Luo Kwan-Liu Ma Ivan Malcevic Cristiano MalossiA. Cristiano I. Malossi James Martin Joaquim R. R. A. Martins Youssef Marzouk 0001Youssef M. Marzouk Stefan Mayer Lois C. McInnesLois Curfman McInnes Juan Meza Gary L. Miller Tommy Minyard F. Morgan Knut Martin Mørken Robert D. Moser Aaron Myers Rami Nammour David Neilsen Ruanui Nicholson Richard Nock J. Tinsley Oden David R. O'Hallaron Thomas O'Leary-RoseberryTom O'Leary-Roseberry Cheng Soon Ong R. V. O'Toole III Dhabaleswar K. Panda 0001 Matthew D. Parno Noemi PetraNoémi Petra Linda R. Petzold Julie Pham Padma Raghavan Leonardo Ramírez-Guzmán Vishwas Rao Robert H. Reid Ulrich Rüde Johann Rudi Suzanne M. Shontz David A. Simon Peter W. J. Staar Georg Stadler Daniel C. Stanzione Jr.Dan Stanzione Hans De Sterck Aleksander Stompel Nathan Stone Hari Sundar Katarzyna SwirydowiczKasia Swirydowicz Ricardo Taborda-Rios Eh Tan Anne E. Trefethen Jiqun Tu Tiankai Tu George M. TurkiyyahGeorge Turkiyyah Peter R. Turner John Urbanic Sreeram Venkat Umberto Villa Christopher D. Visnic Vladimir V. Voevodin Bart G. van Bloemen Waanders Noel Walkington Kainan Wang Yifei Wang 0005 Timothy C. WarburtonTim Warburton John West 0001 Lucas C. Wilcox Karen WillcoxKaren E. Willcox Barbara I. Wohlmuth Noah Wolfe Carol S. Woodward Keyi Wu Shan Yang Boyuan Yao Hongfeng Yu 0001 Stefano Zampini Shijie Zhong Aaron Zimmerman Yosef Zlochower