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Omar Ghattas
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- affiliation: University of Texas at Austin, USA
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2020 – today
- 2024
- [j52]Thomas O'Leary-Roseberry
, Peng Chen, Umberto Villa, Omar Ghattas:
Derivative-Informed Neural Operator: An efficient framework for high-dimensional parametric derivative learning. J. Comput. Phys. 496: 112555 (2024) - [j51]Ricardo Baptista, Lianghao Cao
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport. J. Comput. Phys. 503: 112844 (2024) - [j50]Nick Alger, Tucker Hartland, Noemi Petra
Point Spread Function Approximation of High-Rank Hessians with Locally Supported Nonnegative Integral Kernels. SIAM J. Sci. Comput. 46(3): 1658- (2024) - [i35]Lianghao Cao, Thomas O'Leary-Roseberry, Omar Ghattas:
Efficient geometric Markov chain Monte Carlo for nonlinear Bayesian inversion enabled by derivative-informed neural operators. CoRR abs/2403.08220 (2024) - [i34]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. CoRR abs/2407.13066 (2024) - [i33]Dingcheng Luo, Joshua Chen, Peng Chen, Omar Ghattas:
Gaussian mixture Taylor approximations of risk measures constrained by PDEs with Gaussian random field inputs. CoRR abs/2408.06615 (2024) - [i32]Joseph Kirchhoff, Dingcheng Luo, Thomas O'Leary-Roseberry, Omar Ghattas:
Inference of Heterogeneous Material Properties via Infinite-Dimensional Integrated DIC. CoRR abs/2408.10217 (2024) - [i31]Julie Pham, Omar Ghattas, Noel Clemens, Karen Willcox:
Real-time aerodynamic load estimation for hypersonics via strain-based inverse maps. CoRR abs/2408.15286 (2024) - 2023
- [j49]Jeonghun J. Lee
Interior over-penalized enriched Galerkin methods for second order elliptic equations. Comput. Math. Appl. 152: 102-111 (2023) - [j48]Dingcheng Luo
Optimal design of chemoepitaxial guideposts for the directed self-assembly of block copolymer systems using an inexact Newton algorithm. J. Comput. Phys. 485: 112101 (2023) - [j47]Lianghao Cao
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems. J. Comput. Phys. 486: 112104 (2023) - [j46]Keyi Wu
Large-Scale Bayesian Optimal Experimental Design with Derivative-Informed Projected Neural Network. J. Sci. Comput. 95(1): 30 (2023) - [j45]Keyi Wu, Peng Chen, Omar Ghattas:
A Fast and Scalable Computational Framework for Large-Scale High-Dimensional Bayesian Optimal Experimental Design. SIAM/ASA J. Uncertain. Quantification 11(1): 235-261 (2023) - [j44]Keyi Wu, Peng Chen, Omar Ghattas:
An Offline-Online Decomposition Method for Efficient Linear Bayesian Goal-Oriented Optimal Experimental Design: Application to Optimal Sensor Placement. SIAM J. Sci. Comput. 45(1): 57- (2023) - [j43]Ki-Tae Kim
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty. ACM Trans. Math. Softw. 49(2): 17:1-17:31 (2023) - [i30]Dingcheng Luo, Thomas O'Leary-Roseberry, Peng Chen, Omar Ghattas:
Efficient PDE-Constrained optimization under high-dimensional uncertainty using derivative-informed neural operators. CoRR abs/2305.20053 (2023) - [i29]Lianghao Cao, Keyi Wu, J. Tinsley Oden, Peng Chen, Omar Ghattas:
Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data. CoRR abs/2306.05398 (2023) - [i28]Nick Alger, Tucker Hartland, Noemi Petra, Omar Ghattas:
Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels. CoRR abs/2307.03349 (2023) - 2022
- [j42]Jeonghun J. Lee
Forward and inverse modeling of fault transmissibility in subsurface flows. Comput. Math. Appl. 128: 354-367 (2022) - [j41]Lianghao Cao
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. SIAM J. Sci. Comput. 44(1): 51- (2022) - [c30]Milinda Fernando, David Neilsen, Eric W. Hirschmann, Yosef Zlochower, Hari Sundar, Omar Ghattas, George Biros:
A GPU-Accelerated AMR Solver for Gravitational Wave Propagation. SC 2022: 75:1-75:15 - [i27]Keyi Wu, Thomas O'Leary-Roseberry, Peng Chen, Omar Ghattas:
Derivative-informed projected neural network for large-scale Bayesian optimal experimental design. CoRR abs/2201.07925 (2022) - [i26]Alex Leviyev, Joshua Chen, Yifei Wang, Omar Ghattas, Aaron Zimmerman:
A stochastic Stein Variational Newton method. CoRR abs/2204.09039 (2022) - [i25]Thomas O'Leary-Roseberry, Peng Chen, Umberto Villa, Omar Ghattas:
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning. CoRR abs/2206.10745 (2022) - [i24]Dingcheng Luo, Lianghao Cao, Peng Chen, Omar Ghattas, J. Tinsley Oden:
Optimal design of chemoepitaxial guideposts for directed self-assembly of block copolymer systems using an inexact-Newton algorithm. CoRR abs/2208.01193 (2022) - [i23]Jeonghun J. Lee, Omar Ghattas:
Interior over-stabilized enriched Galerkin methods for second order elliptic equations. CoRR abs/2208.09969 (2022) - [i22]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. CoRR abs/2210.03008 (2022) - 2021
- [j40]Omar Ghattas, Karen Willcox:
Learning physics-based models from data: perspectives from inverse problems and model reduction. Acta Numer. 30: 445-554 (2021) - [j39]Peng Chen, Michael R. Haberman, Omar Ghattas:
Optimal design of acoustic metamaterial cloaks under uncertainty. J. Comput. Phys. 431: 110114 (2021) - [j38]Peng Chen, Omar Ghattas:
Taylor Approximation for Chance Constrained Optimization Problems Governed by Partial Differential Equations with High-Dimensional Random Parameters. SIAM/ASA J. Uncertain. Quantification 9(4): 1381-1410 (2021) - [j37]Karen E. Willcox
The imperative of physics-based modeling and inverse theory in computational science. Nat. Comput. Sci. 1(3): 166-168 (2021) - [j36]Peng Chen
Stein Variational Reduced Basis Bayesian Inversion. SIAM J. Sci. Comput. 43(2): A1163-A1193 (2021) - [j35]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. ACM Trans. Math. Softw. 47(2): 16:1-16:34 (2021) - [i21]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. CoRR abs/2102.04577 (2021) - [i20]Keyi Wu, Peng Chen, Omar Ghattas:
A fast and scalable computational framework for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placement. CoRR abs/2102.06627 (2021) - [i19]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. CoRR abs/2112.00713 (2021) - [i18]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. CoRR abs/2112.07096 (2021) - 2020
- [j34]Ilona Ambartsumyan, Wajih Halim Boukaram, Tan Bui-Thanh
Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs. SIAM J. Sci. Comput. 42(5): A3397-A3426 (2020) - [j33]Nick Alger, Peng Chen, Omar Ghattas:
Tensor Train Construction From Tensor Actions, With Application to Compression of Large High Order Derivative Tensors. SIAM J. Sci. Comput. 42(5): A3516-A3539 (2020) - [c29]Peng Chen, Omar Ghattas:
Projected Stein Variational Gradient Descent. NeurIPS 2020 - [c28]Dan Stanzione
Frontera: The Evolution of Leadership Computing at the National Science Foundation. PEARC 2020: 106-111 - [i17]Thomas O'Leary-Roseberry, Nick Alger, Omar Ghattas:
Low Rank Saddle Free Newton: Algorithm and Analysis. CoRR abs/2002.02881 (2020) - [i16]Thomas O'Leary-Roseberry, Omar Ghattas:
Ill-Posedness and Optimization Geometry for Nonlinear Neural Network Training. CoRR abs/2002.02882 (2020) - [i15]Peng Chen, Omar Ghattas:
Projected Stein Variational Gradient Descent. CoRR abs/2002.03469 (2020) - [i14]Nick Alger, Peng Chen, Omar Ghattas:
Tensor train construction from tensor actions, with application to compression of large high order derivative tensors. CoRR abs/2002.06244 (2020) - [i13]Amal Alghamdi, Marc Andre Hesse, Jingyi Chen, Omar Ghattas:
Bayesian Poroelastic Aquifer Characterization from InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate. CoRR abs/2002.10706 (2020) - [i12]Peng Chen, Omar Ghattas:
Stein variational reduced basis Bayesian inversion. CoRR abs/2002.10924 (2020) - [i11]Ilona Ambartsumyan, Wajih Bou Karam, Tan Bui-Thanh, Omar Ghattas, David E. Keyes
Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs. CoRR abs/2003.10173 (2020) - [i10]Keyi Wu, Peng Chen, Omar Ghattas:
A fast and scalable computational framework for large-scale and high-dimensional Bayesian optimal experimental design. CoRR abs/2010.15196 (2020) - [i9]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. CoRR abs/2010.15271 (2020) - [i8]Thomas O'Leary-Roseberry, Umberto Villa, Peng Chen, Omar Ghattas:
Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs. CoRR abs/2011.15110 (2020) - [i7]Longfei Gao, Omar Ghattas, David E. Keyes
Energy-conserving 3D elastic wave simulation with finite difference discretization on staggered grids with nonconforming interfaces. CoRR abs/2012.13863 (2020)
2010 – 2019
- 2019
- [j32]Peng Chen
Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty. J. Comput. Phys. 385: 163-186 (2019) - [j31]Nick Alger, Vishwas Rao, Aaron Myers, Tan Bui-Thanh
Scalable Matrix-Free Adaptive Product-Convolution Approximation for Locally Translation-Invariant Operators. SIAM J. Sci. Comput. 41(4): A2296-A2328 (2019) - [c27]Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong:
Disentangled behavioural representations. NeurIPS 2019: 2251-2260 - [c26]Peng Chen, Keyi Wu, Joshua Chen, Tom O'Leary-Roseberry, Omar Ghattas:
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions. NeurIPS 2019: 15104-15113 - [i6]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. CoRR abs/1909.03948 (2019) - 2018
- [j30]Umberto Villa, Noemi Petra, Omar Ghattas:
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems. J. Open Source Softw. 3(30): 940 (2018) - [j29]Kainan Wang, Tan Bui-Thanh
A Randomized Maximum A Posteriori Method for Posterior Sampling of High Dimensional Nonlinear Bayesian Inverse Problems. SIAM J. Sci. Comput. 40(1) (2018) - 2017
- [j28]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. SIAM/ASA J. Uncertain. Quantification 5(1): 1166-1192 (2017) - [j27]Nick Alger, Umberto Villa
A Data Scalable Augmented Lagrangian KKT Preconditioner for Large-Scale Inverse Problems. SIAM J. Sci. Comput. 39(5) (2017) - [j26]Johann Rudi
Weighted BFBT Preconditioner for Stokes Flow Problems with Highly Heterogeneous Viscosity. SIAM J. Sci. Comput. 39(5) (2017) - 2016
- [j25]Alen Alexanderian
A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems. SIAM J. Sci. Comput. 38(1) (2016) - [c25]Omar Ghattas, Tobin Isaac, Noémi Petra, Georg Stadler:
Scalable Algorithms for Bayesian Inference of Large-Scale Models from Large-Scale Data. VECPAR 2016: 3-6 - [i5]Johann Rudi
Weighted BFBT Preconditioner for Stokes Flow Problems with Highly Heterogeneous Viscosity. CoRR abs/1607.03936 (2016) - [i4]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, 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. CoRR abs/1610.02608 (2016) - 2015
- [j24]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. J. Comput. Phys. 296: 348-368 (2015) - [j23]Lucas C. Wilcox, Georg Stadler, Tan Bui-Thanh
Discretely Exact Derivatives for Hyperbolic PDE-Constrained Optimization Problems Discretized by the Discontinuous Galerkin Method. J. Sci. Comput. 63(1): 138-162 (2015) - [j22]Tobin Isaac
Recursive Algorithms for Distributed Forests of Octrees. SIAM J. Sci. Comput. 37(5) (2015) - [j21]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. SIAM J. Sci. Comput. 37(6) (2015) - [c24]Hari Sundar, Omar Ghattas:
A Nested Partitioning Algorithm for Adaptive Meshes on Heterogeneous Clusters. ICS 2015: 319-328 - [c23]Johann Rudi
An extreme-scale implicit solver for complex PDEs: highly heterogeneous flow in earth's mantle. SC 2015: 5:1-5:12 - 2014
- [j20]Tan Bui-Thanh
An Analysis of Infinite Dimensional Bayesian Inverse Shape Acoustic Scattering and Its Numerical Approximation. SIAM/ASA J. Uncertain. Quantification 2(1): 203-222 (2014) - [j19]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. SIAM J. Sci. Comput. 36(4) (2014) - [j18]Alen Alexanderian
A-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems with Regularized ℓ0-Sparsification. SIAM J. Sci. Comput. 36(5) (2014) - [i3]Tobin Isaac, Carsten Burstedde, Lucas C. Wilcox, Omar Ghattas:
Recursive Algorithms for Distributed Forests of Octrees. CoRR abs/1406.0089 (2014) - [i2]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. CoRR abs/1406.6573 (2014) - 2013
- [j17]Tan Bui-Thanh, Leszek F. Demkowicz, Omar Ghattas:
Constructively well-posed approximation methods with unity inf-sup and continuity constants for partial differential equations. Math. Comput. 82(284): 1923-1952 (2013) - [j16]Tan Bui-Thanh
A Unified Discontinuous Petrov-Galerkin Method and Its Analysis for Friedrichs' Systems. SIAM J. Numer. Anal. 51(4): 1933-1958 (2013) - [j15]Tan Bui-Thanh
A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems Part I: The Linearized Case, with Application to Global Seismic Inversion. SIAM J. Sci. Comput. 35(6) (2013) - [i1]Jesse Kelly, Omar Ghattas, Hari Sundar:
A Nested Partitioning Scheme for Parallel Heterogeneous Clusters. CoRR abs/1307.4731 (2013) - 2012
- [j14]Tan Bui-Thanh
Analysis of an hp-Nonconforming Discontinuous Galerkin Spectral Element Method for Wave Propagation. SIAM J. Numer. Anal. 50(3): 1801-1826 (2012) - [j13]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. SIAM J. Sci. Comput. 34(3) (2012) - [j12]Tan Bui-Thanh
Adaptive Hessian-Based Nonstationary Gaussian Process Response Surface Method for Probability Density Approximation with Application to Bayesian Solution of Large-Scale Inverse Problems. SIAM J. Sci. Comput. 34(6) (2012) - [c22]Tobin Isaac
Low-Cost Parallel Algorithms for 2: 1 Octree Balance. IPDPS 2012: 426-437 - [c21]Tan Bui-Thanh
Extreme-scale UQ for Bayesian inverse problems governed by PDEs. SC 2012: 3 - [c20]Hari Sundar, George Biros, Carsten Burstedde, Johann Rudi
Parallel geometric-algebraic multigrid on unstructured forests of octrees. SC 2012: 43 - [c19]Douglas L. Allaire, George Biros, J. Chambers, Omar Ghattas, D. Kordonowy, Karen Willcox
Dynamic Data Driven Methods for Self-aware Aerospace Vehicles. ICCS 2012: 1206-1210 - 2011
- [j11]Shan Yang, Georg Stadler, Robert D. Moser
A Shape Hessian-Based Boundary Roughness Analysis of Navier-Stokes Flow. SIAM J. Appl. Math. 71(1): 333-355 (2011) - [j10]H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judith Hill
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations. SIAM J. Sci. Comput. 33(1): 407-432 (2011) - [j9]Carsten Burstedde, Lucas C. Wilcox, Omar Ghattas:
p4est: Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees. SIAM J. Sci. Comput. 33(3): 1103-1133 (2011) - 2010
- [j8]Lucas C. Wilcox, Georg Stadler, Carsten Burstedde, Omar Ghattas:
A high-order discontinuous Galerkin method for wave propagation through coupled elastic-acoustic media. J. Comput. Phys. 229(24): 9373-9396 (2010) - [j7]Chad Lieberman, Karen Willcox
Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems. SIAM J. Sci. Comput. 32(5): 2523-2542 (2010) - [j6]Isabel N. Figueiredo
Variational Image Segmentation for Endoscopic Human Colonic Aberrant Crypt Foci. IEEE Trans. Medical Imaging 29(4): 998-1011 (2010) - [c18]Carsten Burstedde, Omar Ghattas, Michael Gurnis, Tobin Isaac
Extreme-Scale AMR. SC 2010: 1-12
2000 – 2009
- 2008
- [j5]Tan Bui-Thanh
Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space. SIAM J. Sci. Comput. 30(6): 3270-3288 (2008) - [c17]Carsten Burstedde, Omar Ghattas, Michael Gurnis, Georg Stadler, Eh Tan
Scalable adaptive mantle convection simulation on petascale supercomputers. SC 2008: 62 - 2007
- [j4]Tan Bui-Thanh
Goal-oriented, model-constrained optimization for reduction of large-scale systems. J. Comput. Phys. 224(2): 880-896 (2007) - [c16]Omar Bashir, Omar Ghattas, Judith Hill
Hessian-Based Model Reduction for Large-Scale Data Assimilation Problems. International Conference on Computational Science (1) 2007: 1010-1017 - 2006
- [c15]Volkan Akcelik, George Biros, Andrei Draganescu, Omar Ghattas, Judith Hill
Inversion of Airborne Contaminants in a Regional Model. International Conference on Computational Science (3) 2006: 481-488 - [c14]Tiankai Tu, Hongfeng Yu, 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. SC 2006: 91 - [c13]Tiankai Tu, Hongfeng Yu, Jacobo Bielak, Omar Ghattas, Julio C. López, Kwan-Liu Ma, David R. O'Hallaron, Leonardo Ramírez-Guzmán, Nathan Stone, Ricardo Taborda-Rios
Analytics challenge - Remote runtime steering of integrated terascale simulation and visualization. SC 2006: 297 - [p1]Volkan Akçelik, George Biros, Omar Ghattas, Judith Hill, David E. Keyes, Bart G. van Bloemen Waanders:
Parallel Algorithms for PDE-Constrained Optimization. Parallel Processing for Scientific Computing 2006: 291-322 - 2005
- [j3]George Biros, Omar Ghattas:
Parallel Lagrange-Newton-Krylov-Schur Methods for PDE-Constrained Optimization. Part I: The Krylov-Schur Solver. SIAM J. Sci. Comput. 27(2): 687-713 (2005) - [j2]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. SIAM J. Sci. Comput. 27(2): 714-739 (2005) - [c12]Karen Willcox, Omar Ghattas, Bart G. van Bloemen Waanders
An Optimization Frame work for Goal-Oriented, Model-Based Reduction of Large-Scale Systems. CDC/ECC 2005: 2265-2271 - [c11]Tiankai Tu, David R. O'Hallaron, Omar Ghattas:
Scalable Parallel Octree Meshing for TeraScale Applications. SC 2005: 4 - [c10]Volkan Akcelik, George Biros, Andrei Draganescu, Judith Hill
Dynamic Data-Driven Inversion For Terascale Simulations: Real-Time Identification Of Airborne Contaminants. SC 2005: 43 - 2004
- [c9]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. International Conference on Computational Science 2004: 717-724 - 2003
- [c8]Kwan-Liu Ma, Aleksander Stompel, Jacobo Bielak, Omar Ghattas, Eui Joong Kim:
Visualizing Very Large-Scale Earthquake Simulations. SC 2003: 48 - [c7]Volkan Akcelik, Jacobo Bielak, George Biros, Ioannis Epanomeritakis, Antonio Fernandez, Omar Ghattas, Eui Joong Kim, Julio C. López, David R. O'Hallaron, Tiankai Tu, John Urbanic:
High Resolution Forward And Inverse Earthquake Modeling on Terascale Computers. SC 2003: 52 - 2002
- [c6]Volkan Akcelik, George Biros, Omar Ghattas:
Parallel multiscale Gauss-Newton-Krylov methods for inverse wave propagation. SC 2002: 67:1-67:15 - 2001
- [j1]Srinivas Bollapragada, Omar Ghattas, John N. Hooker:
Optimal Design of Truss Structures by Logic-Based Branch and Cut. Oper. Res. 49(1): 42-51 (2001) - 2000
- [c5]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. SC 2000: 26
1990 – 1999
- 1999
- [c4]George Biros, Omar Ghattas:
Parallel Netwon-Krylov Methods for PDE-Constrained Optimization. SC 1999: 28 - 1995
- [c3]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. CVRMed 1995: 123-130 - 1994
- [c2]Christopher D. Visnic, Robert H. Reid, Omar Ghattas, Anthony M. DiGioia, Branislav Jaramaz:
Finite element pre-operative simulation of cementless hip replacement. WSC 1994: 856-860 - 1991
- [c1]George Turkiyyah, Omar Ghattas:
Geometric Reasoning for Shape Design. AAAI 1991: 874-879
Coauthor Index
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