Articole cu mandate pentru acces public - Omar GhattasAflați mai multe
Respinse: 4
Frontera: The evolution of leadership computing at the national science foundation
D Stanzione, J West, RT Evans, T Minyard, O Ghattas, DK Panda
Practice and Experience in Advanced Research Computing 2020: Catch the Wave …, 2020
Mandate: US National Science Foundation
Autori responsabili: D Stanzione
The imperative of physics-based modeling and inverse theory in computational science
KE Willcox, O Ghattas, P Heimbach
Nature Computational Science 1 (3), 166-168, 2021
Mandate: US National Science Foundation, US Department of Energy, US National …
Autori responsabili: KE Willcox
Taylor approximation for PDE‐constrained optimization under uncertainty: Application to turbulent jet flow
P Chen, U Villa, O Ghattas
PAMM 18 (1), e201800466, 2018
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Autori responsabili: P Chen
From data to decisions: A real-time measurement–inversion–prediction–steering framework for hazardous events and health monitoring
S Wogrin, A Singh, D Allaire, O Ghattas, K Willcox
Handbook of Dynamic Data Driven Applications Systems: Volume 2, 195-227, 2023
Mandate: US National Science Foundation, US Department of Defense, National Research …
Autori responsabili: K Willcox
Disponibile undeva: 56
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 …
T Isaac, N Petra, G Stadler, O Ghattas
Journal of Computational Physics 296, 348-368, 2015
Mandate: US Department of Energy
An extreme-scale implicit solver for complex PDEs: highly heterogeneous flow in earth's mantle
J Rudi, ACI Malossi, T Isaac, G Stadler, M Gurnis, PWJ Staar, Y Ineichen, ...
Proceedings of the international conference for high performance computing …, 2015
Mandate: US Department of Energy
Learning physics-based models from data: perspectives from inverse problems and model reduction
O Ghattas, K Willcox
Acta Numerica 30, 445-554, 2021
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Research and Education in Computational Science and Engineering
U Rude, K Willcox, L Curfman McInnes, H De Sterck, G Biros, H Bungartz, ...
SIAM Review 60 (3), 707-754, 2018
Mandate: US Department of Energy, US National Institutes of Health
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs: Part I: Deterministic Inversion and Linearized Bayesian Inference
U Villa, N Petra, O Ghattas
ACM Transactions on Mathematical Software (TOMS) 47 (2), 1-34, 2021
Mandate: US National Science Foundation, US Department of Defense
Recursive algorithms for distributed forests of octrees
T Isaac, C Burstedde, LC Wilcox, O Ghattas
SIAM Journal on Scientific Computing 37 (5), C497-C531, 2015
Mandate: US Department of Energy, German Research Foundation
Mean-variance risk-averse optimal control of systems governed by PDEs with random parameter fields using quadratic approximations
A Alexanderian, N Petra, G Stadler, O Ghattas
SIAM/ASA Journal on Uncertainty Quantification 5 (1), 1166-1192, 2017
Mandate: US National Science Foundation, US Department of Energy
On Bayesian A-and D-optimal experimental designs in infinite dimensions
A Alexanderian, PJ Gloor, O Ghattas
Bayesian Analysis 11 (3), 671-695, 2016
Mandate: US National Science Foundation, US Department of Energy
Projected Stein variational gradient descent
P Chen, O Ghattas
Advances in Neural Information Processing Systems 33, 2020
Mandate: US National Science Foundation, US Department of Energy
Solution of nonlinear Stokes equations discretized by high-order finite elements on nonconforming and anisotropic meshes, with application to ice sheet dynamics
T Isaac, G Stadler, O Ghattas
SIAM Journal on Scientific Computing 37 (6), B804-B833, 2015
Mandate: US Department of Energy
Derivative-informed projected neural networks for high-dimensional parametric maps governed by PDEs
T O’Leary-Roseberry, U Villa, P Chen, O Ghattas
Computer Methods in Applied Mechanics and Engineering 388, 114199, 2022
Mandate: US National Science Foundation, US Department of Energy, US Department of …
hIPPYlib: An extensible software framework for large-scale inverse problems
U Villa, N Petra, O Ghattas
Journal of Open Source Software 3 (30), 2018
Mandate: US National Science Foundation, US Department of Defense
Optimal design of acoustic metamaterial cloaks under uncertainty
P Chen, MR Haberman, O Ghattas
Journal of Computational Physics 431, 110114, 2021
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty
P Chen, U Villa, O Ghattas
Journal of Computational Physics 385, 163-186, 2019
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Hessian-based adaptive sparse quadrature for infinite-dimensional Bayesian inverse problems
P Chen, U Villa, O Ghattas
Computer Methods in Applied Mechanics and Engineering 327, 147-172, 2017
Mandate: US National Science Foundation, US Department of Energy, US Department of …
A fast and scalable computational framework for large-scale high-dimensional Bayesian optimal experimental design
K Wu, P Chen, O Ghattas
SIAM/ASA Journal on Uncertainty Quantification 11 (1), 235-261, 2023
Mandate: US National Science Foundation, US Department of Energy, US Department of …
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