Publications

Advanced Search

Results 26–50 of 254

Scope

Center for Computing Research

All Sandia Publications

Publication Type

Author

Funding Source

Current Filters Clear all

Remove author filter×

Publication	Type	Year
Multifidelity Uncertainty Quantification For Non-Deterministic Models ECCOMAS Congress 2022 Bryan William Reuter, Gianluca Geraci, Timothy Michael Wildey, Michael S. Eldred	Abstract – 2021 Abstract	2021
Model Tuning For Multifidelity Sampling In Dakota 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2022) Michael S. Eldred, Gianluca Geraci, Bryan William Reuter, Teresa Portone, John Davis Jakeman, Alex A. Gorodetsky	Abstract – 2021 Abstract	2021
Elastic Model Calibration using Dakota 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2022) James Derek Tucker, Michael S. Eldred, Devin Francom	Abstract – 2021 Abstract	2021
Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning AIAA SciTech 2021 Geoffrey F. Bomarito, Gianluca Geraci, James E. Warner, Patrick E. Leser, William P. Leser, Michael S. Eldred, John Davis Jakeman, Alex A. Gorodetsky	Conference Proceeding – 2021 Conference Proceeding	2021
Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning AIAA SciTech 2021 Geoffrey F. Bomarito, Gianluca Geraci, James E. Warner, Patrick E. Leser, William P. Leser, Michael S. Eldred, John Davis Jakeman, Alex A. Gorodetsky	Conference Presentation – 2021 Conference Presentation	2021
Leveraging Multiple Information Sources to Enable High-Fidelity Uncertainty Quantification AE585 Chair's Distinguished Lecture Series Michael S. Eldred, Gianluca Geraci, Gorodetsky, John Davis Jakeman	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
aphBO-2GP-3B: A budgeted asynchronous parallel multi-acquisition functions for constrained Bayesian optimization on high-performing computing architecture Structural and Multidisciplinary Optimization Anh Tran, Michael S. Eldred, Timothy Michael Wildey, Scott McCann, Jing Sun, Robert Visintainer	Journal Article – 2021 Journal Article	2021
Automating Model Selection and Tuning for Multifidelity UQ SIAM Conference on Uncertainty Quantification (UQ22) James Warner, Geoffrey Bomarito, Patrick Leser, William Leser, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman	Abstract – 2021 Abstract	2021
Multilevel Monte Carlo estimators for derivative-free optimization under uncertainty SIAM Conference on Uncertainty Quantification (UQ22) Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Youssef Marzouk, Michael S. Eldred, Hans-Joachim Bungartz	Abstract – 2021 Abstract	2021
Multifidelity data fusion in convolutional encoder/decoder networks SIAM Conference on Uncertainty Quantification (UQ22) Lauren Partin, Gianluca Geraci, Ahmad Rushdi, Michael S. Eldred, Daniele Schiavazzi	Abstract – 2021 Abstract	2021
Hybrid multilevel Monte Carlo polynomial chaos method for global sensitivity analysis SIAM Conference on Uncertainty Quantification (UQ22) Michael Merritt, Gianluca Geraci, Teresa Portone, Michael S. Eldred, Pierre Gremaud	Abstract – 2021 Abstract	2021
The Dakota Project: Connecting the Pipeline from Uncertainty Quantification R&D to Mission Impact NASA Langley HPC Seminar Series Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, Teresa Portone, Timothy Michael Wildey, Ahmad Rushdi, Daniel Thomas Seidl	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
Advanced multilevel and multifidelity UQ strategies: surrogates, forward propagation, inverse problems and optimization SIAM Conference of Uncertainty Quantification (UQ22) Michael S. Eldred, Gianluca Geraci, Bryan William Reuter	Abstract – 2021 Abstract	2021
srMO-BO-3GP: A sequential regularized multi-objective Bayesian optimization for constrained design applications using an uncertain Pareto classifier ASME Journal of Mechanical Design Anh Tran, Michael S. Eldred, Scott McCann, Yan Wang https://www.osti.gov/search/identifier:1820417	Journal Article – 2021 Journal Article	2021
Efficient Deployment of Multifidelity Sampling Methods in Production Settings Usnccm16 Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, Teresa Portone	Conference Presentation – 2021 Conference Presentation	2021
Multilevel Estimators for Measures of Robustness in Optimization under Uncertainty 16th US National Congress on Computational Mechanics Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, Ryan King, Hans-Joachim Bungartz, Youssef Marzouk	Conference Presentation – 2021 Conference Presentation	2021
Adaptive Basis for Multifidelity Uncertainty Quantification 16th US National Congress on Computational Mechanics Xiaoshu Zeng, Gianluca Geraci, Michael S. Eldred, John Davis Jakeman, Alex Gorodetsky, Roger Ghanem	Conference Presentation – 2021 Conference Presentation	2021
Hybrid multi-level Monte Carlo polynomial chaos method for global sensitivity analysis 16th US National Congress on Computational Mechanics Merritt Michael, Gianluca Geraci, Michael S. Eldred, Teresa Portone	Conference Presentation – 2021 Conference Presentation	2021
Multi-fidelity Machine Learning Machine Learning and Deep Learning Conference John Davis Jakeman, Michael S. Eldred, Gianluca Geraci, Teresa Portone, Ahmad Rushdi, Daniel Thomas Seidl, Thomas M. Smith https://www.osti.gov/search/identifier:1876608	Conference Presentation – 2021 Conference Presentation	2021
Adaptive resource allocation for surrogate modeling of systems comprised of multiple disciplines with varying fidelity IX International Conference on Coupled Problems in Science and Engineering John Davis Jakeman, Samuel Friedman, Michael S. Eldred, Lorenzo Tamellini, Alex Gorodetsky, Doug Allaire https://www.osti.gov/search/identifier:1872879	Conference Presentation – 2021 Conference Presentation	2021
Adaptive resource allocation for surrogate modeling of systems comprised of multiple disciplines with varying fidelity Sam Friedman, John Davis Jakeman, Michael S. Eldred, Lorenzo Tamellini, Alex Gorodestky, Doug Allaire https://www.osti.gov/search/identifier:1807453	Report – 2021 Report	2021
MFNETS: Multi-Fidelity Data-Driven Networks for Data Analysis MFNETSMulti-Fidelity Data-Driven Networks for Data Analysis John Davis Jakeman, Alex Gorodetsky, Michael S. Eldred, Gianluca Geraci, Thomas M. Smith https://www.osti.gov/search/identifier:1854429	Conference Presentation – 2021 Conference Presentation	2021
Exploring important directions for multifidelity uncertainty quantification by basis adaptation method Siam Cse 2021 Xiaoshu Zeng, Gianluca Geraci, Michael S. Eldred, Roger Ghanem https://www.osti.gov/search/identifier:1848037	Conference Presentation – 2021 Conference Presentation	2021
Recent Advances in Adaptive Refinement of (Regression-Based) Multifidelity Surrogates for UQ Siam Cse21 Michael S. Eldred, Alex Arkady Gorodetsky, Gianluca Geraci, John Davis Jakeman, Teresa Portone https://www.osti.gov/search/identifier:1847573	Conference Presentation – 2021 Conference Presentation	2021
Multifidelity Monte Carlo Estimators for Robust Formulations in Optimization under Uncertainty Siam Cse 2021 Friedrich Menhorn, Gianluca Geraci, Daniel Thomas Seidl, Michael S. Eldred, Ryan King, Hans-Joachim Bungartz, Youssef Marzouk https://www.osti.gov/search/identifier:1847580	Conference Presentation – 2021 Conference Presentation	2021
Document Title	Type	Year

Results 26–50 of 254

Publications

Multifidelity Uncertainty Quantification For Non-Deterministic Models

Model Tuning For Multifidelity Sampling In Dakota

Elastic Model Calibration using Dakota

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Leveraging Multiple Information Sources to Enable High-Fidelity Uncertainty Quantification

aphBO-2GP-3B: A budgeted asynchronous parallel multi-acquisition functions for constrained Bayesian optimization on high-performing computing architecture

Automating Model Selection and Tuning for Multifidelity UQ

Multilevel Monte Carlo estimators for derivative-free optimization under uncertainty

Multifidelity data fusion in convolutional encoder/decoder networks

Hybrid multilevel Monte Carlo polynomial chaos method for global sensitivity analysis

The Dakota Project: Connecting the Pipeline from Uncertainty Quantification R&D to Mission Impact

Advanced multilevel and multifidelity UQ strategies: surrogates, forward propagation, inverse problems and optimization

srMO-BO-3GP: A sequential regularized multi-objective Bayesian optimization for constrained design applications using an uncertain Pareto classifier

Efficient Deployment of Multifidelity Sampling Methods in Production Settings

Multilevel Estimators for Measures of Robustness in Optimization under Uncertainty

Adaptive Basis for Multifidelity Uncertainty Quantification

Hybrid multi-level Monte Carlo polynomial chaos method for global sensitivity analysis

Multi-fidelity Machine Learning

Adaptive resource allocation for surrogate modeling of systems comprised of multiple disciplines with varying fidelity

Adaptive resource allocation for surrogate modeling of systems comprised of multiple disciplines with varying fidelity

MFNETS: Multi-Fidelity Data-Driven Networks for Data Analysis

Exploring important directions for multifidelity uncertainty quantification by basis adaptation method

Recent Advances in Adaptive Refinement of (Regression-Based) Multifidelity Surrogates for UQ

Multifidelity Monte Carlo Estimators for Robust Formulations in Optimization under Uncertainty