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Publication	Type	Year
Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.12 Theory Manual Keith Dalbey, Michael S. Eldred, Gianluca Geraci, John Davis Jakeman, Kathryn Anne Maupin, Jason A. Monschke, Daniel Thomas Seidl, Laura Painton Swiler, Anh Tran, Friedrich Menhorn, Xiaoshu Zeng https://www.osti.gov/search/identifier:1630693	SAND Report – 2020 SAND Report	2020
Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.12 User?s Manual Brian M. Adams, William J. Bohnhoff, Keith Dalbey, Mohamed Salah Ebeida, John P. Eddy, Michael S. Eldred, Russell Hooper, Patricia D. Hough, Kenneth Hu, John Davis Jakeman, Mohammad Khalil, Kathryn Anne Maupin, Jason A. Monschke, Elliott Marshall Ridgway, Ahmad Rushdi, Daniel Thomas Seidl, John Adam Stephens, Laura Painton Swiler, Justin Winokur https://www.osti.gov/search/identifier:1630694	SAND Report – 2020 SAND Report	2020
Dakota Sensitivity Analysis and Uncertainty Quantification, with Examples CDSE Days Keith Dalbey, Brian M. Adams, John Adam Stephens, Laura Painton Swiler https://www.osti.gov/search/identifier:1244466	Conference Paper – 2015 Conference Paper	2015
Dakota: A Toolkit for Sensitivity Analysis, Uncertainty Quantification, and Calibration CDSE Days Keith Dalbey, Brian M. Adams, Laura Painton Swiler	Abstract – 2015 Abstract	2015
Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis Version 6.0 Users ManualVersion 6.0 Users Manual Brian M. Adams, Lara E Bauman, William J. Bohnhoff, Keith Dalbey, John P. Eddy, Mohamed Salah Ebeida, Michael S. Eldred, Patricia D. Hough, Kenneth Hu, John Davis Jakeman, Laura Painton Swiler, John Adam Stephens, Dena Vigil, Timothy Michael Wildey https://www.osti.gov/search/identifier:1177077	SAND Report – 2014 SAND Report	2014
Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis Version 6.0 Theory ManualVersion 6.0 Theory Manual Brian M. Adams, Lara E Bauman, William J. Bohnhoff, Keith Dalbey, John P. Eddy, Mohamed Salah Ebeida, Michael S. Eldred, Patricia D. Hough, Kenneth Hu, John Davis Jakeman, Laura Painton Swiler, John Adam Stephens, Dena Vigil, Timothy Michael Wildey https://www.osti.gov/search/identifier:1177048	SAND Report – 2014 SAND Report	2014
Gaussian Process Adaptive Importance Sampling (GPAIS) SIAM Conference on Uncertainty Quantification Keith Dalbey, Laura Painton Swiler https://www.osti.gov/search/identifier:1141661	Conference Paper – 2014 Conference Paper	2014
Efficient and Robust Gradient Enhanced Kriging Emulators Keith Dalbey https://www.osti.gov/search/identifier:1096451	SAND Report – 2013 SAND Report	2013
Gaussian Process Adaptive Importance Sampling International Journal for Uncertainty Quantification Keith Dalbey, Laura Painton Swiler https://www.osti.gov/search/identifier:1080020	Journal Article – 2013 Journal Article	2013
Fast Generation of Space-filling Latin Hypercube Sample Designs 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference Keith Dalbey, George N. Karystinos https://www.osti.gov/search/identifier:1122442	Conference Paper – 2013 Conference Paper	2013
Gaussian Process Adaptive Importance Sampling (GPAIS) International Journal for Uncertainty Quantification Keith Dalbey, Laura Painton Swiler https://www.osti.gov/search/identifier:1061226	Journal Article – 2012 Journal Article	2012
Gaussian Process Adaptive Importance Sampling (GPAIS) Physical Review Letters Keith Dalbey, Laura Painton Swiler https://www.osti.gov/search/identifier:1064102	Journal Article – 2012 Journal Article	2012
Gaussian Process Adaptive Importance Sampling (GPAIS) Quality and Productivity Research Conference 2012 Keith Dalbey, Laura Painton Swiler https://www.osti.gov/search/identifier:1067635	Conference Paper – 2012 Conference Paper	2012
Effective and Efficient Handling of Ill - Conditioned Correlation Matrices in Kriging and Gradient Enhanced Kriging Emulators Through Pivoted Cholesky Factorization SIAM Conference on Uncertainty Quantification Keith Dalbey, David M. Day, Mark Frederick Hoemmen https://www.osti.gov/search/identifier:1068340	Conference Paper – 2012 Conference Paper	2012
DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis; Version 5.2 Theory Manual Brian M. Adams, William J. Bohnhoff, Keith Dalbey, John P. Eddy, Michael S. Eldred, Patricia D. Hough, Sophia Lefantzi, Laura Painton Swiler, Dena Vigil https://www.osti.gov/search/identifier:1031910	SAND Report – 2011 SAND Report	2011
Towards Breaking the Curse of Dimensionality Through Efficient and Robust Gradient Enhanced Kriging Emulators Computer Methods in Applied Mechanics and Engineering Keith Dalbey https://www.osti.gov/search/identifier:1141656	Journal Article – 2011 Journal Article	2011
Progress Towards Nested Space and Sub-Space Filling Latin Hypercube Sample Designs 11th US National Congress on Computational Mechanics Keith Dalbey, George N. Karystinos https://www.osti.gov/search/identifier:1106676	Conference Paper – 2011 Conference Paper	2011
The Effect of Sample Design Quality on Kriging Emulator Predictions Statistics and Computing Keith Dalbey https://www.osti.gov/search/identifier:1140415	Journal Article – 2011 Journal Article	2011
Surrogate Modeling with Surfpack INFORMS Annual Meeting 2010 Brian M. Adams, Keith Dalbey, Laura Painton Swiler https://www.osti.gov/search/identifier:1035640	Conference Paper – 2011 Conference Paper	2011
Fast Generation of Nested Space-filling Latin Hypercube Sampling Designs 2011 SIAM Conference on Computational Science and Engineering Keith Dalbey, George N. Karystinos https://www.osti.gov/search/identifier:1109274	Conference Paper – 2011 Conference Paper	2011
Fast Generation of Nested Space-filling Latin Hypercube Sample Designs IMAC XXIX A Conference and Exposition on Structural Dynamics Keith Dalbey, George N. Karystinos https://www.osti.gov/search/identifier:1110260	Conference Paper – 2011 Conference Paper	2011
Generation of Pareto Optimal Ensembles of Calibrated Parameter Sets for Climate Models American Geophysical Union's Fall Meeting 2010 Keith Dalbey, Michael Nathan Levy https://www.osti.gov/search/identifier:1035987	Conference Paper – 2010 Conference Paper	2010
Fast Generation of Space-filling Latin Hypercube Sample Designs 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference Keith Dalbey, George N. Karystinos https://www.osti.gov/search/identifier:1027053	Conference Paper – 2010 Conference Paper	2010
DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 5.0 Users ManualQuantification, and Sensitivity Analysis: Version 5.0 Users Manual Brian M. Adams, Keith Dalbey, Michael S. Eldred, David M. Gay, Laura Painton Swiler, William J. Bohnhoff, John P. Eddy, Karen Haskell, Patricia D. Hough https://www.osti.gov/search/identifier:991842	SAND Report – 2010 SAND Report	2010
DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 5.0 Reference ManualQuantification, and Sensitivity Analysis: Version 5.0 Reference Manual Brian M. Adams, Keith Dalbey, Michael S. Eldred, David M. Gay, Laura Painton Swiler, William J. Bohnhoff, John P. Eddy, Karen Haskell, Patricia D. Hough https://www.osti.gov/search/identifier:991841	SAND Report – 2010 SAND Report	2010
Document Title	Type	Year

Results 1–25 of 27

Publications

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.12 Theory Manual

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.12 User?s Manual

Dakota Sensitivity Analysis and Uncertainty Quantification, with Examples

Dakota: A Toolkit for Sensitivity Analysis, Uncertainty Quantification, and Calibration

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis Version 6.0 Users ManualVersion 6.0 Users Manual

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis Version 6.0 Theory ManualVersion 6.0 Theory Manual

Gaussian Process Adaptive Importance Sampling (GPAIS)

Efficient and Robust Gradient Enhanced Kriging Emulators

Gaussian Process Adaptive Importance Sampling

Fast Generation of Space-filling Latin Hypercube Sample Designs

Gaussian Process Adaptive Importance Sampling (GPAIS)

Gaussian Process Adaptive Importance Sampling (GPAIS)

Gaussian Process Adaptive Importance Sampling (GPAIS)

Effective and Efficient Handling of Ill - Conditioned Correlation Matrices in Kriging and Gradient Enhanced Kriging Emulators Through Pivoted Cholesky Factorization

DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis; Version 5.2 Theory Manual

Towards Breaking the Curse of Dimensionality Through Efficient and Robust Gradient Enhanced Kriging Emulators

Progress Towards Nested Space and Sub-Space Filling Latin Hypercube Sample Designs

The Effect of Sample Design Quality on Kriging Emulator Predictions

Surrogate Modeling with Surfpack

Fast Generation of Nested Space-filling Latin Hypercube Sampling Designs

Fast Generation of Nested Space-filling Latin Hypercube Sample Designs

Generation of Pareto Optimal Ensembles of Calibrated Parameter Sets for Climate Models

Fast Generation of Space-filling Latin Hypercube Sample Designs

DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 5.0 Users ManualQuantification, and Sensitivity Analysis: Version 5.0 Users Manual

DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 5.0 Reference ManualQuantification, and Sensitivity Analysis: Version 5.0 Reference Manual