Khachik Sargsyan

Principal Member of the Technical Staff

Author profile picture

Principal Member of the Technical Staff

ksargsy@sandia.gov

Google Scholar

(925) 294-4885

Sandia National Laboratories, California
 P.O. Box 969
 Livermore, CA 94551-0969

Biography

Dr. Khachik Sargsyan is a Distinguished Member of the Technical Staff at Sandia National Laboratories in Livermore, California. Before working in staff and postdoctoral positions at Sandia, he received his Ph.D. in Applied and Interdisciplinary Mathematics from the University of Michigan, Ann Arbor, in 2007. Prior to graduate school, Dr. Sargsyan obtained a B.S. degree in Applied Math and Physics from the Moscow Institute of Physics and Technology. Khachik is the lead developer of PyTUQ, a Python toolkit for uncertainty quantification, and the lead developer of QUiNN, a Python library for Quantifying Uncertainties in Neural Networks. Khachik is also the Land Modeling UQ lead in the Energy Exascale Earth System Model (E3SM) multi-lab project, and is a member of the FASTMath SciDAC Institute, where his work focuses on UQ method development for large scale applications.

Research Interests

Dr. Sargsyan’s research evolves around uncertainty quantification (UQ) and predictability analysis of physical and computational models. He has developed and applied methods for model reduction, UQ and data assimilation, targeting fundamental challenges such as structural errors, intrinsic stochasticity, high-dimensionality, limited data, discontinuities, and rare events, with a range of applications including modeling, chemical kinetics, turbulent combustion, fusion science, hardware architecture simulation. He has published over eighty peer-reviewed journal articles.

Education

DegreeMajorInstitutionLocationYear Completed
PhDInterdisciplinary MathematicsUniversity of MichiganAnn Arbor, MI2007
BSApplied Math and PhysicsMoscow Institute of Physics and TechnologyMoscow, Russia2002

Professional Organizations & Leadership

Journal of Discrete and Continuous Dynamical Systems
Member, Editorial Board
Journal of Machine Learning for Modeling and Computing
Member, Editorial Board
Society of Industrial and Applied Mathematics
Member
American Geophysical Union
Member
International Society of Bayesian Analysis
Member
American Statistical Association
Member

Publications

  • Mueller, J.N., Sargsyan, K., Daniels, C.J., & Najm, H.N. (2025). Polynomial Chaos Surrogate Construction for Random Fields with Parametric Uncertainty. SIAM-ASA Journal on Uncertainty Quantification, 13(1), pp. 1-29. 10.1137/23m1613505 Publication ID: 149248
  • Ghahari, F., Sargsyan, K., & Taciroglu, E. (2024). Quantification of modeling uncertainty in the Rayleigh damping model. Earthquake Engineering and Structural Dynamics, 53(9), pp. 2950-2956. 10.1002/eqe.4143 Publication ID: 149048
  • Williams, L., Sargsyan, K., Rohskopf, A., & Najm, H.N. (2024). Active learning for SNAP interatomic potentials via Bayesian predictive uncertainty. Computational Materials Science, 242. 10.1016/j.commatsci.2024.113074 Publication ID: 124820
  • Blondal, K., Badger, K., Sargsyan, K., Bross, D.H., Ruscic, B., & Goldsmith, C.F. (2024). Importance sampling within configuration space integration for adsorbate thermophysical properties: a case study for CH3/Ni(111). Physical Chemistry Chemical Physics, 26(24), pp. 17265-17273. https://doi.org/10.1039/d4cp01197j Publication ID: 124804
  • Ghahari, F., Sargsyan, K., Parker, G.A., Swensen, D., Celebi, M., Haddadi, H., & Taciroglu, E. (2024). Performance-based earthquake early warning for tall buildings. Earthquake Spectra, 40(2), pp. 1425-1451. 10.1177/87552930241236762 Publication ID: 124840
  • Zhou, W., Zhang, L., Sheshukov, A., Wang, J., Zhu, M., Sargsyan, K., Xu, D., Liu, D., Zhang, T., Mazepa, V., Sokolov, A., Valdayskikh, V., & Ivanov, V. (2024). Ground Heat Flux Reconstruction Using Bayesian Uncertainty Quantification Machinery and Surrogate Modeling. Earth and Space Science, 11(3). 10.1029/2023ea003435 Publication ID: 124240
  • Sargsyan, K., Diaz-Ibarra, O.H., Murgoitio-Esandi, J., Hudson, J., D’Elia, M., & Najm, H.N. (2024). Quantifying Uncertainties in Weight-Parameterized Residual Neural Networks [Conference Presentation]. 10.2172/2540401 Publication ID: 150132
  • Sargsyan, K., & Ricciuto, D. (2024). Reduced-Dimensional Neural Network Surrogate Construction for the E3SM Land Model [Conference Presentation]. 10.2172/2540402 Publication ID: 150136
  • Sargsyan, K., Debusschere, B., & Eldred, M. (2024). Surrogate-Accelerated Parameter Optimization for the Quasi-Biennial Oscillation [Conference Presentation]. 10.2172/2540415 Publication ID: 150188
  • Sargsyan, K., Debusschere, B., & Eldred, M. (2024). Surrogate-based calibration for the quasi-biennial oscillation [Conference Poster]. 10.2172/2540427 Publication ID: 150232
  • Mueller, J.N., Sargsyan, K., & Najm, H.N. (2024). Construction and Performance of Polynomial Chaos Surrogates for Stochastic Processes [Conference Presentation]. 10.2172/2540445 Publication ID: 150304
  • Curry, C.J., Sargsyan, K., Safta, C., & Debusschere, B. (2024). The UQTk C++/Python Toolkit for Uncertainty Quantification: Overview and Applications [Conference Presentation]. 10.2172/2540447 Publication ID: 150312
  • Najm, H.N., Robbe, P., Casey, T., Sargsyan, K., & Khalil, M. (2024). Approximate Bayesian Computation for Model Calibration Given Summary Statistics [Conference Presentation]. 10.2172/2540455 Publication ID: 150344
  • Hudson, J.L., Diaz-Ibarra, O.H., D’Elia, M., Najm, H.N., Rosso, H., Ruthotto, L., & Sargsyan, K. (2023). Analysis of Neural Networks as Random Dynamical Systems. 10.2172/2430214 Publication ID: 147900
  • Diaz-Ibarra, O.H., Sargsyan, K., & Najm, H.N. (2023). Dimensionality Reduction and Weight-Parameterized Neural NetworkSurrogates for Climate Models [Conference Presentation]. 10.2172/2430572 Publication ID: 125944
  • Mueller, J.N., Sargsyan, K., & Najm, H.N. (2023). Joint PCE Surrogate Construction with Uncertainty Quantification for Parameterized Stochastic Processes [Conference Presentation]. 10.2172/2430772 Publication ID: 126640
  • Mueller, J.N., Sargsyan, K., & Najm, H.N. (2023). Polynomial Chaos Surrogate Construction for Stochastic Models with Parametric Uncertainty [Conference Paper]. https://www.osti.gov/biblio/2432080 Publication ID: 131168
  • Mueller, J.N., Najm, H.N., & Sargsyan, K. (2023). A joint PCE Surrogate Construction with Uncertainty Quantification for Parameterized Stochastic Processes Applied to Catalysis [Conference Presentation]. 10.2172/2431031 Publication ID: 127568
  • Sargsyan, K., Najm, H.N., & Mueller, J.N. (2023). A Polynomial Chaos Surrogate Construction for Chemical Catalysis Models [Conference Poster]. 10.2172/2431385 Publication ID: 128844
  • Safta, C., Jakeman, J.D., Sargsyan, K., & Gorodetsky, A.A. (2023). Modeling spatio-temporal processes in climate models via functional tensor networks [Conference Presentation]. 10.2172/2431857 Publication ID: 130428
  • Robbe, P., Andersson, D., Bonnet, L.A.P.L., Casey, T., Cooper, M.W.D., Matthews, C., Sargsyan, K., & Najm, H.N. (2023). Surrogate-assisted Data-Free Inference with summary statistics for predicting xenon diffusivity in uranium oxide nuclear fuel [Conference Presentation]. 10.2172/2431859 Publication ID: 130436
  • Najm, H.N., Sargsyan, K., & D’Elia, M. (2022). The role of stiffness in training and generalization of ResNets. Journal of Machine Learning for Modeling and Computing, 4(2). 10.1615/jmachlearnmodelcomput.2023047131 Publication ID: 123168
  • Ghahari, S.F., Sargsyan, K., Celebi, M., & Taciroglu, E. (2022). Quantifying modeling uncertainty in simplified beam models for building response prediction. Structural Control and Health Monitoring, 29(11). 10.1002/stc.3078 Publication ID: 80058
  • Hudson, J.L., Sargsyan, K., D’Elia, M., & Najm, H.N. (2022). Examining stiffness in ResNets through interpretation as discretized Neural ODEs [Conference Presentation]. 10.2172/2004786 Publication ID: 117972
  • Williams, L., Sargsyan, K., Johnston, K., & Najm, H.N. (2022). Active Learning of SNAP Potentials using Bayesian Uncertainty Estimation [Conference Presentation]. 10.2172/2005291 Publication ID: 118616
  • Sargsyan, K., Williams, L., & Najm, H.N. (2022). Uncertainty Quantification of Machine Learning Interatomic Potential Models [Conference Poster]. 10.2172/2004338 Publication ID: 116568
  • Johnson, M.S., Gierada, M., Bross, D.H., Hermes, E.D., Blais, C., Goldsmith, C.F., West, R.H., Sargsyan, K., Najm, H.N., & Zador, J. (2022). pynta: An automated workflow code for reaction path exploration on surfaces [Conference Presentation]. 10.2172/2004380 Publication ID: 116736
  • Xu, D., Bisht, G., Sargsyan, K., Liao, C., & Ruby Leung, L. (2022). Using a surrogate-assisted Bayesian framework to calibrate the runoff-generation scheme in the Energy Exascale Earth System Model (E3SM) v1. Geoscientific Model Development, 15(12), pp. 5021-5043. https://doi.org/10.5194/gmd-15-5021-2022 Publication ID: 106536
  • Robbe, P., Bonnet, L.A.P.L., Casey, T., Sargsyan, K., Najm, H.N., Matthews, C., Copper, M., & Andersson, D. (2022). Bayesian calibration for summary statistics with applications to a cluster dynamics model [Conference Presentation]. 10.2172/2003860 Publication ID: 114724
  • Sargsyan, K. (2022). Training and Generalization of Residual Neural Networks as Discrete Analogues of Neural ODEs [Conference Presentation]. 10.2172/2003882 Publication ID: 114812
  • Younkin, T.R., Sargsyan, K., Casey, T., Najm, H.N., Canik, J.M., Green, D.L., Doerner, R.P., Nishijima, D., Baldwin, M., Drobny, J., Curreli, D., & Wirth, B.D. (2022). Quantification of the effect of uncertainty on impurity migration in PISCES-A simulated with GITR. Nuclear Fusion, 62(5). 10.1088/1741-4326/ac2bfa Publication ID: 80875
  • Robbe, P., Casey, T., Sargsyan, K., & Najm, H.N. (2022). Uncertainty Quantification in Computational Modeling of Plasma-Surface Interactions [Conference Presentation]. 10.2172/2003181 Publication ID: 112128
  • Blondal, K., Sargsyan, K., Bross, D., Rucic, B., & Goldsmith, F. (2022). Including Anharmonicity in Adsorbate Partition Functions: Effect on the Thermodynamic Properties of Carbon Monoxide on Pt(111) and Methanol on Cu(111) [Conference Poster]. 10.2172/2003285 Publication ID: 112520
  • Robbe, P., Casey, T., Sargsyan, K., Bonnet, L.A.P.L., & Najm, H.N. (2022). Bayesian calibration of a cluster dynamics model [Conference Presentation]. 10.2172/2003389 Publication ID: 112888
  • Safta, C., Jakeman, J.D., & Sargsyan, K. (2022). Quantifying Uncertainty in E3SM via Functional Tensor Network Approximations [Conference Presentation]. 10.2172/2002262 Publication ID: 110012
  • Sargsyan, K., Williams, L., Johnston, K., & Najm, H.N. (2022). Quantification and Propagation of Uncertainties in Machine Learning Interatomic Potentials for Molecular Dynamics [Conference Presentation]. 10.2172/2002297 Publication ID: 110140
  • Boll, L., Johnston, K., Sargsyan, K., Safta, C., & Debusschere, B. (2022). The UQTk C++/Python Toolkit for Uncertainty Quantification: Overview and Applications [Conference Presentation]. 10.2172/2002312 Publication ID: 110196
  • Robbe, P., Casey, T., Sargsyan, K., & Najm, H.N. (2022). Uncertainty Quantification in Computational Modeling of Plasma-Surface Interactions [Conference Presentation]. 10.2172/2002352 Publication ID: 110352
  • Sargsyan, K., Safta, C., Boll, L., Johnston, K., Khalil, M., Chowdhary, K., Rai, P., Casey, T., Zeng, X., & Debusschere, B. (2021). UQTk Version 3.1.2 User Manual. 10.2172/1855040 Publication ID: 79950
  • Hudson, J.L., Sargsyan, K., D’Elia, M., & Najm, H.N. (2021). Detecting stiffness in ResNets inspired by Neural ODEs [Conference Poster]. 10.2172/2001529 Publication ID: 107232
  • Safta, C., Sargsyan, K., & Jakeman, J.D. (2021). Functional Tensor Network Approximations for E3SM Land Model [Conference Presentation]. 10.2172/2001640 Publication ID: 107652
  • Ivanov, V.Y., Xu, D., Dwelle, M.C., & Sargsyan, K. (2021). Breaking Down the Computational Barriers to Real-Time Urban Flood Forecasting. Geophysical Research Letters, 48(20). 10.1029/2021gl093585 Publication ID: 80939
  • Najm, H.N., Sargsyan, K., Kim, K., Goldsmith, C.F., West, R.H., Bylaska, E.J., Bross, D.H., Ruscic, B., Safta, C., Zador, J., Blais, C., Blondal, K., Diaz-Ibarra, O.H., Hermes, E., & Mazeau, E. (2021). Exascale Catalytic Chemistry (ECC) [Conference Poster]. 10.2172/1890393 Publication ID: 76037
  • Hermes, E., Blondal, K., Kreitz, B., Sargsyan, K., Najm, H.N., Zador, J., Goldsmith, C.F., & West, R. (2021). Application of a Novel Saddle Point Optimization Algorithm on Surface Reactions Involving Bidentate Adsorbates [Conference Poster]. 10.2172/1890874 Publication ID: 76044
  • Blondal, K., Sargsyan, K., Bross, D.H., Ruscic, B., & Goldsmith, C.F. (2021). Adsorbate Partition Functions via Phase Space Integration: Quantifying the Effect of Translational Anharmonicity on Thermodynamic Properties. Journal of Physical Chemistry C, 125(37), pp. 20249-20260. https://doi.org/10.1021/acs.jpcc.1c04009 Publication ID: 80869
  • Hermes, E., Sargsyan, K., Najm, H.N., & Zador, J. (2021). Geometry optimization speedup through a geodesic approach to internal coordinates. Journal of Chemical Physics, 155(9). 10.1063/5.0060146 Publication ID: 75381
  • Sargsyan, K., Johnstone, K., Dantanarayana, V., & Najm, H.N. (2021). Active Learning and Uncertainty Quantification for Machine Learning Interatomic Potentials [Conference Presentation]. 10.2172/1890912 Publication ID: 75904
  • Blondal, K., Sargsyan, K., Bross, D., & Goldsmith, F. (2021). Adsorbate Partition Functions via Phase Space Integration: Quantifying the Effect of Translational Anharmonicity on Thermodynamic Properties [Conference Poster]. 10.2172/2006428 Publication ID: 122364
  • Kreitz, B., Sargsyan, K., Mazeau, E.J., Blondal, K., West, R.H., Wehinger, G.D., Turek, T., & Goldsmith, C.F. (2021). Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO2 Hydrogenation on Ni(111). JACS Au, 1(10), pp. 1656-1673. https://doi.org/10.1021/jacsau.1c00276 Publication ID: 80885
  • Hudson, J.L., Sargsyan, K., D’Elia, M., & Najm, H.N. (2021). Analysis of Neural Networks as Dynamical Systems [Conference Presentation]. 10.2172/1883507 Publication ID: 79301
  • Blondal, K., Sargsyan, K., Bross, D., Ruscic, B., & Goldsmith, C.F. (2021). Including anharmonicity in adsorbate partition functions: Effect on equilibrium constant estimates in heterogeneous catalysis [Conference Presentation]. 10.2172/1863707 Publication ID: 78110
  • Sargsyan, K., Safta, C., & Daniel, R. (2021). Dimensionality Reduction and Physics-Informed Neural Networks for Climate Land Models [Conference Presentation]. 10.2172/1854072 Publication ID: 77435
  • Safta, C., Sargsyan, K., Jakeman, J.D., & Gorodetsky, A.A. (2021). Low-Rank Tensor Network Approximations for Earth System Model [Conference Presentation]. 10.2172/1854317 Publication ID: 77458
  • Sargsyan, K., Safta, C., Johnston, K., Khalil, M., Chowdhary, K., Rai, P., Casey, T., Boll, L., Zeng, X., & Debusschere, B. (2021). UQTk Version 3.1.1 User Manual. 10.2172/1777090 Publication ID: 103436
  • Ray, J., Blonigan, P.J., Safta, C., & Sargsyan, K. (2020). Characterization of Partially Observed Epidemics Through Bayesian Inference – Application to COVID-19 Forecasts [Conference Presentation]. 10.2172/1842250 Publication ID: 75113
  • Blondal, K., Sargsyan, K., Bross, D.H., Hermes, E., Najm, H.N., Zador, J., & Goldsmith, C.F. (2020). Including anharmonicity in adsorbate partition functions and how it affects theoretical parameter estimates for desorption of methanol from a Cu(111) surface [Conference Presentation]. 10.2172/1831569 Publication ID: 71767
  • Safta, C., Ray, J., & Sargsyan, K. (2020). Characterization of partially observed epidemics through Bayesian inference: application to COVID-19. Computational Mechanics, 66(5), pp. 1109-1129. 10.1007/s00466-020-01897-z Publication ID: 74505
  • Johnston, K., Boll, L., Sargsyan, K., Safta, C., & Debusschere, B. (2020). UQTk A C++/Python Toolkit for Uncertainty Quantification: Overview and Applications [Presentation]. https://www.osti.gov/biblio/1820270 Publication ID: 74786
  • Sargsyan, K., Tran, V.N., Ivanov, V.Y., & Kim, J. (2020). A Novel Modeling Framework for Computationally Efficient and Accurate Real-Time Ensemble Flood Forecasting With Uncertainty Quantification. Water Resources Research, 56(3). 10.1029/2019wr025727 Publication ID: 103288
  • Sargsyan, K., Safta, C., Johnston, K., Khalil, M., Chowdhary, K., Rai, P., Casey, T., Zeng, X., & Debusschere, B. (2020). UQTk User Manual (V.3.1.0). 10.2172/1605051 Publication ID: 105620
  • Safta, C., Sargsyan, K., & Jakeman, J.D. (2019). Uncertainty Quantification for E3SM Land Component using Low-Rank Surrogate Models [Conference Poster]. https://www.osti.gov/biblio/1643449 Publication ID: 66773
  • Ratnaswamy, V., Safta, C., Sargsyan, K., & Ricciuto, . (2019). Physics Informed Neural Network Surrogate for E3SM Land Model [Conference Poster]. https://www.osti.gov/biblio/1643429 Publication ID: 66804
  • Casey, T., Sargsyan, K., & Najm, H.N. (2019). Uncertainty quantification workflows in fusion plasma surface interaction modeling [Conference Poster]. https://www.osti.gov/biblio/1643062 Publication ID: 66036
  • Najm, H.N., Safta, C., Huan, X., Casey, T., Sargsyan, K., Oefelein, J., Lacaze, G., Vane, Z., Eldred, M., & Geraci, G. (2019). Uncertainty Quantification in Computational Models of Large Scale Physical Systems [Conference Poster]. https://www.osti.gov/biblio/1641505 Publication ID: 70287
  • Ratnaswamy, V., Sargsyan, K., Safta, C., & Ricciuto, D. (2019). Physics-driven RNN Approach for E3SM Land Model Surrogate Construction [Conference Poster]. https://www.osti.gov/biblio/1641516 Publication ID: 70310
  • Casey, T., Debusschere, B., Eldred, M., Geraci, G., Ghanem, R., Jakeman, J.D., Marzouk, Y., Najm, H.N., Safta, C., & Sargsyan, K. (2019). FASTMath: UQ Algorithms [Conference Poster]. https://www.osti.gov/biblio/1641088 Publication ID: 69621
  • Najm, H.N., Safta, C., Huan, X., Casey, T., Sargsyan, K., Oefelein, J., Lacaze, G., Eldred, M., & Geraci, G. (2019). Uncertainty Quantification in Large Scale Computational Models [Conference Poster]. https://www.osti.gov/biblio/1641089 Publication ID: 69622
  • Safta, C., Reid, T., Jakeman, J.D., & Sargsyan, K. (2019). Approximating Data with Stochastic and Physical Dependence using the Functional Tensor Train Models [Conference Poster]. https://www.osti.gov/biblio/1641238 Publication ID: 69801
  • Sargsyan, K., & Safta, C. (2019). Surrogate-enabled Sensitivity Analysis and Parameter Inference of High-Dimensional Models [Conference Poster]. https://www.osti.gov/biblio/1641209 Publication ID: 69878
  • Sargsyan, K., Younkin, T., Casey, T., Najm, H.N., & Wirth, B. (2019). Uncertainty Quantification and Propagation for Impurity Migration [Conference Poster]. https://www.osti.gov/biblio/1643670 Publication ID: 68990
  • Safta, C., Sargsyan, K., Jakeman, J.D., Gorodetsky, A.A., & Ricciuto, D. (2019). Exploiting Model Structure for Forward Propagation of Uncertainty in Earth System Models [Conference Poster]. https://www.osti.gov/biblio/1640926 Publication ID: 69353
  • Safta, C., Tsilifis, P., Huan, X., Sargsyan, K., Lacaze, G., Oefelein, J.C., Najm, H.N., & Ghanem, R.G. (2019). Compressive sensing adaptation for polynomial chaos expansions. Journal of Computational Physics, 380(C), pp. 29-47. 10.1016/j.jcp.2018.12.010 Publication ID: 58677
  • Safta, C., Sargsyan, K., Jakeman, J.D., Gorodetsky, A., & Ricciuto, D. (2019). Exploiting Low-Rank Structure for Sensitivity Analysis in Earth System Models [Conference Poster]. https://www.osti.gov/biblio/1639271 Publication ID: 67283
  • Huan, X., Sargsyan, K., & Najm, H.N. (2019). Embedded Model Error Representation for Bayesian Model Calibration. arXiv.org Repository, 2019. https://www.osti.gov/biblio/1529284 Publication ID: 58730
  • Carlberg, K.T., Guzzetti, S., Khalil, M., & Sargsyan, K. (2019). Large-Scale Uncertainty Propagation via Overlapping Domain Decomposition [Conference Poster]. https://www.osti.gov/biblio/1602394 Publication ID: 67151
  • Debusschere, B., Sargsyan, K., & Safta, C. (2019). UQTk A Flexible Python/C++ Toolkit for Uncertainty Quantification [Conference Poster]. https://www.osti.gov/biblio/1602639 Publication ID: 67187
  • Sargsyan, K., Huan, X., & Najm, H.N. (2019). Embedded model error representation for bayesianmodel calibration. International Journal for Uncertainty Quantification, 9(4), pp. 365-394. https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073061599&origin=inward Publication ID: 104312
  • Mayer, M., Zador, J., & Sargsyan, K. (2018). Uncertainty in master-equation-based rate coefficient calculations. 10.2172/1531319 Publication ID: 59306
  • Safta, C., Huan, X., Najm, H.N., Sargsyan, K., Eldred, M., & Geraci, G. (2018). Adaptive Sparse Quadrature for Multifidelity Scramjet Simulations [Conference Poster]. https://www.osti.gov/biblio/1569685 Publication ID: 63078
  • Sargsyan, K. (2018). Bayesian inference for model error quantification and propagation with UQTk [Conference Poster]. https://www.osti.gov/biblio/1570576 Publication ID: 63122
  • Debusschere, B., Sargsyan, K., & Parekh, O.D. (2018). Quantum Annealing Approaches for Building Sparse Surrogate Models in Uncertainty Quantification [Conference Poster]. https://www.osti.gov/biblio/1806634 Publication ID: 63222
  • Sargsyan, K., Huan, X., & Najm, H.N. (2018). Bayesian Framework for Embedded Model Error Representation and Quantification [Conference Poster]. https://www.osti.gov/biblio/1806614 Publication ID: 63235
  • Huan, X., Safta, C., Sargsyan, K., Vane, Z.P., Lacaze, G., Oefelein, J.C., & Najm, H.N. (2018). Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions. SIAM/ASA Journal on Uncertainty Quantification, 6(2). 10.1137/17M1141096 Publication ID: 98340
  • Hermes, E., Rai, P., Sargsyan, K., Zador, J., & Najm, H.N. (2018). Optimization of low-rank tensor functional approximations [Conference Poster]. https://www.osti.gov/biblio/1525693 Publication ID: 62439
  • Huan, X., Sargsyan, K., & Najm, H.N. (2018). Choosing Embedding for Capturing Model Misspecification [Conference Poster]. https://www.osti.gov/biblio/1529749 Publication ID: 62692
  • Safta, C., Sargsyan, K., & Ricciuto, D. (2018). Machine Learning Techniques for Global Sensitivity Analysis in Earth System Models [Conference Poster]. https://www.osti.gov/biblio/1524507 Publication ID: 62321
  • Debusschere, B., Sargsyan, K., Safta, C., Rai, P., & Chowdhary, K. (2018). UQTk: A Flexible Python/C++ Toolkit for Uncertainty Quantification [Conference Poster]. https://www.osti.gov/biblio/1510846 Publication ID: 61718
  • Safta, C., Huan, X., Sargsyan, K., Najm, H.N., Eldred, M., & Geraci, G. (2018). Sparse multifidelity approximations for forward UQ [Conference Poster]. https://www.osti.gov/biblio/1510682 Publication ID: 61747
  • Rai, P., Sargsyan, K., & Najm, H.N. (2018). Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals. Computer Methods in Applied Mechanics and Engineering, 336. 10.1016/j.cma.2018.02.026 Publication ID: 61090
  • Sargsyan, K., Ricciuto, D., & Thornton, P. (2018). The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model. Journal of Advances in Modeling Earth Systems, 10(2), pp. 297-319. https://doi.org/10.1002/2017MS000962 Publication ID: 54911
  • Debusschere, B., Safta, C., Sargsyan, K., & Chowdhary, K. (2018). UQTk: A C++/Python Uncertainty Quantification Toolkit [Presentation]. https://www.osti.gov/biblio/1497545 Publication ID: 60786
  • Najm, H.N., Debusschere, B., Sparks, N., Sargsyan, K., Huan, X., Oefelein, J., Vane, Z., Eldred, M., Geraci, G., Knio, O., Sraj, I., Scovazzi, G., Colomes, O., Marzouk, Y., Zahm, O., Menhorn, F., Ghanem, R., & Tsilifis, P. (2018). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine ? ScramjetUQ ? [Conference Poster]. https://www.osti.gov/biblio/1572447 Publication ID: 60908
  • Huan, X., Safta, C., Sargsyan, K., Geraci, G., Eldred, M., Vane, Z.P., Lacaze, G., Oefelein, J.C., & Najm, H.N. (2018). Global sensitivity analysis and estimation of model error, toward uncertainty quantification in scramjet computations. AIAA Journal, 56(3), pp. 1170-1184. https://doi.org/10.2514/1.J056278 Publication ID: 57736
  • Huan, X., Geraci, G., Vane, Z.P., Safta, C., Eldred, M., Oefelein, J., Najm, H.N., & Sargsyan, K. (2018). Multifidelity Statistical Analysis of Large Eddy Simulations in Scramjet Computations [Conference Poster]. https://doi.org/10.2514/6.2018-1180 Publication ID: 58547
  • Debusschere, B., Templeton, J.A., Safta, C., Sargsyan, K., Pinar, A., & Najm, H.N. (2018). Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations [Conference Poster]. https://www.osti.gov/biblio/1512381 Publication ID: 58575
  • Huan, X., Geraci, G., Safta, C., Eldred, M., Sargsyan, K., Vane, Z.P., Oefelein, J.C., & Najm, H.N. (2018). Multifidelity statistical analysis of large eddy simulations in scramjet computations [Conference Poster]. AIAA Non-Deterministic Approaches Conference, 2018. https://doi.org/10.2514/6.2018-1180 Publication ID: 58602
  • Huan, X., Safta, C., Sargsyan, K., Geraci, G., Eldred, M., Vane, Z.P., Lacaze, G., Oefelein, J., & Najm, H.N. (2018). Global sensitivity analysis and estimation of model error, toward uncertainty quantification in scramjet computations. AIAA Journal, 56(3), pp. 1170-1184. 10.2514/1.J056278 Publication ID: 60730
  • Huan, X., Safta, C., Sargsyan, K., Vane, Z.P., Lacaze, G., Oefelein, J.C., & Najm, H.N. (2018). Compressive sensing with cross-validation and stop-sampling for sparse polynomial chaos expansions [Conference Poster]. SIAM-ASA Journal on Uncertainty Quantification. 10.1137/17M1141096 Publication ID: 61717
  • Kenny, J., Sargsyan, K., Knight, S., Michelogiannakis, G., & Wilke, J. (2018). The pitfalls of provisioning exascale networks: A trace replay analysis for understanding communication performance [Conference Poster]. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-319-92040-5_14 Publication ID: 61906
  • Safta, C., Huan, X., Geraci, G., Eldred, M., Sargsyan, K., Vane, Z.P., Oefelein, J., & Najm, H.N. (2017). Multifidelity Statistical Analysis of Large Eddy Simulations in Scramjet Computations [Conference Poster]. https://www.osti.gov/biblio/1513486 Publication ID: 58676
  • Wilke, J., Kenny, J., Knight, S., Michelogiannakis, G., & Sargsyan, K. (2017). The Pitfalls of Provisioning Exascale Networks: A Trace Replay Analysis for Understanding Communication Performance [Conference Poster]. https://www.osti.gov/biblio/1513495 Publication ID: 58690
  • Wilke, J., Kenny, J., Knight, S., Sargsyan, K., & Rumley, S. (2017). Compiler-assisted Source-to-Source Skeletonization of Application Models for System Simulation [Conference Poster]. 10.1007/978-3-319-92040-5_7 Publication ID: 58691
  • Debusschere, B., Templeton, J.A., Safta, C., Sargsyan, K., Pinar, A., & Najm, H.N. (2017). Predictive Fidelity of Machine Learning Methods Applied to Scientific Simulations [Conference Poster]. https://www.osti.gov/biblio/1513665 Publication ID: 58794
  • Safta, C., Sargsyan, K., & Ricciuto, D. (2017). Machine Learning Techniques for Global Sensitivity Analysis in Earth System Models [Conference Poster]. https://www.osti.gov/biblio/1512022 Publication ID: 54660
  • Sargsyan, K., Safta, C., Ricciuto, D., Thornton, P., Najm, H.N., & Huan, X. (2017). Embedded Model Error Representation and Propagation in Climate Models [Conference Poster]. https://www.osti.gov/biblio/1512030 Publication ID: 54686
  • Griffiths, N.A., Hanson, P.J., Ricciuto, D.M., Jensen, A.M., Malhotra, A., McFarlane, K.J., Norby, R.J., Sargsyan, K., Sebestyen, S.D., Shi, X., Walker, A.P., Ward, E.J., Warren, J.M., & Weston, D.J. (2017). Temporal and spatial variation in peatland carbon cycling and implications for interpreting responses of an ecosystem-scale warming experiment. Soil Science Society of America Journal, 81(6), pp. 1668-1688. https://doi.org/10.2136/sssaj2016.12.0422 Publication ID: 97948
  • Sargsyan, K., Safta, C., Chowdhary, K., Castorena, S., de Bord, S., & Debusschere, B. (2017). UQTk Version 3.0.4 User Manual. 10.2172/1813904 Publication ID: 53568
  • Rai, P., Sargsyan, K., Najm, H.N., Hermes, M.R., & Hirata, S. (2017). Low-rank canonical-tensor decomposition of potential energy surfaces: application to grid-based diagrammatic vibrational Green’s function theory. Molecular Physics, 115(17-18), pp. 2120-2134. 10.1080/00268976.2017.1288937 Publication ID: 52923
  • Debusschere, B., Rizzi, F., Foulk, J.W., Sargsyan, K., Safta, C., Najm, H.N., Knio, O., Mycek, P., Contreras, A., & le Olivier, M. (2017). Probabilistic Approach to Enable Extreme-Scale Simulations under Uncertainty and System Faults [Conference Poster]. https://www.osti.gov/biblio/1470926 Publication ID: 58435
  • Debusschere, B., Pinar, A., Sargsyan, K., Templeton, J.A., & Najm, H.N. (2017). Predictive Fidelity Interpretability and Resilience of Machine Learning Methods Applied to Scientific Simulations [Conference Poster]. https://www.osti.gov/biblio/1508933 Publication ID: 58088
  • Najm, H.N., Debusschere, B., Safta, C., Sargsyan, K., Huan, X., Oefelein, J., Vane, Z., Eldred, M., Geraci, G., Knio, O., Sraj, I., Scovazzi, G., Colomes, O., Marzouk, Y., Zahm, O., Menhorn, F., Ghanem, R., & Tsilifis, P. (2017). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine [Conference Poster]. https://www.osti.gov/biblio/1574094 Publication ID: 58225
  • Najm, H.N., Sargsyan, K., Huan, X., Khalil, M., Hakim, L., Oefelein, J., Lacaze, G., & Vane, Z.P. (2017). Bayesian Estimation of Model Error in Physical Systems [Conference Poster]. https://www.osti.gov/biblio/1462640 Publication ID: 57594
  • Huan, X., Sargsyan, K., & Najm, H.N. (2017). A Non-Intrusive Embedding Approach for Statistical Characterization of Model Error [Conference Poster]. https://www.osti.gov/biblio/1462642 Publication ID: 57596
  • Huan, X., Sargsyan, K., & Najm, H.N. (2017). Bayesian Model Calibration with an Embedded Statistical Characterization of Model Error [Conference Poster]. https://www.osti.gov/biblio/1462643 Publication ID: 57597
  • Debusschere, B., Safta, C., Sargsyan, K., & Chowdhary, K. (2017). Polynomial Chaos Based Uncertainty Quantification [Conference Poster]. https://www.osti.gov/biblio/1513464 Publication ID: 57773
  • Debusschere, B., Safta, C., Sargsyan, K., & Chowdhary, K. (2017). Polynomial Chaos Based Uncertainty Quantification [Conference Poster]. https://www.osti.gov/biblio/1463445 Publication ID: 57774
  • Foulk, J.W., Rizzi, F., Cook, B., Dahlgren, K., Sargsyan, K., Mycek, P., le Maitre, O., Knio, O., & Debusschere, B. (2017). A Resilient ULFM-based PDE Solver: Performance Scaling and Energy Analysis [Conference Poster]. 10.1109/ScalA.2016.010 Publication ID: 56981
  • Rizzi, F., Foulk, J.W., Cook, B., Dahlgren, K., Sargsyan, K., Mycek, P., Lemaitre, O., Knio, O., & Debusschere, B. (2017). Scaling and Energy Analysis for a Resilient ULFM-Based PDE Solver [Conference Poster]. https://www.osti.gov/biblio/1476821 Publication ID: 56982
  • Foulk, J.W., Rizzi, F., Sargsyan, K., Dahlgren, K., Debusschere, B., Cook, B., Mycek, P., le Maitre, O., & Knio, O. (2017). Performance Scaling Variability and Energy Analysis for a Resilient ULFM-based PDE Solver [Presentation]. 10.1109/ScalA.2016.010 Publication ID: 56543
  • Sargsyan, K., Safta, C., Chowdhary, K., Castorena, S., de Bord, S., & Debusschere, B. (2017). UQTk Version 3.0.3 User Manual. 10.2172/1367452 Publication ID: 56649
  • Huan, X., Sargsyan, K., Vane, Z.P., Lacaze, G., Oefelein, J., & Najm, H.N. (2017). Quantifying Uncertainty from Model Error in Turbulent Combustion Applications [Conference Poster]. https://www.osti.gov/biblio/1456433 Publication ID: 55632
  • Huan, X., Safta, C., Geraci, G., Eldred, M., Vane, Z.P., Lacaze, G., Oefelein, J., Sargsyan, K., & Najm, H.N. (2017). Robust Compressive Sensing with Application to Multifidelity Analysis of Complex Turbulent Flows [Conference Poster]. https://www.osti.gov/biblio/1427446 Publication ID: 55202
  • Najm, H.N., Sargsyan, K., Huan, X., Hakim, L., Khalil, M., Oefelein, J., Lacaze, G., & Vane, Z.P. (2017). Model Error and Statistical Calibration of [Conference Poster]. https://www.osti.gov/biblio/1426633 Publication ID: 55340
  • Safta, C., Blaylock, M.L., Templeton, J.A., Domino, S.P., Sargsyan, K., & Najm, H.N. (2017). Uncertainty quantification in LES of channel flow. International Journal for Numerical Methods in Fluids, 83(4), pp. 376-401. 10.1002/fld.4272 Publication ID: 41556
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Contreras, A., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2017). Partial Differential Equations Solver Resilient to Soft and Hard Faults [Conference Poster]. https://www.osti.gov/biblio/1424869 Publication ID: 55125
  • Huan, X., Safta, C., Sargsyan, K., Geraci, G., Eldred, M., Vane, Z.P., Lacaze, G., Oefelein, J., & Najm, H.N. (2017). Global sensitivity analysis and quantification of model error for large eddy simulation in scramjet design [Conference Poster]. 19th AIAA Non-Deterministic Approaches Conference, 2017. 10.2514/6.2017-1089 Publication ID: 52795
  • Huan, X., Safta, C., Sargsyan, K., Geraci, G., Eldred, M., Vane, Z.P., Lacaze, G., Oefelein, J., & Najm, H.N. (2016). Global Sensitivity Analysis and Quantification of Model Form Error for Large Eddy Simulation of Scramjet Design [Conference Poster]. https://www.osti.gov/biblio/1413414 Publication ID: 48116
  • Sargsyan, K., Safta, C., Najm, H.N., Debusschere, B., Ricciuto, D., & Thornton, P. (2016). Weighted Iterative Bayesian Compressive Sensing (WIBCS) for High Dimensional Polynomial Surrogate Construction [Conference Poster]. https://www.osti.gov/biblio/1576186 Publication ID: 48156
  • Najm, H.N., Debusschere, B., Safta, C., Sargsyan, K., Huan, X., Oefelein, J., Lacaze, G., Vane, Z.P., Eldred, M., Geraci, G., Knio, O., Sraj, I., Scovazzi, G., Colomes, O., Marzouk, Y., Zahm, O., Menhorn, F., Ghanem, R., & Tsilifis, P. (2016). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine ? ScramjetUQ ? [Conference Poster]. https://www.osti.gov/biblio/1420843 Publication ID: 47626
  • Rizzi, F., Foulk, J.W., Cook, B., Sargsyan, K., Mycek, P., le Maitre, O., Knio, O., Dahlgren, K., & Debusschere, B. (2016). Performance Scaling Variability and Energy Analysis for a Resilient ULFM-based PDE Solver [Conference Poster]. https://www.osti.gov/biblio/1408949 Publication ID: 47715
  • Khalil, M., Chowdhary, K., Safta, C., Sargsyan, K., & Najm, H.N. (2016). Inference of reaction rate parameters based on summary statistics from experiments. Proceedings of the Combustion Institute. 10.1016/j.proci.2016.08.058 Publication ID: 50088
  • Najm, H.N., Sargsyan, K., Huan, X., Hakim, L., Oefelein, J., Lacaze, G., & Vane, Z.P. (2016). Uncertainty Quantification with Model Error [Conference Poster]. https://www.osti.gov/biblio/1527218 Publication ID: 52156
  • Carlberg, K.T., Guzzetta, S.L., Khalil, M., & Sargsyan, K. (2016). Uncertainty Propagation in (large-scale) Networks via Domain Decomposition [Presentation]. https://www.osti.gov/biblio/1393766 Publication ID: 52227
  • Sargsyan, K., Safta, C., Chowdhary, K., Castorena, S., de Bord, S., & Debusschere, B. (2016). UQTk (V. 3.0) User Manual. 10.2172/1562399 Publication ID: 52322
  • Najm, H.N., Sargsyan, K., Huan, X., Khalil, M., Hakim, L., Oefelein, J., Lacaze, G., & Vane, Z.P. (2016). Uncertainty Quantification with Model Error [Conference Poster]. https://www.osti.gov/biblio/1397104 Publication ID: 52533
  • Najm, H.N., Debusschere, B., Safta, C., Sargsyan, K., Huan, X., Oefelein, J., Lacaze, G., Vane, Z.P., Eldred, M., Geraci, G., Knio, O., Sraj, I., Scovazzi, G., Colomes, O., Marzouk, Y., Zahm, O., Augustin, F., Menhorn, F., Ghanem, R., & Tsilifis, P. (2016). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine [Conference Poster]. https://www.osti.gov/biblio/1397105 Publication ID: 52534
  • Huan, X., Safta, C., Eldred, M., Vane, Z.P., Lacaze, G., Oefelein, J., Sargsyan, K., & Najm, H.N. (2016). Global Sensitivity Analysis for Large Eddy Simulation Models [Conference Poster]. https://www.osti.gov/biblio/1372012 Publication ID: 51034
  • Teichman, S., & Sargsyan, K. (2016). Polynomial Surrogate Construction for Computational Models [Presentation]. https://www.osti.gov/biblio/1373064 Publication ID: 51257
  • Heindel, J., Rai, P., Jasper, A.W., Sargsyan, K., & Najm, H.N. (2016). Low-rank decomposition of potential energy surfaces for rovibrational properties at high energies [Presentation]. https://www.osti.gov/biblio/1373066 Publication ID: 51259
  • Najm, H.N., Sargsyan, K., Huan, X., Bender, J., & Ghanem, R. (2016). On Model Error and Statistical Calibration of Physical Models [Conference Poster]. https://www.osti.gov/biblio/1529794 Publication ID: 51268
  • Khalil, M., Chowdhary, K., Safta, C., Sargsyan, K., & Najm, H.N. (2016). Inference of reaction rate parameters based on summary statistics from experiments [Conference Poster]. 10.1016/j.proci.2016.08.058 Publication ID: 51426
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). ULFM-MPI Implementation of a Resilient Task-Based Partial Differential Equations Preconditioner [Conference Poster]. https://doi.org/10.1145/2909428.2909429 Publication ID: 49778
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). ULFM-MPI Implementation of a Resilient Task-Based Partial Differential Equations Preconditioner [Poster]. 10.2172/1561476 Publication ID: 49784
  • Foulk, J.W., Rizzi, F., Sargsyan, K., Dahlgren, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). Scalability of Partial Differential Equations Preconditioner Resilient to Soft and Hard Faults [Poster]. 10.2172/1561477 Publication ID: 49785
  • Foulk, J.W., Rizzi, F., Sargsyan, K., Dahlgren, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). Scalability of Partial Differential Equations Preconditioner Resilient to Soft and Hard Faults [Conference Poster]. https://doi.org/10.1007/978-3-319-41321-1_24 Publication ID: 49914
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). ULFM-MPI Implementation of a Resilient Task-Based Partial Differential Equations Preconditioner [Conference Poster]. https://doi.org/10.1145/2909428.2909429 Publication ID: 50023
  • Sargsyan, K., Huan, X., Najm, H.N., & Bender, J. (2016). Density Estimation Framework for Model Error Quantification [Conference Poster]. https://www.osti.gov/biblio/1368714 Publication ID: 50301
  • Oefelein, J., Hakim, L., Lacaze, G., Khalil, M., Sargsyan, K., & Najm, H.N. (2016). Parameter Estimation and Uncertainty Quantification in Turbulent Combustion Computations [Conference Poster]. https://www.osti.gov/biblio/1366683 Publication ID: 49208
  • Debusschere, B., Sargsyan, K., Safta, C., & Chowdhary, K. (2016). UQTk: A C++/Python Toolkit for Uncertainty Quantification [Conference Poster]. https://www.osti.gov/biblio/1530503 Publication ID: 49217
  • Foulk, J.W., Rizzi, F., Sargsyan, K., Mycek, P., Safta, C., Lemaitre, O., Knio, O., & Debusschere, B. (2016). ULFM-MPI Implementation of a Resilient Task-Based Preconditioner for 2D Uncertain Elliptic PDEs [Conference Poster]. https://www.osti.gov/biblio/1365075 Publication ID: 49272
  • Sargsyan, K. (2016). Probabilistic Methods for Uncertainty Quantification in Computational Models [Presentation]. https://www.osti.gov/biblio/1365204 Publication ID: 49510
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). Exploring the Interplay of Resilience and Energy Consumption for a Task-Based Partial Differential Equations Preconditioner. 10.2172/1561016 Publication ID: 48786
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Safta, C., Mycek, P., le Maitre, O., Knio, O., & Debusschere, B. (2016). Interplay of Resilience and Energy Consumption for a Task-Based Partial Differential Equations Preconditioner [Conference Poster]. https://www.osti.gov/biblio/1346895 Publication ID: 48793
  • Najm, H.N., Debusschere, B., Safta, C., Sargsyan, K., Oefelein, J., Lacaze, G., Eldred, M., Knio, O., Scovazzi, G., Marzouk, Y., & Ghanem, R. (2016). Uncertainty Quantification in LES Computations of Turbulent Multiphase Combustion in a Scramjet Engine [Conference Poster]. https://www.osti.gov/biblio/1530652 Publication ID: 49101
  • Safta, C., Chowdhary, K., Sargsyan, K., & Debusschere, B. (2016). Implementation of UQ Workflows with the C++/Python UQTk Toolkit [Conference Poster]. https://www.osti.gov/biblio/1618229 Publication ID: 49134
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). Quantifying Performance of a Resilient Elliptic PDE Solver on Uncertain Architectures using SST/macro [Conference Poster]. https://www.osti.gov/biblio/1530654 Publication ID: 49143
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). A Soft and Hard Faults Resilient Solver for 2D Elliptic PDEs via Server-Client Implementation [Conference Poster]. https://www.osti.gov/biblio/1618235 Publication ID: 49144
  • Khalil, M., Najm, H.N., Chowdhary, K., Safta, C., & Sargsyan, K. (2016). Probabilistic Inference of Model Parameters and Missing High-Dimensional Data Based on Summary Statistics [Conference Poster]. https://www.osti.gov/biblio/1618243 Publication ID: 49171
  • Sargsyan, K., Ricciuto, D., Thornton, P., Safta, C., Debusschere, B., & Najm, H.N. (2016). Quantifying the Impacts of Parametric Uncertainty on Biogeochemistry in the ACME Land Model [Conference Poster]. https://www.osti.gov/biblio/1366666 Publication ID: 49199
  • Sargsyan, K., Huan, X., & Najm, H.N. (2016). Density Estimation Framework for Model Error Quantification [Conference Poster]. https://www.osti.gov/biblio/1366667 Publication ID: 49200
  • Foulk, J.W., Rizzi, F., Sargsyan, K., Dahlgren, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). Scalability of partial differential equations preconditioner resilient to soft and hard faults [Conference Poster]. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-319-41321-1_24 Publication ID: 50587
  • Foulk, J.W., Rizzi, F., Sargsyan, K., Dahlgren, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2016). Scalability of partial differential equations preconditioner resilient to soft and hard faults [Conference Poster]. Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics. 10.1007/978-3-319-41321-1_24 Publication ID: 51019
  • Debusschere, B., Najm, H.N., Sargsyan, K., Chowdhary, K., Lucas, D., Bulaevskaya, V., Qian, Y., Ghan, S., Rosa, D., & Collins, B. (2015). Calibration and Comparison of Climate Models: Accounting for Structural and Discretization Error [Poster] [Conference Poster]. https://www.osti.gov/biblio/1239394 Publication ID: 46817
  • Debusschere, B., Najm, H.N., Sargsyan, K., Chowdhary, K., Lucas, D., Bulaevskaya, V., Qian, Y., Ghan, S., Rosa, D., & Collins, W. (2015). Calibration and Comparison of Climate Models: Accounting for Structural and Discretization Error [Conference Poster]. https://www.osti.gov/biblio/1338030 Publication ID: 41809
  • Rizzi, F., Knio, O., Jones, R.E., Adalsteisson, H., Najm, H.N., Sargsyan, K., Salloum, M., Safta, C., & Debusschere, B. (2015). UQ in Molecular Dynamics Simulations: Forward and Inverse Problem [Presentation]. https://www.osti.gov/biblio/1335540 Publication ID: 41880
  • Sargsyan, K., Safta, C., Najm, H.N., Debusschere, B., Ricciuto, D., & Thornton, P. (2015). Sparse Polynomial Chaos Surrogate for ACME Land Model via Iterative Bayesian Compressive Sensing [Conference Poster]. https://www.osti.gov/biblio/1335739 Publication ID: 41907
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Safta, C., le Maitre, O., Knio, O., & Debusschere, B. (2015). Partial differential equations preconditioner resilient to soft and hard faults [Conference Poster]. Proceedings – IEEE International Conference on Cluster Computing, ICCC. 10.1109/CLUSTER.2015.103 Publication ID: 45303
  • Debusschere, B., Sargsyan, K., Safta, C., & Chowdhary, K. (2015). The Uncertainty Quantification Toolkit (UQTk). https://www.osti.gov/biblio/1234310 Publication ID: 45961
  • Templeton, J.A., Blaylock, M.L., Domino, S.P., Hewson, J.C., Kumar, P.R., Ling, J., Najm, H.N., Ruiz, A., Safta, C., Sargsyan, K., Stewart, A., & Wagner, G. (2015). Calibration and Forward Uncertainty Propagation for Large-eddy Simulations of Engineering Flows. 10.2172/1221181 Publication ID: 45562
  • Najm, H.N., Sargsyan, K., Chowdhary, K., & Khalil, M. (2015). Computational Statistical Inverse Problems with Sparse or Missing Data [Conference Poster]. https://www.osti.gov/biblio/1312660 Publication ID: 45189
  • Sargsyan, K., Rai, P., Najm, H.N., Hermes, M., & Hirata, S. (2015). Low Rank Approximation-based Quadrature for Fast Evaluation of Multi-Particle Integrals. 10.2172/1221857 Publication ID: 45276
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Safta, C., Lemaitre, O., Knio, O., Najm, H.N., & Debusschere, B. (2015). Partial Differential Equations Solver Resilient to Soft and Hard Faults [Conference Poster]. https://www.osti.gov/biblio/1326569 Publication ID: 45304
  • Eldred, M., Debusschere, B., Chowdhary, K., Jakeman, J.D., Rai, P., Safta, C., & Sargsyan, K. (2015). Sandia Software Enabling Extreme-Scale Uncertainty Quantification [Conference Poster]. https://www.osti.gov/biblio/1266821 Publication ID: 44419
  • Rai, P., Sargsyan, K., Najm, H.N., Hirata, S., & Matthew, H. (2015). Low Rank Approximation-based Quadrature for Fast Evaluation of Multi-Particle Integrals [Conference Poster]. https://www.osti.gov/biblio/1266829 Publication ID: 44431
  • de Bord, S.I., Debusschere, B., & Sargsyan, K. (2015). Performance of Numerical Integration Methods for High-Dimensional Functions [Presentation]. https://www.osti.gov/biblio/1340032 Publication ID: 44553
  • Debusschere, B., Jakeman, J.D., Chowdhary, K., Safta, C., Sargsyan, K., Rai, P., Ghanem, R., Knio, O., la Maitre, O., Winokur, J., Li, G., Ghattas, O., Moser, R., Simmons, C., Alexanderian, A., Gattiker, J., Higdon, D., Lawrence, E., Bhat, S., … Parno, M. (2015). Quantification of Uncertainty in Extreme Scale Computations [Conference Poster]. https://www.osti.gov/biblio/1328212 Publication ID: 44684
  • Sargsyan, K., Najm, H.N., Jason, B., & Ghanem, R. (2015). Density Estimation Framework for Model Error Assessment [Conference Poster]. https://www.osti.gov/biblio/1279688 Publication ID: 44743
  • Lefantzi, S., Arunajatesan, S., Dechant, L., Hou, Z., Huang, M., Sargsyan, K., & Swiler, L.P. (2015). Bayesian calibration of engineering and scientific models using surrogates [Conference Poster]. https://www.osti.gov/biblio/1253310 Publication ID: 43426
  • Salloum, M., Sargsyan, K., Jones, R.E., Rizzi, F., Najm, H.N., & Debusschere, B. (2015). Quantifying Sampling Noise and Parametric Uncertainty in Coupled Atomistic-Continuum Simulations [Conference Poster]. https://www.osti.gov/biblio/1258267 Publication ID: 43585
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Safta, C., Mycek, P., Lemaitre, O., Najm, H.N., Knio, O., & Debusschere, B. (2015). Partial Differential Equations Solver Resilient to Soft and Hard Faults [Conference Poster]. https://www.osti.gov/biblio/1531275 Publication ID: 42991
  • Sargsyan, K., Safta, C., Najm, H.N., Debusschere, B., Ricciuto, D., & Thornton, P. (2015). High-Dimensional Sparse Surrogate Construction via Bayesian Compressive Sensing [Conference Poster]. https://www.osti.gov/biblio/1249469 Publication ID: 43203
  • Najm, H.N., Sargsyan, K., Bender, J., & Ghanem, R. (2015). Accounting for Model Error in the Calibration of Physical Models [Conference Poster]. https://www.osti.gov/biblio/1245918 Publication ID: 42523
  • Najm, H.N., Sargsyan, K., Bender, J., & Ghanem, R. (2015). Handling Model Error in the Calibration of Physical Models [Conference Poster]. https://www.osti.gov/biblio/1245934 Publication ID: 42747
  • Debusschere, B., & Sargsyan, K. (2015). Uncertainty Quantification – Lecture 3 [Presentation]. https://www.osti.gov/biblio/1531267 Publication ID: 41434
  • Debusschere, B., & Sargsyan, K. (2015). Uncertainty Quantification – Lecture 2 [Presentation]. https://www.osti.gov/biblio/1237887 Publication ID: 41435
  • Rizzi, F., Foulk, J.W., Sargsyan, K., Mycek, P., Safta, C., Lemaitre, O., Knio, O., Najm, H.N., & Debusschere, B. (2015). Partial Differential Equations Solver Resilient to Soft and Hard Faults [Conference Poster]. https://www.osti.gov/biblio/1238560 Publication ID: 41559
  • Safta, C., Sargsyan, K., Debusschere, B., & Najm, H.N. (2015). Hybrid discrete/continuum algorithms for stochastic reaction networks. Journal of Computational Physics, 281(C), pp. 177-198. 10.1016/j.jcp.2014.10.026 Publication ID: 31741
  • Safta, C., Sargsyan, K., Najm, H.N., Chowdhary, K., Debusschere, B., Swiler, L.P., & Eldred, M. (2015). Probabilistic methods for sensitivity analysis and calibration in the NASA challenge problem. Journal of Aerospace Information Systems, 12(1), pp. 219-234. 10.2514/1.I010256 Publication ID: 40146
  • Sargsyan, K., Safta, C., Debusschere, B., Najm, H.N., Rizzi, F., Foulk, J.W., Mycek, P., le Maitre, O., & Knio, O. (2015). Fault resilient domain decomposition preconditioner for PDES. SIAM Journal on Scientific Computing. 10.2172/1494624 Publication ID: 43981
  • Salloum, M., Sargsyan, K., Jones, R.E., Najm, H.N., & Debusschere, B. (2015). Quantifying sampling noise and parametric uncertainty in atomistic-to-continuum simulations using surrogate models. Multiscale Modeling and Simulation, 13(3), pp. 953-976. 10.1137/140989601 Publication ID: 97072
  • Pebay, P.P., Wilke, J., & Sargsyan, K. (2014). A Workflow for Parameter Calibration and and Model Validation in SST: Interim Report. 10.2172/1165842 Publication ID: 39833
  • Liu, Z., Pinto, J., Turner, A., Bruhwiler, L., Henze, D., Brioude, J., Bousserez, N., Sargsyan, K., Safta, C., Najm, H.N., Lafranchi, B.W., Bambha, R., & Michelsen, H.A. (2014). Contribution of Oil and Gas Production to Atmospheric CH4 int eh South-Central United States: Reconciling bottom-up and top-down estimates [Conference Poster]. https://www.osti.gov/biblio/1315004 Publication ID: 39873
  • Sargsyan, K., Najm, H.N., Safta, C., Debusschere, B., Ricciuto, D., & Thornton, P. (2014). Parameter Estimation in High-Dimensional Climate Models [Presentation]. https://www.osti.gov/biblio/1504061 Publication ID: 39875
  • Sargsyan, K., Najm, H.N., Safta, C., Michelsen, H.A., Bambha, R., Liu, Z., & van Bloemen Waanders, B. (2014). Density Estimation Framework for Model Error Assessmen [Presentation]. https://www.osti.gov/biblio/1504062 Publication ID: 39876
  • Salloum, M., Sargsyan, K., Jones, R.E., Rizzi, F., Najm, H.N., & Debusschere, B. (2014). Quantifying Sampling Noise and Parametric Uncertainty in Atomistic-to-Continuum Simulations using Surrogate Models [Conference Poster]. 10.1137/140989601 Publication ID: 39965
  • Michelsen, H.A., Liu, Z., Bambha, R., Lafranchi, B.W., Sargsyan, K., Safta, C., Najm, H.N., & Schrader, P. (2014). Sandia?s Work on Verifying CH4 Emissions [Presentation]. https://www.osti.gov/biblio/1502756 Publication ID: 38546
  • Liu, Z., Safta, C., Sargsyan, K., Najm, H.N., van Bloemen Waanders, B., Lafranchi, B.W., Ivey, M.D., Schrader, P., Michelsen, H.A., & Bambha, R. (2014). Greenhouse Gas Source Attribution: Measurements Modeling and Uncertainty Quantification. 10.2172/1322290 Publication ID: 38662
  • Rizzi, F., Sargsyan, K., Debusschere, B., Safta, C., Foulk, J.W., Knio, O., & Najm, H.N. (2014). Towards a Probabilistic Approach to Extreme-Scale Simulations under Uncertainty and System Faults [Presentation]. https://www.osti.gov/biblio/1569398 Publication ID: 37661
  • Michelsen, H.A., Bambha, R., Liu, Z., Schrader, P., Ivey, M.D., Roesler, E.L., Taylor, M.A., Lafranchi, B.W., Helsel, F.M., Najm, H.N., Sargsyan, K., & Safta, C. (2014). Black Carbon Methane and Carbon Dioxide: Measurement Modeling and Source Attribution [Presentation]. https://www.osti.gov/biblio/1494427 Publication ID: 37741
  • Eldred, M., Debusschere, B., Chowdhary, K., Jakeman, J.D., Najm, H.N., Safta, C., & Sargsyan, K. (2014). Sandia Software Enabling Extreme-Scale Uncertainty Quantification [Presentation]. https://www.osti.gov/biblio/1494264 Publication ID: 37782
  • Najm, H.N., Eldred, M., Debusschere, B., Chowdhary, K., Jakeman, J.D., Safta, C., & Sargsyan, K. (2014). An Overview of Select UQ Algorithms and their Utility in Applications [Presentation]. https://www.osti.gov/biblio/1494413 Publication ID: 37818
  • Jakeman, J.D., Eldred, M., & Sargsyan, K. (2014). Enhancing %601-minimization estimates of polynomial chaos expansions using basis selection. Journal of Computational Physics. https://www.osti.gov/biblio/1182997 Publication ID: 37936
  • Chowdhary, K., & Sargsyan, K. (2014). Uncertainty Quantification and Calibration of Physical Models [Conference]. https://www.osti.gov/biblio/1146585 Publication ID: 41001
  • Safta, C., Sargsyan, K., Debusschere, B., & Najm, H.N. (2014). Bayesian discontinuity detection and surrogate construction for complex computer models [Conference]. https://www.osti.gov/biblio/1142115 Publication ID: 40288
  • Ray, J., Swiler, L.P., & Sargsyan, K. (2014). BAYESIAN CALIBRATION OF THE COMMUNITY LAND MODEL USING SURROGATES. SIAM Journal of Uncertainty Quantification. https://www.osti.gov/biblio/1141039 Publication ID: 37288
  • Swiler, L.P., Ray, J., & Sargsyan, K. (2014). Bayesian calibration of hydrological parameters in the Community Land Model (CODA Presentation) [Conference]. https://www.osti.gov/biblio/1140888 Publication ID: 37304
  • Debusschere, B., Sargsyan, K., Rizzi, F., Safta, C., Morris Wright, K.V., & Najm, H.N. (2014). Probabilistic Approaches for Fault-Tolerance and Scalability in Extreme-Scale Computing [Conference]. https://www.osti.gov/biblio/1141119 Publication ID: 37274
  • Sargsyan, K., Najm, H.N., Chowdhary, K., Debusschere, B., Swiler, L.P., & Eldred, M. (2013). Uncertainty Quantification Methods for Model Calibration Validation and Risk Analysis [Conference]. 10.2514/6.2014-1497 Publication ID: 36802
  • Sargsyan, K., Debusschere, B., & Najm, H.N. (2013). Global Sensitivity Analysis and Parameter Calibration for an Ecosystem Carbon Model [Conference]. https://www.osti.gov/biblio/1122345 Publication ID: 31837
  • Sargsyan, K., Najm, H.N., Chowdhary, K., Debusschere, B., Swiler, L.P., & Eldred, M. (2013). Uncertainty Quantification Methods for Model Calibration Validation and Risk Analysis [Conference]. https://doi.org/10.2514/6.2014-1497 Publication ID: 31866
  • Najm, H.N., Chowdhary, K., Sargsyan, K., & Debusschere, B. (2013). Inference of Chemical Model Parameters given Partial Information [Conference]. https://www.osti.gov/biblio/1121920 Publication ID: 31788
  • Sargsyan, K. (2013). Bayesian compressive sensing and dimensionality reduction for high-dimensional models [Conference]. https://www.osti.gov/biblio/1122434 Publication ID: 31851
  • Debusschere, B., Safta, C., Sargsyan, K., & Najm, H.N. (2013). Hybrid Discrete / Continuum Algorithms for Stochastic Reaction Networks [Presentation]. https://www.osti.gov/biblio/1673517 Publication ID: 36133
  • Kenny, J., Hendry, G., Sargsyan, K., & Dechev, D. (2013). SST/macro Manual [Presentation]. https://www.osti.gov/biblio/1673515 Publication ID: 36169
  • Debusschere, B., Sargsyan, K., & Safta, C. (2013). UQTk version 2.0 user manual. 10.2172/1115280 Publication ID: 36357
  • Prager, J., Najm, H.N., Sargsyan, K., & Safta, C. (2013). Uncertainty quantification of reaction mechanisms accounting for correlations introduced by rate rules and fitted Arrhenius parameters. Combustion and Flame, 160(9), pp. 1583-1593. https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84879460812&origin=inward Publication ID: 30513
  • Safta, C., Debusschere, B., Sargsyan, K., & Najm, H.N. (2013). Hybrid Discrete – Continuum Algorithms for Stochastic Reaction Networks [Conference]. https://www.osti.gov/biblio/1106462 Publication ID: 34957
  • Debusschere, B., Najm, H.N., Sargsyan, K., & Safta, C. (2013). Probabilistic Approaches for Communication Avoidance and Resilience in Exascale Simulations [Conference]. https://www.osti.gov/biblio/1140465 Publication ID: 35230
  • Wilke, J., Sargsyan, K., Kenny, J., Hendry, G., Debusschere, B., & Najm, H.N. (2013). Presentation: Validating extreme-scale HPC simulation through Bayesian inference uncertainty quantification [Conference]. https://www.osti.gov/biblio/1107500 Publication ID: 35260
  • Hendry, G., Wilke, J., Kenny, J., Sargsyan, K., Drohmann, M., & Allan, B.A. (2013). SST/macro: A coarse-grained simulation workflow [Conference]. https://www.osti.gov/biblio/1106483 Publication ID: 34424
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2013). Sparse surrogate model construction via compressive sensing [Conference]. https://www.osti.gov/biblio/1106053 Publication ID: 34576
  • Safta, C., Sargsyan, K., Debusschere, B., & Najm, H.N. (2013). DALEC calibration with daily NEE Data at Harvard Forest [Presentation]. https://www.osti.gov/biblio/1661144 Publication ID: 33614
  • Najm, H.N., Chowdhary, K., Safta, C., Sargsyan, K., & Debusschere, B. (2013). Parameter Estimation with Partial Information [Conference]. https://www.osti.gov/biblio/1079802 Publication ID: 33659
  • Debusschere, B., Sargsyan, K., Safta, C., & Najm, H.N. (2013). UQ tutorial slides [Presentation]. https://www.osti.gov/biblio/1661320 Publication ID: 33766
  • Najm, H.N., Safta, C., Sargsyan, K., Debusschere, B., & Chowdhary, K. (2013). Parameter Estimation with Missing Data [Conference]. https://www.osti.gov/biblio/1078649 Publication ID: 32977
  • Najm, H.N., Safta, C., Sargsyan, K., Debusschere, B., & Chowdhary, K. (2013). QUEST SNL Activities [Conference]. https://www.osti.gov/biblio/1115638 Publication ID: 33185
  • Debusschere, B., Sargsyan, K., Safta, C., Hendry, G., & Najm, H.N. (2013). Probabilistic Schwarz Coupling for Fault-Tolerance and Scalability [Conference]. https://www.osti.gov/biblio/1115986 Publication ID: 32388
  • Safta, C., Sargsyan, K., Debusschere, B., & Najm, H.N. (2013). Dimensionality Reduction and Global Sensitivity Analysis for the Community Land Model [Conference]. https://www.osti.gov/biblio/1063570 Publication ID: 32141
  • Wilke, J., Sargsyan, K., Kenny, J., Hendry, G., Debusschere, B., & Najm, H.N. (2013). Validating extreme-scale HPC simulation through Bayesian inference uncertainty quantification [Conference]. https://www.osti.gov/biblio/1063301 Publication ID: 32117
  • Safta, C., Sargsyan, K., Debusschere, B., & Najm, H.N. (2013). Hybrid Discrete/Continuum Algorithms for Stochastic Reaction Networks [Conference]. https://www.osti.gov/biblio/1145251 Publication ID: 32344
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2012). Multiparameter spectral representation of noise-induced competence in bacillus subtilis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(6), pp. 1709-1723. https://doi.org/10.1109/TCBB.2012.107 Publication ID: 25769
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2012). Multiparameter spectral representation of noise-induced competence in bacillus subtilis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(6), pp. 1709-1723. 10.1109/TCBB.2012.107 Publication ID: 26085
  • Ray, J., & Sargsyan, K. (2012). Bayesian calibration of the Community Land Model using surrogates [Conference]. https://www.osti.gov/biblio/1063367 Publication ID: 26321
  • Sargsyan, K. (2012). Surrogate-Based Uncertainty Quantification in Climate Models [Conference]. https://www.osti.gov/biblio/1063531 Publication ID: 26327
  • Liu, Z., Safta, C., Sargsyan, K., van Bloemen Waanders, B., Bambha, R., & Michelsen, H.A. (2012). Verifying fossil fuel CO2 emissions with CMAQ [Conference]. https://www.osti.gov/biblio/1295396 Publication ID: 26335
  • Bambha, R., Liu, Z., Safta, C., Sargsyan, K., & van Bloemen Waanders, B. (2012). Verifying fossil fuel CO2 emissions with CMAQ [Conference]. https://www.osti.gov/biblio/1072623 Publication ID: 30629
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2012). Project report for Stochastic Dynamical Systems: Analysis of Dynamics and Predictability [Presentation]. https://www.osti.gov/biblio/1648427 Publication ID: 30930
  • Salloum, M., Sargsyan, K., Jones, R.E., Debusschere, B., Najm, H.N., & Adalsteinsson, H. (2012). A stochastic multiscale coupling scheme to account for sampling noise in atomistic-to-continuum simulations. Multiscale Modeling and Simulation, 10(2), pp. 550-584. https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84865699428&origin=inward Publication ID: 24093
  • Liu, Z., Safta, C., Sargsyan, K., van Bloemen Waanders, B., Debusschere, B., Najm, H.N., & Bambha, R. (2012). Uncertainty Analysis and Bayesian Inference of Emissions and Transport from Urban Areas [Conference]. https://www.osti.gov/biblio/1073293 Publication ID: 29491
  • Debusschere, B., Najm, H.N., Safta, C., & Sargsyan, K. (2012). Polynomial Chaos based uncertainty propagation Intrusive and Non-Intrusive Methods [Presentation]. https://www.osti.gov/biblio/1647838 Publication ID: 29720
  • Najm, H.N., Sargsyan, K., Safta, C., Debusschere, B., Jakeman, J.D., & Eldred, M. (2012). Sparse Polynomial Representations of High Dimensional Models [Conference]. https://www.osti.gov/biblio/1073443 Publication ID: 28932
  • Najm, H.N., Safta, C., Debusschere, B., & Sargsyan, K. (2012). Uncertainty Quantification in the Community Land Model [Conference]. https://www.osti.gov/biblio/1073227 Publication ID: 28695
  • Najm, H.N., Safta, C., Sargsyan, K., & Debusschere, B. (2012). INFERENCE OF UNCERTAIN PARAMETERS IN CHEMICALMODELS. Proposed for publication in International Journal for Uncertainty Quantification.. https://www.osti.gov/biblio/1073410 Publication ID: 28829
  • Najm, H.N., Debusschere, B., Safta, C., & Sargsyan, K. (2012). Bayesian Parameter Estimation with Partial Information [Conference]. https://www.osti.gov/biblio/1073174 Publication ID: 27998
  • Sargsyan, K. (2012). Adaptive Basis Selection and Dimensionality Reduction with Bayesian Compressive Sensing [Conference]. https://www.osti.gov/biblio/1078647 Publication ID: 27438
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2012). Coupled Chemical Master Equation – Fokker Planck Solver for Stochastic Reaction Networks [Conference]. https://www.osti.gov/biblio/1068329 Publication ID: 27466
  • Safta, C., Sargsyan, K., Debusschere, B., & Najm, H.N. (2012). Efficient Surrogate Construction for High-Dimensional Climate Model [Conference]. https://www.osti.gov/biblio/1078600 Publication ID: 27471
  • Debusschere, B., Safta, C., & Sargsyan, K. (2012). Uncertainty Quantification: UQTk example problems [Presentation]. https://www.osti.gov/biblio/1657036 Publication ID: 27529
  • Sargsyan, K., Jones, R.E., Debusschere, B., & Najm, H.N. (2012). Quantifying Sampling Noise and Parametric Uncertainty in Coupled Atomistic-Continuum Simulations [Conference]. https://www.osti.gov/biblio/1078657 Publication ID: 27422
  • Sargsyan, K., Safta, C., Berry, R.D., Debusschere, B., & Najm, H.N. (2011). Uncertainty Quantification in ClimateModeling [Conference]. https://www.osti.gov/biblio/1106672 Publication ID: 25612
  • Safta, C., Sargsyan, K., Bambha, R., Michelsen, H.A., Debusschere, B., Najm, H.N., & van Bloemen Waanders, B. (2011). Efficient Source Inversion Methodologies using Regional Transport Models [Conference]. https://www.osti.gov/biblio/1106861 Publication ID: 25603
  • Sargsyan, K., Safta, C., Berry, R.D., Ray, J., Debusschere, B., & Najm, H.N. (2011). Efficient uncertainty quantification methodologies for high-dimensional climate land models. 10.2172/1113860 Publication ID: 25433
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2011). Bayesian Quantification of Uncertainty in Systems with Intrinsic Noise [Presentation]. https://www.osti.gov/biblio/1728568 Publication ID: 24910
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2011). Bayesian Quantification of Uncertainty in Systems with Intrinsic Noise [Presentation]. https://www.osti.gov/biblio/1728569 Publication ID: 24979
  • Salloum, M., Jones, R.E., Sargsyan, K., Debusschere, B., & Najm, H.N. (2011). Propagating Uncertainty from Simulation Parameters and Sampling Noise through Coupled Atomistic-to-Continuum Systems [Conference]. https://www.osti.gov/biblio/1106012 Publication ID: 25040
  • Safta, C., Ray, J., Sargsyan, K., & Lefantzi, S. (2011). Real-time Characterization of Partially Observed Epidemics using Surrogate Models. Mathematical Biosciences. https://www.osti.gov/biblio/1106850 Publication ID: 24392
  • Safta, C., Ray, J., Sargsyan, K., & Lefantzi, S. (2011). Real-time characterization of partially observed epidemics using surrogate models. https://doi.org/10.2172/1030325 Publication ID: 24467
  • Sargsyan, K., Safta, C., Berry, R.D., Debusschere, B., & Najm, H.N. (2011). Uncertainty Quantication in Climate Modeling [Conference]. https://www.osti.gov/biblio/1106987 Publication ID: 23958
  • Najm, H.N., Safta, C., Sargsyan, K., & Debusschere, B. (2011). Uncertainty Quantification given Discontinuities Long-tailed Distributions and Computationally Intensive Models [Conference]. https://www.osti.gov/biblio/1106267 Publication ID: 23598
  • Najm, H.N., Salloum, M., Sargsyan, K., Jones, R.E., Debusschere, B., & Adalsteinsson, H. (2011). Uncertainty Quantification in Multiscale Atomistic-Continuum Models [Conference]. https://www.osti.gov/biblio/1107557 Publication ID: 23193
  • Safta, C., Sargsyan, K., Debusschere, B., & Najm, H.N. (2011). Uncertainty Quantification given Discontinuities Long-tailed Distributions and Computationally Intensive Models [Conference]. https://www.osti.gov/biblio/1109206 Publication ID: 21791
  • Salloum, M., Sargsyan, K., Jones, R.E., Debusschere, B., Najm, H.N., & Adalsteinsson, H. (2011). Stochastic Atomistic-to-Continuum Coupling using Bayesian inference [Presentation]. https://www.osti.gov/biblio/1671594 Publication ID: 21810
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2010). Uncertainty quantification given discontinuous climate model response and a limited number of model runs [Conference]. https://www.osti.gov/biblio/1038998 Publication ID: 21059
  • Sargsyan, K., Najm, H.N., & Debusschere, B. (2010). Sources of Cell-to-Cell Variability in NFkB Signaling Based on Pathways Inferred from Single Cell Dynamic Images. PLoS Computational Biology. https://www.osti.gov/biblio/1114593 Publication ID: 21131
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2010). Uncertainty Quantication given Discontinuous Model Response and a Limited Number of Model Runs. SIAM Journal on Scientific Computing. https://www.osti.gov/biblio/1114609 Publication ID: 21124
  • Safta, C., Debusschere, B., Najm, H.N., & Sargsyan, K. (2010). Advanced methods for uncertainty quantification in tail regions of climate model predictions [Conference]. https://www.osti.gov/biblio/1038989 Publication ID: 21125
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2010). Uncertainty quantification in the presence of limited climate model data with discontinuities [Conference]. https://www.osti.gov/biblio/1028371 Publication ID: 19676
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2010). Advanced methods for uncertainty quantification in tail regions of climate model predictions [Conference]. https://www.osti.gov/biblio/1028370 Publication ID: 19677
  • Safta, C., Sargsyan, K., Debusschere, B., & Najm, H.N. (2010). Uncertainty quantification for large-scale ocean circulation predictions. 10.2172/1008117 Publication ID: 19790
  • Frank, J.H., Lawson, M., Sargsyan, K., Debusschere, B., & Najm, H.N. (2010). Uncertainty quantification of cinematic imaging for development of predictive simulations of turbulent combustion. 10.2172/1011617 Publication ID: 21159
  • Safta, C., Sargsyan, K., Debusschere, B., & Najm, H.N. (2010). Accuracy of tail regions in uncertain climate model [Conference]. https://www.osti.gov/biblio/1123302 Publication ID: 19121
  • Sargsyan, K., Debusschere, B., & Najm, H.N. (2010). Predictability in stochastic reaction networks [Conference]. https://www.osti.gov/biblio/1021668 Publication ID: 19145
  • Sargsyan, K., & Debusschere, B. (2010). Uncertainty quantification methodologies for climate model data with discontinuities [Conference]. https://www.osti.gov/biblio/1021667 Publication ID: 19146
  • Sargsyan, K., & Debusschere, B. (2010). Uncertainty quantification in climate modeling [Conference]. https://www.osti.gov/biblio/1021665 Publication ID: 19147
  • Safta, C., Debusschere, B., Najm, H.N., & Sargsyan, K. (2010). Bayesian methods for discontinuity detection in climate model predictions [Conference]. https://www.osti.gov/biblio/1020453 Publication ID: 18589
  • Adalsteinsson, H., Debusschere, B., Najm, H.N., Jones, R.E., & Sargsyan, K. (2010). Quantifying prediction fidelity in multiscale multiphysics simulations [Conference]. https://www.osti.gov/biblio/1012450 Publication ID: 18179
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2009). Uncertainty quantification in the presence of limited climate model data with discontinuities [Conference]. ICDM Workshops 2009 – IEEE International Conference on Data Mining. https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77951182165&origin=inward Publication ID: 16551
  • Sargsyan, K., Safta, C., Debusschere, B., & Najm, H.N. (2009). Uncertainty quantification in the presence of limited climate model data with discontinuities [Conference]. https://www.osti.gov/biblio/972860 Publication ID: 17075
  • Sargsyan, K., Debusschere, B., Safta, C., & Najm, H.N. (2009). Uncertainty Quanti%02cation for Large-Scale Ocean Circulation Predictions [Conference]. https://www.osti.gov/biblio/1142141 Publication ID: 17076
  • Sargsyan, K., Debusschere, B., & Najm, H.N. (2008). Predictability and reduced order modeling in stochastic reaction networks [Conference]. https://www.osti.gov/biblio/970272 Publication ID: 15068
  • Sargsyan, K., Debusschere, B., Najm, H.N., & Marzouk, Y.M. (2008). Predictability Assessment in Stochastic Reaction Networks. Journal of Computational and Theoretical Nanoscience. https://www.osti.gov/biblio/1182955 Publication ID: 13463
  • Sargsyan, K., Debusschere, B., Najm, H.N., & Marzouk, Y.M. (2007). Uncertainty Quantification in Stochastic Reaction Networks [Presentation]. https://www.osti.gov/biblio/1714450 Publication ID: 12242
Showing 5 of 282 publications.