Cosmin Safta
Cited by
Cited by
Dimensionality reduction for complex models via Bayesian compressive sensing
K Sargsyan, C Safta, HN Najm, BJ Debusschere, D Ricciuto, P Thornton
International Journal for Uncertainty Quantification 4 (1), 2014
A survey of constrained Gaussian process regression: Approaches and implementation challenges
LP Swiler, M Gulian, AL Frankel, C Safta, JD Jakeman
Journal of Machine Learning for Modeling and Computing 1 (2), 2020
Uncertainty quantification of reaction mechanisms accounting for correlations introduced by rate rules and fitted Arrhenius parameters
J Prager, HN Najm, K Sargsyan, C Safta, WJ Pitz
Combustion and flame 160 (9), 1583-1593, 2013
Compressive sensing adaptation for polynomial chaos expansions
P Tsilifis, X Huan, C Safta, K Sargsyan, G Lacaze, JC Oefelein, HN Najm, ...
Journal of Computational Physics 380, 29-47, 2019
The Uncertainty Quantification Toolkit (UQTk).
B Debusschere, K Sargsyan, C Safta, KS Chowdhary
Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2015
Efficient uncertainty quantification in stochastic economic dispatch
C Safta, RLY Chen, HN Najm, A Pinar, JP Watson
IEEE Transactions on Power Systems 32 (4), 2535-2546, 2016
TChem-a software toolkit for the analysis of complex kinetic models
C Safta, HN Najm, O Knio
Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2011
Uncertainty quantification given discontinuous model response and a limited number of model runs
K Sargsyan, C Safta, B Debusschere, H Najm
SIAM Journal on Scientific Computing 34 (1), B44-B64, 2012
Chemical model reduction under uncertainty
RM Galassi, M Valorani, HN Najm, C Safta, M Khalil, PP Ciottoli
Combustion and Flame 179, 242-252, 2017
Compressive sensing with cross-validation and stop-sampling for sparse polynomial chaos expansions
X Huan, C Safta, K Sargsyan, ZP Vane, G Lacaze, JC Oefelein, HN Najm
SIAM/ASA Journal on Uncertainty Quantification 6 (2), 907-936, 2018
Global sensitivity analysis and estimation of model error, toward uncertainty quantification in scramjet computations
X Huan, C Safta, K Sargsyan, G Geraci, MS Eldred, ZP Vane, G Lacaze, ...
AIAA Journal 56 (3), 1170-1184, 2018
Autoignition and structure of nonpremixed CH4/H2 flames: detailed and reduced kinetic models
C Safta, CK Madnia
Combustion and flame 144 (1-2), 64-73, 2006
Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods
D Lu, D Ricciuto, A Walker, C Safta, W Munger
Biogeosciences 14 (18), 4295-4314, 2017
A high-order low-Mach number AMR construction for chemically reacting flows
C Safta, J Ray, HN Najm
Journal of Computational Physics 229 (24), 9299-9322, 2010
Entropy-based closure for probabilistic learning on manifolds
C Soize, R Ghanem, C Safta, X Huan, ZP Vane, J Oefelein, G Lacaze, ...
Journal of Computational Physics 388, 518-533, 2019
Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds
RG Ghanem, C Soize, C Safta, X Huan, G Lacaze, JC Oefelein, HN Najm
Journal of Computational Physics 399, 108930, 2019
A second-order coupled immersed boundary-SAMR construction for chemically reacting flow over a heat-conducting Cartesian grid-conforming solid
KS Kedia, C Safta, J Ray, HN Najm, AF Ghoniem
Journal of Computational Physics 272, 408-428, 2014
Data-free inference of uncertain parameters in chemical models
HN Najm, RD Berry, C Safta, K Sargsyan, BJ Debusschere
International Journal for Uncertainty Quantification 4 (2), 2014
Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model
C Safta, DM Ricciuto, K Sargsyan, B Debusschere, HN Najm, M Williams, ...
Geoscientific Model Development 8 (7), 1899-1918, 2015
Probabilistic methods for sensitivity analysis and calibration in the NASA challenge problem
C Safta, K Sargsyan, HN Najm, K Chowdhary, B Debusschere, LP Swiler, ...
Journal of Aerospace Information Systems 12 (1), 219-234, 2015
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