Alireza Doostan

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Gianluca IaccarinoStanford UniversityEmail yang diverifikasi di stanford.edu
Jerrad HamptonSiemens EnergyEmail yang diverifikasi di siemens-energy.com
Brandon A. JonesThe University of Texas at AustinEmail yang diverifikasi di utexas.edu
Kurt MauteProfessor of Aerospace Engineering, University of Colorado BoulderEmail yang diverifikasi di colorado.edu
Roger GhanemProfessor Civil Engineering, University of Southern CaliforniaEmail yang diverifikasi di usc.edu
John A. EvansAssociate Professor, Jack Rominger Faculty Fellow, University of Colorado BoulderEmail yang diverifikasi di colorado.edu
Mark HadigolPfizerEmail yang diverifikasi di pfizer.com
Iman HajirasoulihaProfessor of Structural Engineering, The University of SheffieldEmail yang diverifikasi di sheffield.ac.uk
Paul G. ConstantineAssistant Professor of Computer Science, University of Colorado BoulderEmail yang diverifikasi di colorado.edu
Gianluca GeraciSandia National LaboratoriesEmail yang diverifikasi di sandia.gov
Ji PengData Science at EarninEmail yang diverifikasi di earnin.com
Akil NarayanUniversity of UtahEmail yang diverifikasi di sci.utah.edu
Jan NordströmProfessor in Scientific Computing, Linköping University and University of JohannesburgEmail yang diverifikasi di liu.se
Per PetterssonSenior researcher, NORCE Norwegian Research CentreEmail yang diverifikasi di norceresearch.no
Jay McMahonUniversity of ColoradoEmail yang diverifikasi di colorado.edu
Daniel J. ScheeresUniversity of ColoradoEmail yang diverifikasi di colorado.edu
Rene PecnikDelft University of TechnologyEmail yang diverifikasi di tudelft.nl
Jeroen A.S. WitteveenScientific Staff Member, Center for Mathematics and Computer Science (CWI), AmsterdamEmail yang diverifikasi di cwi.nl
Gregory BeylkinProfessor of Applied Mathematics, University of Colorado at BoulderEmail yang diverifikasi di colorado.edu
Paul Diaz, Ph.D.Red Canyon Software & EngineeringEmail yang diverifikasi di colorado.edu

Ikuti

Alireza Doostan

University of Colorado, Boulder

Email yang diverifikasi di colorado.edu - Beranda

Uncertainty quantification computational mechanics


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
A non-adapted sparse approximation of PDEs with stochastic inputs A Doostan, H Owhadi Journal of Computational Physics 230 (8), 3015-3034, 2011	505	2011
Stochastic model reduction for chaos representations A Doostan, RG Ghanem, J Red-Horse Computer methods in applied mechanics and engineering 196 (37-40), 3951-3966, 2007	246	2007
Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies J Hampton, A Doostan Journal of Computational Physics 280, 363-386, 2015	237	2015
Nonlinear propagation of orbit uncertainty using non-intrusive polynomial chaos BA Jones, A Doostan, GH Born Journal of Guidance, Control, and Dynamics 36 (2), 430-444, 2013	237	2013
A weighted ℓ1-minimization approach for sparse polynomial chaos expansions J Peng, J Hampton, A Doostan Journal of Computational Physics 267, 92-111, 2014	234	2014
On the construction and analysis of stochastic models: characterization and propagation of the errors associated with limited data RG Ghanem, A Doostan Journal of Computational Physics 217 (1), 63-81, 2006	230	2006
Least squares polynomial chaos expansion: A review of sampling strategies M Hadigol, A Doostan Computer Methods in Applied Mechanics and Engineering 332, 382-407, 2018	182	2018
A least-squares approximation of partial differential equations with high-dimensional random inputs A Doostan, G Iaccarino Journal of computational physics 228 (12), 4332-4345, 2009	180	2009
Coherence motivated sampling and convergence analysis of least squares polynomial Chaos regression J Hampton, A Doostan Computer Methods in Applied Mechanics and Engineering 290, 73-97, 2015	165	2015
Non-intrusive low-rank separated approximation of high-dimensional stochastic models A Doostan, AA Validi, G Iaccarino Computer Methods in Applied Mechanics and Engineering 263, 42-55, 2013	118	2013
Sparse polynomial chaos expansions via compressed sensing and D-optimal design P Diaz, A Doostan, J Hampton Computer Methods in Applied Mechanics and Engineering 336, 640-666, 2018	116	2018
A simple and efficient preconditioning scheme for heaviside enriched XFEM C Lang, D Makhija, A Doostan, K Maute Computational Mechanics 54, 1357-1374, 2014	112	2014
Optimum seismic design of concentrically braced steel frames: concepts and design procedures H Moghaddam, I Hajirasouliha, A Doostan Journal of Constructional Steel Research 61 (2), 151-166, 2005	107	2005
Padé–Legendre approximants for uncertainty analysis with discontinuous response surfaces T Chantrasmi, A Doostan, G Iaccarino Journal of Computational Physics 228 (19), 7159-7180, 2009	106	2009
On polynomial chaos expansion via gradient-enhanced ℓ1-minimization J Peng, J Hampton, A Doostan Journal of Computational Physics 310, 440-458, 2016	102	2016
A probabilistic construction of model validation RG Ghanem, A Doostan, J Red-Horse Computer Methods in Applied Mechanics and Engineering 197 (29-32), 2585-2595, 2008	98	2008
Satellite collision probability estimation using polynomial chaos expansions BA Jones, A Doostan Advances in Space Research 52 (11), 1860-1875, 2013	97	2013
Sparse identification of nonlinear dynamical systems via reweighted ℓ1-regularized least squares A Cortiella, KC Park, A Doostan Computer Methods in Applied Mechanics and Engineering 376, 113620, 2021	81	2021
On transfer learning of neural networks using bi-fidelity data for uncertainty propagation S De, J Britton, M Reynolds, R Skinner, K Jansen, A Doostan International Journal for Uncertainty Quantification 10 (6), 2020	76	2020
Stochastic identification of composite material properties from limited experimental databases, Part II: Uncertainty modelling L Mehrez, A Doostan, D Moens, D Vandepitte Mechanical Systems and Signal Processing 27, 484-498, 2012	74	2012

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