Alireza Doostan

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Gianluca IaccarinoStanford UniversityZweryfikowany adres z stanford.edu
Jerrad HamptonSiemens EnergyZweryfikowany adres z siemens-energy.com
Brandon A. JonesThe University of Texas at AustinZweryfikowany adres z utexas.edu
Kurt MauteProfessor of Aerospace Engineering, University of Colorado BoulderZweryfikowany adres z colorado.edu
Roger GhanemProfessor Civil Engineering, University of Southern CaliforniaZweryfikowany adres z usc.edu
John A. EvansAssociate Professor, Jack Rominger Faculty Fellow, University of Colorado BoulderZweryfikowany adres z colorado.edu
Mark HadigolPfizerZweryfikowany adres z pfizer.com
Iman HajirasoulihaProfessor of Structural Engineering, The University of SheffieldZweryfikowany adres z sheffield.ac.uk
Paul G. ConstantineAssistant Professor of Computer Science, University of Colorado BoulderZweryfikowany adres z colorado.edu
Gianluca GeraciSandia National LaboratoriesZweryfikowany adres z sandia.gov
Ji PengData Science at EarninZweryfikowany adres z earnin.com
Akil NarayanUniversity of UtahZweryfikowany adres z sci.utah.edu
Jan NordströmProfessor in Scientific Computing, Linköping University and University of JohannesburgZweryfikowany adres z liu.se
Per PetterssonSenior researcher, NORCE Norwegian Research CentreZweryfikowany adres z norceresearch.no
Jay McMahonUniversity of ColoradoZweryfikowany adres z colorado.edu
Daniel J. ScheeresUniversity of ColoradoZweryfikowany adres z colorado.edu
Gregory BeylkinProfessor of Applied Mathematics, University of Colorado at BoulderZweryfikowany adres z colorado.edu
Paul Diaz, Ph.D.Red Canyon Software & EngineeringZweryfikowany adres z colorado.edu
Hermann G MatthiesProfessor of Computer Science, Inst. of Scientific Computing, TU BraunschweigZweryfikowany adres z tu-bs.de
Qiqi WangAssociate Professor of Aeronautics and Astronautics, MITZweryfikowany adres z mit.edu

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Alireza Doostan

University of Colorado, Boulder

Zweryfikowany adres z colorado.edu - Strona główna

Uncertainty quantification computational mechanics


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
A non-adapted sparse approximation of PDEs with stochastic inputs A Doostan, H Owhadi Journal of Computational Physics 230 (8), 3015-3034, 2011	507	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	243	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	239	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	237	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	227	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	175	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	167	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	121	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	117	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	113	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	110	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	105	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	99	2008
Satellite collision probability estimation using polynomial chaos expansions BA Jones, A Doostan Advances in Space Research 52 (11), 1860-1875, 2013	98	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	82	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	75	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	73	2012

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