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ORCIDAlireza Doostan
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2020 – today
- 2024
[j29]Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan:
QuadConv: Quadrature-based convolutions with applications to non-uniform PDE data compression. J. Comput. Phys. 498: 112636 (2024)- [j28]Nuojin Cheng, Osman Asif Malik
, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan:
Subsampling of Parametric Models with Bifidelity Boosting. SIAM/ASA J. Uncertain. Quantification 12(2): 213-241 (2024) - [i22]Angran Li, Stephen Becker, Alireza Doostan:
Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction. CoRR abs/2405.16076 (2024) - [i21]Grant Norman, Jacqueline Wentz, Hemanth Kolla, Kurt Maute, Alireza Doostan:
Constrained or Unconstrained? Neural-Network-Based Equation Discovery from Data. CoRR abs/2406.02581 (2024) - 2023
- [j27]Jacqueline Wentz, Alireza Doostan:
GenMod: A generative modeling approach for spectral representation of PDEs with random inputs. J. Comput. Phys. 472: 111691 (2023) - [j26]Jeffrey M. Hokanson, Gianluca Iaccarino, Alireza Doostan:
Simultaneous Identification and Denoising of Dynamical Systems. SIAM J. Sci. Comput. 45(4) (2023) - [i20]Nuojin Cheng, Osman Asif Malik, Stephen Becker, Alireza Doostan:
Bi-fidelity Variational Auto-encoder for Uncertainty Quantification. CoRR abs/2305.16530 (2023) - [i19]Riccardo Balin, Filippo Simini, Cooper Simpson, Andrew Shao, Alessandro Rigazzi, Matthew Ellis, Stephen Becker, Alireza Doostan, John A. Evans, Kenneth E. Jansen:
In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD. CoRR abs/2306.12900 (2023) - [i18]Malik Hassanaly, Peter J. Weddle, Ryan N. King, Subhayan De, Alireza Doostan, Corey R. Randall, Eric J. Dufek, Andrew M. Colclasure, Kandler Smith:
PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model. CoRR abs/2312.17329 (2023) - [i17]Malik Hassanaly, Peter J. Weddle, Ryan N. King, Subhayan De, Alireza Doostan, Corey R. Randall, Eric J. Dufek, Andrew M. Colclasure, Kandler Smith:
PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model. CoRR abs/2312.17336 (2023) - 2022
- [j25]Felix Newberry, Corey Wetterer-Nelson, John A. Evans, Alireza Doostan, Kenneth E. Jansen:
Software tools to enable immersive simulation. Eng. Comput. 38(5): 4697-4713 (2022) - [j24]Heather Pacella, Alec M. Dunton, Alireza Doostan, Gianluca Iaccarino:
Task-parallel in situ temporal compression of large-scale computational fluid dynamics data. Int. J. High Perform. Comput. Appl. 36(3): 388-418 (2022) - [j23]Eric L. Peters, Riccardo Balin, Kenneth E. Jansen, Alireza Doostan, John A. Evans:
S-frame discrepancy correction models for data-informed Reynolds stress closure. J. Comput. Phys. 448: 110717 (2022) - [j22]Subhayan De, Alireza Doostan:
Neural network training using ℓ1-regularization and bi-fidelity data. J. Comput. Phys. 458: 111010 (2022) - [i16]Alexandre Cortiella, Kwang-Chun Park, Alireza Doostan:
A Priori Denoising Strategies for Sparse Identification of Nonlinear Dynamical Systems: A Comparative Study. CoRR abs/2201.12683 (2022) - [i15]Jacqueline Wentz, Alireza Doostan:
GenMod: A generative modeling approach for spectral representation of PDEs with random inputs. CoRR abs/2201.12973 (2022) - [i14]Aaron Allred, Lauren J. Abbott, Alireza Doostan, Kurt Maute:
Automated processing of X-ray computed tomography images via panoptic segmentation for modeling woven composite textiles. CoRR abs/2202.01265 (2022) - [i13]Jeffrey M. Hokanson, Gianluca Iaccarino, Alireza Doostan:
Simultaneous Identification and Denoising of Dynamical Systems. CoRR abs/2203.13837 (2022) - [i12]Subhayan De, Malik Hassanaly, Matthew J. Reynolds, Ryan N. King, Alireza Doostan:
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets. CoRR abs/2204.00997 (2022) - [i11]Osman Asif Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan:
Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems. CoRR abs/2209.05662 (2022) - [i10]Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan:
Quadrature Sampling of Parametric Models with Bi-fidelity Boosting. CoRR abs/2209.05705 (2022) - [i9]Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan:
QCNN: Quadrature Convolutional Neural Network with Application to Unstructured Data Compression. CoRR abs/2211.05151 (2022) - 2021
- [j21]David Kozak, Stephen Becker, Alireza Doostan, Luis Tenorio:
A stochastic subspace approach to gradient-free optimization in high dimensions. Comput. Optim. Appl. 79(2): 339-368 (2021) - [i8]Heather Pacella, Alec M. Dunton, Alireza Doostan, Gianluca Iaccarino:
Task-parallel in-situ temporal compression of large-scale computational fluid dynamics data. CoRR abs/2103.01380 (2021) - [i7]Felix Newberry, Jerrad Hampton, Kenneth E. Jansen, Alireza Doostan:
Bi-fidelity Reduced Polynomial Chaos Expansion for Uncertainty Quantification. CoRR abs/2104.07462 (2021) - [i6]Alec Michael Dunton, Alireza Doostan:
Deterministic matrix sketches for low-rank compression of high-dimensional simulation data. CoRR abs/2105.01271 (2021) - [i5]Subhayan De, Bhuiyan Shameem Mahmood Ebna Hai, Alireza Doostan, Markus Bause:
Prediction of Ultrasonic Guided Wave Propagation in Solid-fluid and their Interface under Uncertainty using Machine Learning. CoRR abs/2105.02813 (2021) - [i4]Subhayan De, Alireza Doostan:
Neural Network Training Using 𝓁1-Regularization and Bi-fidelity Data. CoRR abs/2105.13011 (2021) - 2020
- [j20]Hillary R. Fairbanks, Lluís Jofre, Gianluca Geraci, Gianluca Iaccarino, Alireza Doostan:
Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence. J. Comput. Phys. 402 (2020) - [j19]Alec M. Dunton, Lluís Jofre, Gianluca Iaccarino, Alireza Doostan:
Pass-efficient methods for compression of high-dimensional turbulent flow data. J. Comput. Phys. 423: 109704 (2020) - [i3]Subhayan De, Jolene Britton, Matthew J. Reynolds, Ryan Skinner, Kenneth E. Jansen, Alireza Doostan:
On transfer learning of neural networks using bi-fidelity data for uncertainty propagation. CoRR abs/2002.04495 (2020) - [i2]Alexandre Cortiella, Kwang-Chun Park, Alireza Doostan:
Sparse Identification of Nonlinear Dynamical Systems via Reweighted 𝓁s1-regularized Least Squares. CoRR abs/2005.13232 (2020)
2010 – 2019
- 2019
- [j18]Per Pettersson, Alireza Doostan, Jan Nordström:
Level set methods for stochastic discontinuity detection in nonlinear problems. J. Comput. Phys. 392: 511-531 (2019) - [i1]Subhayan De, Jerrad Hampton, Kurt Maute, Alireza Doostan:
Topology Optimization under Uncertainty using a Stochastic Gradient-based Approach. CoRR abs/1902.04562 (2019) - 2018
- [j17]Jerrad Hampton, Hillary R. Fairbanks, Akil Narayan, Alireza Doostan:
Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction. J. Comput. Phys. 368: 315-332 (2018) - [j16]Jerrad Hampton, Alireza Doostan:
Basis adaptive sample efficient polynomial chaos (BASE-PC). J. Comput. Phys. 371: 20-49 (2018) - 2017
- [j15]Hillary R. Fairbanks, Alireza Doostan, Christian Ketelsen, Gianluca Iaccarino:
A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems. J. Comput. Phys. 341: 121-139 (2017) - [j14]Matthew J. Reynolds, Gregory Beylkin, Alireza Doostan:
Optimization via separated representations and the canonical tensor decomposition. J. Comput. Phys. 348: 220-230 (2017) - [j13]Paul G. Constantine, Alireza Doostan:
Time-dependent global sensitivity analysis with active subspaces for a lithium ion battery model. Stat. Anal. Data Min. 10(5): 243-262 (2017) - 2016
- [j12]Per Pettersson, Jan Nordström, Alireza Doostan:
A well-posed and stable stochastic Galerkin formulation of the incompressible Navier-Stokes equations with random data. J. Comput. Phys. 306: 92-116 (2016) - [j11]Ji Peng, Jerrad Hampton, Alireza Doostan:
On polynomial chaos expansion via gradient-enhanced ℓ1-minimization. J. Comput. Phys. 310: 440-458 (2016) - [j10]Matthew J. Reynolds, Alireza Doostan, Gregory Beylkin:
Randomized Alternating Least Squares for Canonical Tensor Decompositions: Application to A PDE With Random Data. SIAM J. Sci. Comput. 38(5) (2016) - 2015
- [j9]Jerrad Hampton, Alireza Doostan:
Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies. J. Comput. Phys. 280: 363-386 (2015) - 2014
- [j8]Ji Peng, Jerrad Hampton, Alireza Doostan:
A weighted l1-minimization approach for sparse polynomial chaos expansions. J. Comput. Phys. 267: 92-111 (2014) - [j7]Jayanth Jagalur-Mohan, Onkar Sahni, Alireza Doostan, Assad A. Oberai:
Variational Multiscale Analysis: The Fine-Scale Green's Function for Stochastic Partial Differential Equations. SIAM/ASA J. Uncertain. Quantification 2(1): 397-422 (2014) - [j6]Marian Brezina, Alireza Doostan, Tom Manteuffel, Steve F. McCormick, John W. Ruge:
Smoothed aggregation algebraic multigrid for stochastic PDE problems with layered materials. Numer. Linear Algebra Appl. 21(2): 239-255 (2014) - 2011
- [j5]Alireza Doostan, Houman Owhadi:
A non-adapted sparse approximation of PDEs with stochastic inputs. J. Comput. Phys. 230(8): 3015-3034 (2011) - 2010
- [j4]Iman Hajirasouliha, Alireza Doostan:
A simplified model for seismic response prediction of concentrically braced frames. Adv. Eng. Softw. 41(3): 497-505 (2010)
2000 – 2009
- 2009
- [j3]Alireza Doostan, Gianluca Iaccarino:
A least-squares approximation of partial differential equations with high-dimensional random inputs. J. Comput. Phys. 228(12): 4332-4345 (2009) - [j2]Tonkid Chantrasmi, Alireza Doostan, Gianluca Iaccarino:
Padé-Legendre approximants for uncertainty analysis with discontinuous response surfaces. J. Comput. Phys. 228(19): 7159-7180 (2009) - 2006
- [j1]Roger G. Ghanem, Alireza Doostan:
On the construction and analysis of stochastic models: Characterization and propagation of the errors associated with limited data. J. Comput. Phys. 217(1): 63-81 (2006)
Coauthor Index
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