Alireza Doostan

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 42

Top Topics

Sensitivity Analysis

Dynamical Systems

Top Venues

J. Comput. Phys.

SIAM/ASA J. Uncertain. Quantification

SIAM J. Sci. Comput.

Publications

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) (2024)
Grant Norman, Jacqueline Wentz, Hemanth Kolla, Kurt Maute, Alireza Doostan
Constrained or Unconstrained? Neural-Network-Based Equation Discovery from Data. CoRR (2024)
Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan
QuadConv: Quadrature-based convolutions with applications to non-uniform PDE data compression. J. Comput. Phys. 498 (2024)
Angran Li, Stephen Becker, Alireza Doostan
Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction. CoRR (2024)
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 (2023)
Jacqueline Wentz, Alireza Doostan
GenMod: A generative modeling approach for spectral representation of PDEs with random inputs. J. Comput. Phys. 472 (2023)
Nuojin Cheng, Osman Asif Malik, Stephen Becker, Alireza Doostan
Bi-fidelity Variational Auto-encoder for Uncertainty Quantification. CoRR (2023)
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 (2023)
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 (2023)
Jeffrey M. Hokanson, Gianluca Iaccarino, Alireza Doostan
Simultaneous Identification and Denoising of Dynamical Systems. SIAM J. Sci. Comput. 45 (4) (2023)
Subhayan De, Malik Hassanaly, Matthew J. Reynolds, Ryan N. King, Alireza Doostan
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets. CoRR (2022)
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 (2022)
Eric L. Peters, Riccardo Balin, Kenneth E. Jansen, Alireza Doostan, John A. Evans
-frame discrepancy correction models for data-informed Reynolds stress closure. J. Comput. Phys. 448 (2022)
Alexandre Cortiella, Kwang-Chun Park, Alireza Doostan
A Priori Denoising Strategies for Sparse Identification of Nonlinear Dynamical Systems: A Comparative Study. CoRR (2022)
Subhayan De, Alireza Doostan
-regularization and bi-fidelity data. J. Comput. Phys. 458 (2022)
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 (2022)
Jacqueline Wentz, Alireza Doostan
GenMod: A generative modeling approach for spectral representation of PDEs with random inputs. CoRR (2022)
Felix Newberry, Corey Wetterer-Nelson, John A. Evans, Alireza Doostan, Kenneth E. Jansen
Software tools to enable immersive simulation. Eng. Comput. 38 (5) (2022)
Jeffrey M. Hokanson, Gianluca Iaccarino, Alireza Doostan
Simultaneous Identification and Denoising of Dynamical Systems. CoRR (2022)
Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan
QCNN: Quadrature Convolutional Neural Network with Application to Unstructured Data Compression. CoRR (2022)
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) (2022)
Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan
Quadrature Sampling of Parametric Models with Bi-fidelity Boosting. CoRR (2022)
David Kozak, Stephen Becker, Alireza Doostan, Luis Tenorio
A stochastic subspace approach to gradient-free optimization in high dimensions. Comput. Optim. Appl. 79 (2) (2021)
Felix Newberry, Jerrad Hampton, Kenneth E. Jansen, Alireza Doostan
Bi-fidelity Reduced Polynomial Chaos Expansion for Uncertainty Quantification. CoRR (2021)
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 (2021)
Heather Pacella, Alec M. Dunton, Alireza Doostan, Gianluca Iaccarino
Task-parallel in-situ temporal compression of large-scale computational fluid dynamics data. CoRR (2021)
Alec Michael Dunton, Alireza Doostan
Deterministic matrix sketches for low-rank compression of high-dimensional simulation data. CoRR (2021)
Subhayan De, Alireza Doostan
-Regularization and Bi-fidelity Data. CoRR (2021)
Alexandre Cortiella, Kwang-Chun Park, Alireza Doostan
-regularized Least Squares. CoRR (2020)
Alec M. Dunton, Lluís Jofre, Gianluca Iaccarino, Alireza Doostan
Pass-efficient methods for compression of high-dimensional turbulent flow data. J. Comput. Phys. 423 (2020)
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 (2020)
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)
Subhayan De, Jerrad Hampton, Kurt Maute, Alireza Doostan
Topology Optimization under Uncertainty using a Stochastic Gradient-based Approach. CoRR (2019)
Per Pettersson, Alireza Doostan, Jan Nordström
Level set methods for stochastic discontinuity detection in nonlinear problems. J. Comput. Phys. 392 (2019)
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 (2018)
Jerrad Hampton, Alireza Doostan
Basis adaptive sample efficient polynomial chaos (BASE-PC). J. Comput. Phys. 371 (2018)
Matthew J. Reynolds, Gregory Beylkin, Alireza Doostan
Optimization via separated representations and the canonical tensor decomposition. J. Comput. Phys. 348 (2017)
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 (2017)
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) (2017)
Ji Peng, Jerrad Hampton, Alireza Doostan
-minimization. J. Comput. Phys. 310 (2016)
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)
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 (2016)
Jerrad Hampton, Alireza Doostan
Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies. J. Comput. Phys. 280 (2015)
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) (2014)
Ji Peng, Jerrad Hampton, Alireza Doostan
-minimization approach for sparse polynomial chaos expansions. J. Comput. Phys. 267 (2014)
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) (2014)
Alireza Doostan, Houman Owhadi
A non-adapted sparse approximation of PDEs with stochastic inputs. J. Comput. Phys. 230 (8) (2011)
Iman Hajirasouliha, Alireza Doostan
A simplified model for seismic response prediction of concentrically braced frames. Adv. Eng. Softw. 41 (3) (2010)
Tonkid Chantrasmi, Alireza Doostan, Gianluca Iaccarino
Padé-Legendre approximants for uncertainty analysis with discontinuous response surfaces. J. Comput. Phys. 228 (19) (2009)
Alireza Doostan, Gianluca Iaccarino
A least-squares approximation of partial differential equations with high-dimensional random inputs. J. Comput. Phys. 228 (12) (2009)
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) (2006)