Alireza Doostan

67 papers Journal 66Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Fast algorithms for least squares problems with Kronecker lower subsets. J. Sci. Comput. Osman Asif Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan
2026	J	`jnl`	Integration of local and global surrogates for failure probability estimation. CoRR Audrey Gaymann, Juan M. Cardenas, Sung Min Jo, Marco Panesi, Alireza Doostan
2026	J	`jnl`	Learning Gradient Flow: Using Equation Discovery to Accelerate Engineering Optimization. CoRR Grant Norman, Conor Rowan, Kurt Maute, Alireza Doostan
2026	J	`jnl`	Robust prediction of parameterized cardiovascular hemodynamics using deep operator networks with time normalization. Comput. Methods Programs Biomed. Junki Hong, Bomi Lee, Adelle Ria Persad, Hyunwoo Song, Changhee Min, Jaehak Jeong, Alireza Doostan, Yong-Hwa Park
2025	J	`jnl`	Bi-fidelity Interpolative Decomposition for Multimodal Data. CoRR Murray Cutforth, Tiffany Fan, Tony Zahtila, Alireza Doostan, Eric Darve
2025	J	`jnl`	Boundary condition enforcement with PINNs: a comparative study and verification on 3D geometries. CoRR Conor Rowan, Kai Hampleman, Kurt Maute, Alireza Doostan
2025	J	`jnl`	In Situ Training of Implicit Neural Compressors for Scientific Simulations via Sketch-Based Regularization. CoRR Cooper Simpson, Stephen Becker, Alireza Doostan
2025	J	`jnl`	On the definition and importance of interpretability in scientific machine learning. CoRR Conor Rowan, Alireza Doostan
2025	J	`jnl`	Physically Interpretable Representation Learning with Gaussian Mixture Variational AutoEncoder (GM-VAE). CoRR Tiffany Fan, Murray Cutforth, Marta D'Elia, Alexandre Cortiella, Alireza Doostan, Eric Darve
2025	—	`conf`	Physically Interpretable Representation and Controlled Generation for Turbulence Data. CAI Tiffany Fan, Murray Cutforth, Marta D'Elia, Alexandre Cortiella, Alireza Doostan, Eric Darve
2025	J	`jnl`	Physically Interpretable Representation and Controlled Generation for Turbulence Data. CoRR Tiffany Fan, Murray Cutforth, Marta D'Elia, Alexandre Cortiella, Alireza Doostan, Eric Darve
2025	J	`jnl`	Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method. CoRR Conor Rowan, Kurt Maute, Alireza Doostan
2025	J	`jnl`	Risk-Aware Aerocapture Guidance Through a Probabilistic Indicator Function. CoRR Grace E. Calkins, Jay W. McMahon, Alireza Doostan, David C. Woffinden
2025	J	`jnl`	Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient. CoRR Conor Rowan, John A. Evans, Kurt Maute, Alireza Doostan
2025	J	`jnl`	Stochastic Subspace Descent Accelerated via Bi-fidelity Line Search. CoRR Nuojin Cheng, Alireza Doostan, Stephen Becker
2025	J	`jnl`	Stochastic Subspace Descent Accelerated via Bi-fidelity Line Search. Trans. Mach. Learn. Res. Nuojin Cheng, Alireza Doostan, Stephen Becker
2024	J	`jnl`	Constrained or Unconstrained? Neural-Network-Based Equation Discovery from Data. CoRR Grant Norman, Jacqueline Wentz, Hemanth Kolla, Kurt Maute, Alireza Doostan
2024	J	`jnl`	Ensemble WSINDy for Data Driven Discovery of Governing Equations from Laser-based Full-field Measurements. CoRR Abigail C. Schmid, Alireza Doostan, Fatemeh Pourahmadian
2024	J	`jnl`	Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction. CoRR Angran Li, Stephen Becker, Alireza Doostan
2024	J	`jnl`	QuadConv: Quadrature-based convolutions with applications to non-uniform PDE data compression. J. Comput. Phys. Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan
2024	J	`jnl`	Subsampling of Parametric Models with Bifidelity Boosting. SIAM/ASA J. Uncertain. Quantification Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan
2023	J	`jnl`	Bi-fidelity Variational Auto-encoder for Uncertainty Quantification. CoRR Nuojin Cheng, Osman Asif Malik, Stephen Becker, Alireza Doostan
2023	J	`jnl`	GenMod: A generative modeling approach for spectral representation of PDEs with random inputs. J. Comput. Phys. Jacqueline Wentz, Alireza Doostan
2023	J	`jnl`	In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD. CoRR Riccardo Balin, Filippo Simini, Cooper Simpson, Andrew Shao, Alessandro Rigazzi, Matthew Ellis, Stephen Becker, Alireza Doostan, John A. Evans, Kenneth E. Jansen
2023	J	`jnl`	PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model. CoRR Malik Hassanaly, Peter J. Weddle, Ryan N. King, Subhayan De, Alireza Doostan, Corey R. Randall, Eric J. Dufek, Andrew M. Colclasure, Kandler Smith
2023	J	`jnl`	PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model. CoRR Malik Hassanaly, Peter J. Weddle, Ryan N. King, Subhayan De, Alireza Doostan, Corey R. Randall, Eric J. Dufek, Andrew M. Colclasure, Kandler Smith
2023	J	`jnl`	Simultaneous Identification and Denoising of Dynamical Systems. SIAM J. Sci. Comput. Jeffrey M. Hokanson, Gianluca Iaccarino, Alireza Doostan
2022	J	`jnl`	A Priori Denoising Strategies for Sparse Identification of Nonlinear Dynamical Systems: A Comparative Study. CoRR Alexandre Cortiella, Kwang-Chun Park, Alireza Doostan
2022	J	`jnl`	Automated processing of X-ray computed tomography images via panoptic segmentation for modeling woven composite textiles. CoRR Aaron Allred, Lauren J. Abbott, Alireza Doostan, Kurt Maute
2022	J	`jnl`	Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets. CoRR Subhayan De, Malik Hassanaly, Matthew J. Reynolds, Ryan N. King, Alireza Doostan
2022	J	`jnl`	Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems. CoRR Osman Asif Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan
2022	J	`jnl`	GenMod: A generative modeling approach for spectral representation of PDEs with random inputs. CoRR Jacqueline Wentz, Alireza Doostan
2022	J	`jnl`	Neural network training using J. Comput. Phys. Subhayan De, Alireza Doostan
2022	J	`jnl`	QCNN: Quadrature Convolutional Neural Network with Application to Unstructured Data Compression. CoRR Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan
2022	J	`jnl`	Quadrature Sampling of Parametric Models with Bi-fidelity Boosting. CoRR Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan
2022	J	`jnl`	Simultaneous Identification and Denoising of Dynamical Systems. CoRR Jeffrey M. Hokanson, Gianluca Iaccarino, Alireza Doostan
2022	J	`jnl`	Software tools to enable immersive simulation. Eng. Comput. Felix Newberry, Corey Wetterer-Nelson, John A. Evans, Alireza Doostan, Kenneth E. Jansen
2022	J	`jnl`	Task-parallel in situ temporal compression of large-scale computational fluid dynamics data. Int. J. High Perform. Comput. Appl. Heather Pacella, Alec M. Dunton, Alireza Doostan, Gianluca Iaccarino
2021	J	`jnl`	A stochastic subspace approach to gradient-free optimization in high dimensions. Comput. Optim. Appl. David Kozak, Stephen Becker, Alireza Doostan, Luis Tenorio
2021	J	`jnl`	Bi-fidelity Reduced Polynomial Chaos Expansion for Uncertainty Quantification. CoRR Felix Newberry, Jerrad Hampton, Kenneth E. Jansen, Alireza Doostan
2021	J	`jnl`	Deterministic matrix sketches for low-rank compression of high-dimensional simulation data. CoRR Alec Michael Dunton, Alireza Doostan
2021	J	`jnl`	Neural Network Training Using 𝓁 CoRR Subhayan De, Alireza Doostan
2021	J	`jnl`	Prediction of Ultrasonic Guided Wave Propagation in Solid-fluid and their Interface under Uncertainty using Machine Learning. CoRR Subhayan De, Bhuiyan Shameem Mahmood Ebna Hai, Alireza Doostan, Markus Bause
2021	J	`jnl`	Task-parallel in-situ temporal compression of large-scale computational fluid dynamics data. CoRR Heather Pacella, Alec M. Dunton, Alireza Doostan, Gianluca Iaccarino
2020	J	`jnl`	Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence. J. Comput. Phys. Hillary R. Fairbanks, Lluís Jofre, Gianluca Geraci, Gianluca Iaccarino, Alireza Doostan
2020	J	`jnl`	On transfer learning of neural networks using bi-fidelity data for uncertainty propagation. CoRR Subhayan De, Jolene Britton, Matthew J. Reynolds, Ryan Skinner, Kenneth E. Jansen, Alireza Doostan
2020	J	`jnl`	Pass-efficient methods for compression of high-dimensional turbulent flow data. J. Comput. Phys. Alec M. Dunton, Lluís Jofre, Gianluca Iaccarino, Alireza Doostan
2020	J	`jnl`	Sparse Identification of Nonlinear Dynamical Systems via Reweighted 𝓁s CoRR Alexandre Cortiella, Kwang-Chun Park, Alireza Doostan
2019	J	`jnl`	Level set methods for stochastic discontinuity detection in nonlinear problems. J. Comput. Phys. Per Pettersson, Alireza Doostan, Jan Nordström
2019	J	`jnl`	Topology Optimization under Uncertainty using a Stochastic Gradient-based Approach. CoRR Subhayan De, Jerrad Hampton, Kurt Maute, Alireza Doostan
2018	J	`jnl`	Basis adaptive sample efficient polynomial chaos (BASE-PC). J. Comput. Phys. Jerrad Hampton, Alireza Doostan
2018	J	`jnl`	Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction. J. Comput. Phys. Jerrad Hampton, Hillary R. Fairbanks, Akil Narayan, Alireza Doostan
2017	J	`jnl`	A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems. J. Comput. Phys. Hillary R. Fairbanks, Alireza Doostan, Christian Ketelsen, Gianluca Iaccarino
2017	J	`jnl`	Optimization via separated representations and the canonical tensor decomposition. J. Comput. Phys. Matthew J. Reynolds, Gregory Beylkin, Alireza Doostan
2017	J	`jnl`	Time-dependent global sensitivity analysis with active subspaces for a lithium ion battery model. Stat. Anal. Data Min. Paul G. Constantine, Alireza Doostan
2016	J	`jnl`	A well-posed and stable stochastic Galerkin formulation of the incompressible Navier-Stokes equations with random data. J. Comput. Phys. Per Pettersson, Jan Nordström, Alireza Doostan
2016	J	`jnl`	On polynomial chaos expansion via gradient-enhanced ℓ J. Comput. Phys. Ji Peng, Jerrad Hampton, Alireza Doostan
2016	J	`jnl`	Randomized Alternating Least Squares for Canonical Tensor Decompositions: Application to A PDE With Random Data. SIAM J. Sci. Comput. Matthew J. Reynolds, Alireza Doostan, Gregory Beylkin
2015	J	`jnl`	Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies. J. Comput. Phys. Jerrad Hampton, Alireza Doostan
2014	J	`jnl`	A weighted l J. Comput. Phys. Ji Peng, Jerrad Hampton, Alireza Doostan
2014	J	`jnl`	Smoothed aggregation algebraic multigrid for stochastic PDE problems with layered materials. Numer. Linear Algebra Appl. Marian Brezina, Alireza Doostan, Tom Manteuffel, Steve F. McCormick, John W. Ruge
2014	J	`jnl`	Variational Multiscale Analysis: The Fine-Scale Green's Function for Stochastic Partial Differential Equations. SIAM/ASA J. Uncertain. Quantification Jayanth Jagalur-Mohan, Onkar Sahni, Alireza Doostan, Assad A. Oberai
2011	J	`jnl`	A non-adapted sparse approximation of PDEs with stochastic inputs. J. Comput. Phys. Alireza Doostan, Houman Owhadi
2010	J	`jnl`	A simplified model for seismic response prediction of concentrically braced frames. Adv. Eng. Softw. Iman Hajirasouliha, Alireza Doostan
2009	J	`jnl`	A least-squares approximation of partial differential equations with high-dimensional random inputs. J. Comput. Phys. Alireza Doostan, Gianluca Iaccarino
2009	J	`jnl`	Padé-Legendre approximants for uncertainty analysis with discontinuous response surfaces. J. Comput. Phys. Tonkid Chantrasmi, Alireza Doostan, Gianluca Iaccarino
2006	J	`jnl`	On the construction and analysis of stochastic models: Characterization and propagation of the errors associated with limited data. J. Comput. Phys. Roger G. Ghanem, Alireza Doostan