Alireza Doostan

According to our database1, Alireza Doostan authored at least 16 papers between 2006 and 2018.

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Bibliography

2018
Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction.
J. Comput. Physics, 2018

Basis adaptive sample efficient polynomial chaos (BASE-PC).
J. Comput. Physics, 2018

2017
Time-dependent global sensitivity analysis with active subspaces for a lithium ion battery model.
Statistical Analysis and Data Mining, 2017

Optimization via separated representations and the canonical tensor decomposition.
J. Comput. Physics, 2017

A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems.
J. Comput. Physics, 2017

2016
Randomized Alternating Least Squares for Canonical Tensor Decompositions: Application to A PDE With Random Data.
SIAM J. Scientific Computing, 2016

A well-posed and stable stochastic Galerkin formulation of the incompressible Navier-Stokes equations with random data.
J. Comput. Physics, 2016

On polynomial chaos expansion via gradient-enhanced ℓ1-minimization.
J. Comput. Physics, 2016

2015
Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies.
J. Comput. Physics, 2015

2014
Smoothed aggregation algebraic multigrid for stochastic PDE problems with layered materials.
Numerical Lin. Alg. with Applic., 2014

A weighted l1-minimization approach for sparse polynomial chaos expansions.
J. Comput. Physics, 2014

2011
A non-adapted sparse approximation of PDEs with stochastic inputs.
J. Comput. Physics, 2011

2010
A simplified model for seismic response prediction of concentrically braced frames.
Advances in Engineering Software, 2010

2009
A least-squares approximation of partial differential equations with high-dimensional random inputs.
J. Comput. Physics, 2009

Padé-Legendre approximants for uncertainty analysis with discontinuous response surfaces.
J. Comput. Physics, 2009

2006
On the construction and analysis of stochastic models: Characterization and propagation of the errors associated with limited data.
J. Comput. Physics, 2006


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