Arvind K. Saibaba

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 50

Top Topics

Inverse Problems

Positive Semidefinite Matrices

Top Venues

SIAM J. Sci. Comput.

SIAM J. Matrix Anal. Appl.

Numer. Linear Algebra Appl.

Publications

Srinivas Eswar, Vishwas Rao, Arvind K. Saibaba
Bayesian D-Optimal Experimental Designs via Column Subset Selection: The Power of Reweighted Sensors. CoRR (2024)
Amit N. Subrahmanya, Vishwas Rao, Arvind K. Saibaba
Randomized Preconditioned Solvers for Strong Constraint 4D-Var Data Assimilation. CoRR (2024)
Ilse C. F. Ipsen, Arvind K. Saibaba
Stable Rank and Intrinsic Dimension of Real and Complex Matrices. CoRR (2024)
Harbir Antil, Arvind K. Saibaba
Efficient Algorithms for Bayesian Inverse Problems with Whittle-Matérn Priors. SIAM J. Sci. Comput. 46 (2) (2024)
Abraham Khan, Arvind K. Saibaba
Parametric kernel low-rank approximations using tensor train decomposition. CoRR (2024)
Julianne Chung, Jiahua Jiang, Scot M. Miller, Arvind K. Saibaba
Hybrid Projection Methods for Solution Decomposition in Large-Scale Bayesian Inverse Problems. SIAM J. Sci. Comput. 46 (2) (2024)
Eric Hallman, Ilse C. F. Ipsen, Arvind K. Saibaba
Monte Carlo Methods for Estimating the Diagonal of a Real Symmetric Matrix. SIAM J. Matrix Anal. Appl. 44 (1) (2023)
Harbir Antil, Arvind K. Saibaba
Randomized Reduced Basis Methods for Parameterized Fractional Elliptic PDEs. CoRR (2023)
Hussam Al Daas, Grey Ballard, Paul Cazeaux, Eric Hallman, Agnieszka Miedlar, Mirjeta Pasha, Tim W. Reid, Arvind K. Saibaba
Randomized Algorithms for Rounding in the Tensor-Train Format. SIAM J. Sci. Comput. 45 (1) (2023)
Arvind K. Saibaba, Agnieszka Miedlar
Randomized low-rank approximations beyond Gaussian random matrices. CoRR (2023)
Khalil A Hall-Hooper, Arvind K. Saibaba, Julianne Chung, Scot M. Miller
Efficient iterative methods for hyperparameter estimation in large-scale linear inverse problems. CoRR (2023)
Harbir Antil, Arvind K. Saibaba
Efficient algorithms for Bayesian Inverse Problems with Whittle-Matérn Priors. CoRR (2022)
Arvind K. Saibaba, Rachel Minster, Misha E. Kilmer
Efficient randomized tensor-based algorithms for function approximation and low-rank kernel interactions. Adv. Comput. Math. 48 (5) (2022)
Katherine J. Pearce, Ilse C. F. Ipsen, Mansoor A. Haider, Arvind K. Saibaba, Ralph C. Smith
Robust Parameter Identifiability Analysis via Column Subset Selection. CoRR (2022)
Ege Ozsar, Misha Elena Kilmer, Eric L. Miller, Eric de Sturler, Arvind K. Saibaba
Parametric Level-sets Enhanced To Improve Reconstruction (PaLEnTIR). CoRR (2022)
Misha E. Kilmer, Arvind K. Saibaba
Structured Matrix Approximations via Tensor Decompositions. SIAM J. Matrix Anal. Appl. 43 (4) (2022)
Mohammad Farazmand, Arvind K. Saibaba
Tensor-based flow reconstruction from optimally located sensor measurements. CoRR (2022)
Eric Hallman, Ilse C. F. Ipsen, Arvind K. Saibaba
Monte Carlo Methods for Estimating the Diagonal of a Real Symmetric Matrix. CoRR (2022)
Suman Majumder, Yawen Guan, Brian J. Reich, Arvind K. Saibaba
Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods. Stat. Comput. 32 (5) (2022)
Julianne Chung, Jiahua Jiang, Scot M. Miller, Arvind K. Saibaba
Hybrid Projection Methods for Solution Decomposition in Large-scale Bayesian Inverse Problems. CoRR (2022)
Arvind K. Saibaba, Rachel Minster, Misha E. Kilmer
Efficient randomized tensor-based algorithms for function approximation and low-rank kernel interactions. CoRR (2021)
Mirjeta Pasha, Arvind K. Saibaba, Silvia Gazzola, Malena I. Español, Eric de Sturler
Efficient edge-preserving methods for dynamic inverse problems. CoRR (2021)
Arvind K. Saibaba, Joseph L. Hart, Bart G. van Bloemen Waanders
Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis. Numer. Linear Algebra Appl. 28 (4) (2021)
Arvind K. Saibaba
Approximating monomials using Chebyshev polynomials. CoRR (2021)
Arvind K. Saibaba, Pranjal Prasad, Eric de Sturler, Eric L. Miller, Misha E. Kilmer
Randomized approaches to accelerate MCMC algorithms for Bayesian inverse problems. J. Comput. Phys. 440 (2021)
Hussam Al Daas, Grey Ballard, Paul Cazeaux, Eric Hallman, Agnieszka Miedlar, Mirjeta Pasha, Tim W. Reid, Arvind K. Saibaba
Randomized algorithms for rounding in the Tensor-Train format. CoRR (2021)
William Reese, Arvind K. Saibaba, Jonghyun Lee
Bayesian Level Set Approach for Inverse Problems with Piecewise Constant Reconstructions. CoRR (2021)
Misha E. Kilmer, Arvind K. Saibaba
Structured Matrix Approximations via Tensor Decompositions. CoRR (2021)
Rachel Minster, Arvind K. Saibaba, Jishnudeep Kar, Aranya Chakrabortty
Efficient Algorithms for Eigensystem Realization Using Randomized SVD. SIAM J. Matrix Anal. Appl. 42 (2) (2021)
Arvind K. Saibaba, Joseph L. Hart, Bart G. van Bloemen Waanders
Randomized Algorithms for Generalized Singular Value Decomposition with Application to Sensitivity Analysis. CoRR (2020)
Arvind K. Saibaba, Julianne Chung, Katrina Petroske
Efficient Krylov subspace methods for uncertainty quantification in large Bayesian linear inverse problems. Numer. Linear Algebra Appl. 27 (5) (2020)
Rachel Minster, Arvind K. Saibaba, Misha E. Kilmer
Randomized Algorithms for Low-Rank Tensor Decompositions in the Tucker Format. SIAM J. Math. Data Sci. 2 (1) (2020)
Rachel Minster, Arvind K. Saibaba, Jishnudeep Kar, Aranya Chakrabortty
Efficient Randomized Algorithms for Subspace System Identification. CoRR (2020)
Elizabeth Herman, Alen Alexanderian, Arvind K. Saibaba
-Minimization for A-Optimal Design of Linear Inverse Problems. SIAM J. Sci. Comput. 42 (3) (2020)
Arvind K. Saibaba
Randomized Discrete Empirical Interpolation Method for Nonlinear Model Reduction. SIAM J. Sci. Comput. 42 (3) (2020)
Ethan Dudley, Arvind K. Saibaba, Alen Alexanderian
Monte Carlo Estimators for the Schatten p-norm of Symmetric Positive Semidefinite Matrices. CoRR (2020)
Elizabeth Herman, Alen Alexanderian, Arvind K. Saibaba
-minimization for A-optimal design of linear inverse problems. CoRR (2019)
Arvind K. Saibaba
Randomized Subspace Iteration: Analysis of Canonical Angles and Unitarily Invariant Norms. SIAM J. Matrix Anal. Appl. 40 (1) (2019)
Arvind K. Saibaba, Johnathan M. Bardsley, D. Andrew Brown, Alen Alexanderian
Efficient Marginalization-Based MCMC Methods for Hierarchical Bayesian Inverse Problems. SIAM/ASA J. Uncertain. Quantification 7 (3) (2019)
Rachel Minster, Arvind K. Saibaba, Misha E. Kilmer
Randomized algorithms for low-rank tensor decompositions in the Tucker format. CoRR (2019)
Jiani Zhang, Arvind K. Saibaba, Misha E. Kilmer, Shuchin Aeron
A randomized tensor singular value decomposition based on the t-product. Numer. Linear Algebra Appl. 25 (5) (2018)
Ahmed Attia, Alen Alexanderian, Arvind K. Saibaba
Goal-Oriented Optimal Design of Experiments for Large-Scale Bayesian Linear Inverse Problems. CoRR (2018)
D. Andrew Brown, Arvind K. Saibaba, Sarah Vallélian
Low-Rank Independence Samplers in Hierarchical Bayesian Inverse Problems. SIAM/ASA J. Uncertain. Quantification 6 (3) (2018)
Alen Alexanderian, Arvind K. Saibaba
Efficient D-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems. SIAM J. Sci. Comput. 40 (5) (2018)
Arvind K. Saibaba, Alen Alexanderian, Ilse C. F. Ipsen
Randomized matrix-free trace and log-determinant estimators. Numerische Mathematik 137 (2) (2017)
Julianne Chung, Arvind K. Saibaba
Generalized Hybrid Iterative Methods for Large-Scale Bayesian Inverse Problems. SIAM J. Sci. Comput. 39 (5) (2017)
Tania Bakhos, Peter K. Kitanidis, Scott Ladenheim, Arvind K. Saibaba, Daniel B. Szyld
Multipreconditioned Gmres for Shifted Systems. SIAM J. Sci. Comput. 39 (5) (2017)
Jiani Zhang, Arvind K. Saibaba, Misha Elena Kilmer, Shuchin Aeron
A Randomized Tensor Singular Value Decomposition based on the t-product. CoRR (2016)
Arvind K. Saibaba
HOID: Higher Order Interpolatory Decomposition for Tensors Based on Tucker Representation. SIAM J. Matrix Anal. Appl. 37 (3) (2016)
Arvind K. Saibaba, Jonghyun Lee, Peter K. Kitanidis
Randomized algorithms for generalized Hermitian eigenvalue problems with application to computing Karhunen-Loève expansion. Numer. Linear Algebra Appl. 23 (2) (2016)
Arvind K. Saibaba, Misha Elena Kilmer, Eric L. Miller, Sergio Fantini
Fast Algorithms for Hyperspectral Diffuse Optical Tomography. SIAM J. Sci. Comput. 37 (5) (2015)
Tania Bakhos, Arvind K. Saibaba, Peter K. Kitanidis
A fast algorithm for parabolic PDE-based inverse problems based on Laplace transforms and flexible Krylov solvers. J. Comput. Phys. 299 (2015)
Arvind K. Saibaba
HOID: Higher Order Interpolatory Decomposition for tensors based on Tucker representation. CoRR (2015)
Arvind K. Saibaba, Eric L. Miller, Peter K. Kitanidis
A fast Kalman filter for time-lapse electrical resistivity tomography. IGARSS (2014)
Arvind K. Saibaba, Tania Bakhos, Peter K. Kitanidis
A Flexible Krylov Solver for Shifted Systems with Application to Oscillatory Hydraulic Tomography. SIAM J. Sci. Comput. 35 (6) (2013)