Arvind K. Saibaba
Orcid: 0000-0002-8698-6100
According to our database1,
Arvind K. Saibaba
authored at least 47 papers
between 2013 and 2025.
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Bibliography
2025
SIAM J. Math. Data Sci., 2025
2024
Efficient iterative methods for hyperparameter estimation in large-scale linear inverse problems.
Adv. Comput. Math., December, 2024
Hybrid Projection Methods for Solution Decomposition in Large-Scale Bayesian Inverse Problems.
SIAM J. Sci. Comput., 2024
SIAM J. Sci. Comput., 2024
Efficient hyperparameter estimation in Bayesian inverse problems using sample average approximation.
CoRR, 2024
CoRR, 2024
Bayesian D-Optimal Experimental Designs via Column Subset Selection: The Power of Reweighted Sensors.
CoRR, 2024
CoRR, 2024
2023
SIAM J. Matrix Anal. Appl., March, 2023
SIAM J. Sci. Comput., February, 2023
CoRR, 2023
2022
SIAM J. Matrix Anal. Appl., 2022
Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods.
Stat. Comput., 2022
CoRR, 2022
Efficient randomized tensor-based algorithms for function approximation and low-rank kernel interactions.
Adv. Comput. Math., 2022
2021
SIAM J. Matrix Anal. Appl., 2021
Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis.
Numer. Linear Algebra Appl., 2021
J. Comput. Phys., 2021
Bayesian Level Set Approach for Inverse Problems with Piecewise Constant Reconstructions.
CoRR, 2021
2020
SIAM J. Math. Data Sci., 2020
SIAM J. Sci. Comput., 2020
Randomization and Reweighted ℓ<sub>1</sub>-Minimization for A-Optimal Design of Linear Inverse Problems.
SIAM J. Sci. Comput., 2020
Efficient Krylov subspace methods for uncertainty quantification in large Bayesian linear inverse problems.
Numer. Linear Algebra Appl., 2020
Monte Carlo Estimators for the Schatten p-norm of Symmetric Positive Semidefinite Matrices.
CoRR, 2020
2019
Randomized Subspace Iteration: Analysis of Canonical Angles and Unitarily Invariant Norms.
SIAM J. Matrix Anal. Appl., 2019
Efficient Marginalization-Based MCMC Methods for Hierarchical Bayesian Inverse Problems.
SIAM/ASA J. Uncertain. Quantification, 2019
Randomization and reweighted 𝓁<sup>1</sup>-minimization for A-optimal design of linear inverse problems.
CoRR, 2019
2018
Efficient D-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems.
SIAM J. Sci. Comput., 2018
The Discrete Empirical Interpolation Method: Canonical Structure and Formulation in Weighted Inner Product Spaces.
SIAM J. Matrix Anal. Appl., 2018
Numer. Linear Algebra Appl., 2018
SIAM/ASA J. Uncertain. Quantification, 2018
Goal-Oriented Optimal Design of Experiments for Large-Scale Bayesian Linear Inverse Problems.
CoRR, 2018
2017
SIAM J. Sci. Comput., 2017
Numerische Mathematik, 2017
2016
HOID: Higher Order Interpolatory Decomposition for Tensors Based on Tucker Representation.
SIAM J. Matrix Anal. Appl., 2016
Randomized algorithms for generalized Hermitian eigenvalue problems with application to computing Karhunen-Loève expansion.
Numer. Linear Algebra Appl., 2016
2015
SIAM J. Sci. Comput., 2015
A fast algorithm for parabolic PDE-based inverse problems based on Laplace transforms and flexible Krylov solvers.
J. Comput. Phys., 2015
2014
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014
2013
A Flexible Krylov Solver for Shifted Systems with Application to Oscillatory Hydraulic Tomography.
SIAM J. Sci. Comput., 2013