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Arvind K. Saibaba
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2020 – today
- 2024
- [j28]Harbir Antil
, Arvind K. Saibaba
Efficient Algorithms for Bayesian Inverse Problems with Whittle-Matérn Priors. SIAM J. Sci. Comput. 46(2): S176-S198 (2024) - [j27]Julianne Chung
Hybrid Projection Methods for Solution Decomposition in Large-Scale Bayesian Inverse Problems. SIAM J. Sci. Comput. 46(2): S97-S119 (2024) - [i27]Amit N. Subrahmanya, Vishwas Rao, Arvind K. Saibaba:
Randomized Preconditioned Solvers for Strong Constraint 4D-Var Data Assimilation. CoRR abs/2401.15758 (2024) - [i26]Srinivas Eswar
Bayesian D-Optimal Experimental Designs via Column Subset Selection: The Power of Reweighted Sensors. CoRR abs/2402.16000 (2024) - [i25]Abraham Khan, Arvind K. Saibaba:
Parametric kernel low-rank approximations using tensor train decomposition. CoRR abs/2406.06344 (2024) - [i24]Ilse C. F. Ipsen, Arvind K. Saibaba:
Stable Rank and Intrinsic Dimension of Real and Complex Matrices. CoRR abs/2407.21594 (2024) - 2023
- [j26]Eric Hallman
Monte Carlo Methods for Estimating the Diagonal of a Real Symmetric Matrix. SIAM J. Matrix Anal. Appl. 44(1): 240-269 (2023) - [j25]Hussam Al Daas
Randomized Algorithms for Rounding in the Tensor-Train Format. SIAM J. Sci. Comput. 45(1): 74- (2023) - [i23]Harbir Antil, Arvind K. Saibaba:
Randomized Reduced Basis Methods for Parameterized Fractional Elliptic PDEs. CoRR abs/2306.16148 (2023) - [i22]Arvind K. Saibaba, Agnieszka Miedlar:
Randomized low-rank approximations beyond Gaussian random matrices. CoRR abs/2308.05814 (2023) - [i21]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 abs/2311.15827 (2023) - 2022
- [j24]Arvind K. Saibaba
Efficient randomized tensor-based algorithms for function approximation and low-rank kernel interactions. Adv. Comput. Math. 48(5): 66 (2022) - [j23]Suman Majumder
Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods. Stat. Comput. 32(5): 74 (2022) - [j22]Misha E. Kilmer
Structured Matrix Approximations via Tensor Decompositions. SIAM J. Matrix Anal. Appl. 43(4): 1599-1626 (2022) - [i20]Eric Hallman, Ilse C. F. Ipsen, Arvind K. Saibaba:
Monte Carlo Methods for Estimating the Diagonal of a Real Symmetric Matrix. CoRR abs/2202.02887 (2022) - [i19]Ege Ozsar, Misha Elena Kilmer, Eric L. Miller, Eric de Sturler
Parametric Level-sets Enhanced To Improve Reconstruction (PaLEnTIR). CoRR abs/2204.09815 (2022) - [i18]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 abs/2205.04203 (2022) - [i17]Harbir Antil, Arvind K. Saibaba:
Efficient algorithms for Bayesian Inverse Problems with Whittle-Matérn Priors. CoRR abs/2205.04417 (2022) - [i16]Julianne Chung, Jiahua Jiang, Scot M. Miller, Arvind K. Saibaba:
Hybrid Projection Methods for Solution Decomposition in Large-scale Bayesian Inverse Problems. CoRR abs/2206.06664 (2022) - [i15]Mohammad Farazmand, Arvind K. Saibaba:
Tensor-based flow reconstruction from optimally located sensor measurements. CoRR abs/2208.09875 (2022) - 2021
- [j21]Arvind K. Saibaba
Randomized approaches to accelerate MCMC algorithms for Bayesian inverse problems. J. Comput. Phys. 440: 110391 (2021) - [j20]Arvind K. Saibaba
Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis. Numer. Linear Algebra Appl. 28(4) (2021) - [j19]Rachel Minster, Arvind K. Saibaba
Efficient Algorithms for Eigensystem Realization Using Randomized SVD. SIAM J. Matrix Anal. Appl. 42(2): 1045-1072 (2021) - [i14]Arvind K. Saibaba:
Approximating monomials using Chebyshev polynomials. CoRR abs/2101.06818 (2021) - [i13]Misha E. Kilmer, Arvind K. Saibaba:
Structured Matrix Approximations via Tensor Decompositions. CoRR abs/2105.01170 (2021) - [i12]Mirjeta Pasha, Arvind K. Saibaba, Silvia Gazzola, Malena I. Español, Eric de Sturler:
Efficient edge-preserving methods for dynamic inverse problems. CoRR abs/2107.05727 (2021) - [i11]Arvind K. Saibaba, Rachel Minster, Misha E. Kilmer:
Efficient randomized tensor-based algorithms for function approximation and low-rank kernel interactions. CoRR abs/2107.13107 (2021) - [i10]Hussam Al Daas, Grey Ballard, Paul Cazeaux, Eric Hallman, Agnieszka Miedlar
Randomized algorithms for rounding in the Tensor-Train format. CoRR abs/2110.04393 (2021) - [i9]William Reese, Arvind K. Saibaba, Jonghyun Lee:
Bayesian Level Set Approach for Inverse Problems with Piecewise Constant Reconstructions. CoRR abs/2111.15620 (2021) - 2020
- [j18]Arvind K. Saibaba
Efficient Krylov subspace methods for uncertainty quantification in large Bayesian linear inverse problems. Numer. Linear Algebra Appl. 27(5) (2020) - [j17]Arvind K. Saibaba
Randomized Discrete Empirical Interpolation Method for Nonlinear Model Reduction. SIAM J. Sci. Comput. 42(3): A1582-A1608 (2020) - [j16]Elizabeth Herman, Alen Alexanderian, Arvind K. Saibaba
Randomization and Reweighted ℓ1-Minimization for A-Optimal Design of Linear Inverse Problems. SIAM J. Sci. Comput. 42(3): A1714-A1740 (2020) - [j15]Rachel Minster, Arvind K. Saibaba
Randomized Algorithms for Low-Rank Tensor Decompositions in the Tucker Format. SIAM J. Math. Data Sci. 2(1): 189-215 (2020) - [i8]Arvind K. Saibaba, Joseph L. Hart, Bart G. van Bloemen Waanders:
Randomized Algorithms for Generalized Singular Value Decomposition with Application to Sensitivity Analysis. CoRR abs/2002.02812 (2020) - [i7]Rachel Minster, Arvind K. Saibaba, Jishnudeep Kar, Aranya Chakrabortty:
Efficient Randomized Algorithms for Subspace System Identification. CoRR abs/2003.11872 (2020) - [i6]Ethan Dudley, Arvind K. Saibaba, Alen Alexanderian:
Monte Carlo Estimators for the Schatten p-norm of Symmetric Positive Semidefinite Matrices. CoRR abs/2005.10174 (2020)
2010 – 2019
- 2019
- [j14]Arvind K. Saibaba
Efficient Marginalization-Based MCMC Methods for Hierarchical Bayesian Inverse Problems. SIAM/ASA J. Uncertain. Quantification 7(3): 1105-1131 (2019) - [j13]Arvind K. Saibaba
Randomized Subspace Iteration: Analysis of Canonical Angles and Unitarily Invariant Norms. SIAM J. Matrix Anal. Appl. 40(1): 23-48 (2019) - [i5]Rachel Minster, Arvind K. Saibaba, Misha E. Kilmer:
Randomized algorithms for low-rank tensor decompositions in the Tucker format. CoRR abs/1905.07311 (2019) - [i4]Elizabeth Herman, Alen Alexanderian, Arvind K. Saibaba:
Randomization and reweighted 𝓁1-minimization for A-optimal design of linear inverse problems. CoRR abs/1906.03791 (2019) - 2018
- [j12]D. Andrew Brown
Low-Rank Independence Samplers in Hierarchical Bayesian Inverse Problems. SIAM/ASA J. Uncertain. Quantification 6(3): 1076-1100 (2018) - [j11]Jiani Zhang
A randomized tensor singular value decomposition based on the t-product. Numer. Linear Algebra Appl. 25(5) (2018) - [j10]Zlatko Drmac
The Discrete Empirical Interpolation Method: Canonical Structure and Formulation in Weighted Inner Product Spaces. SIAM J. Matrix Anal. Appl. 39(3): 1152-1180 (2018) - [j9]Alen Alexanderian, Arvind K. Saibaba
Efficient D-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems. SIAM J. Sci. Comput. 40(5): A2956-A2985 (2018) - [i3]Ahmed Attia, Alen Alexanderian, Arvind K. Saibaba:
Goal-Oriented Optimal Design of Experiments for Large-Scale Bayesian Linear Inverse Problems. CoRR abs/1802.06517 (2018) - 2017
- [j8]Arvind K. Saibaba
Randomized matrix-free trace and log-determinant estimators. Numerische Mathematik 137(2): 353-395 (2017) - [j7]Tania Bakhos, Peter K. Kitanidis
Multipreconditioned Gmres for Shifted Systems. SIAM J. Sci. Comput. 39(5) (2017) - [j6]Julianne Chung
Generalized Hybrid Iterative Methods for Large-Scale Bayesian Inverse Problems. SIAM J. Sci. Comput. 39(5) (2017) - 2016
- [j5]Arvind K. Saibaba
Randomized algorithms for generalized Hermitian eigenvalue problems with application to computing Karhunen-Loève expansion. Numer. Linear Algebra Appl. 23(2): 314-339 (2016) - [j4]Arvind K. Saibaba
HOID: Higher Order Interpolatory Decomposition for Tensors Based on Tucker Representation. SIAM J. Matrix Anal. Appl. 37(3): 1223-1249 (2016) - [i2]Jiani Zhang, Arvind K. Saibaba, Misha Elena Kilmer, Shuchin Aeron:
A Randomized Tensor Singular Value Decomposition based on the t-product. CoRR abs/1609.07086 (2016) - 2015
- [j3]Tania Bakhos, Arvind K. Saibaba
A fast algorithm for parabolic PDE-based inverse problems based on Laplace transforms and flexible Krylov solvers. J. Comput. Phys. 299: 940-954 (2015) - [j2]Arvind K. Saibaba
Fast Algorithms for Hyperspectral Diffuse Optical Tomography. SIAM J. Sci. Comput. 37(5) (2015) - [i1]Arvind K. Saibaba:
HOID: Higher Order Interpolatory Decomposition for tensors based on Tucker representation. CoRR abs/1511.05208 (2015) - 2014
- [c1]Arvind K. Saibaba
A fast Kalman filter for time-lapse electrical resistivity tomography. IGARSS 2014: 3152-3155 - 2013
- [j1]Arvind K. Saibaba
A Flexible Krylov Solver for Shifted Systems with Application to Oscillatory Hydraulic Tomography. SIAM J. Sci. Comput. 35(6) (2013)
Coauthor Index
aka: Misha E. Kilmer
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last updated on 2024-08-22 19:42 CEST by the dblp team
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