Arvind Krishna Saibaba

Efficient hyperparameter estimation in Bayesian inverse problems using sample average approximation

Chung, J., Miller, S. M., Landman, M. S., & Saibaba, A. K. (2025, September 25). Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Vol. 383.

Optimal sensor placement under model uncertainty in the weak-constraint 4D-Var framework

Alexanderian, A., Díaz, H., Rao, V., & Saibaba, A. K. (2025, January 1). Foundations of Data Science.

Parametric Kernel Low-Rank Approximations Using Tensor Train Decomposition

Khan, A., & Saibaba, A. K. (2025, April 9). SIAM Journal on Matrix Analysis and Applications.

Parametric level-sets enhanced to improve reconstruction (PaLEnTIR)

Ozsar, E., Kilmer, M., Sturler, E., Saibaba, A. K., & Miller, E. (2025, January 8). Inverse Problems, Vol. 41.

Randomized Low-Rank Approximations beyond Gaussian Random Matrices

Saibaba, A. K., & Międlar, A. (2025, January 16). SIAM Journal on Mathematics of Data Science, Vol. 7, pp. 136–162.

Randomized Preconditioned Solvers for Strong Constraint 4D-Var Data Assimilation

Subrahmanya, A. N., Rao, V., & Saibaba, A. K. (2025, August 28). Optimization and Engineering.

Stable Rank and Intrinsic Dimension of Real and Complex Matrices

Ipsen, I. C. F., & Saibaba, A. K. (2025, August 28). SIAM Journal on Matrix Analysis and Applications, Vol. 46.

A joint reconstruction and model selection approach for large-scale linear inverse modeling (msHyBR v2)

Landman, M. S., Chung, J., Jiang, J., Miller, S. M., & Saibaba, A. K. (2024, December 12). Geoscientific Model Development, Vol. 17, pp. 8853–8872.

Efficient iterative methods for hyperparameter estimation in large-scale linear inverse problems

Hall-Hooper, K. A., Saibaba, A. K., Chung, J., & Miller, S. M. (2024, December 1). Advances in Computational Mathematics.

A computational framework for edge-preserving regularization in dynamic inverse problems

Pasha, M., Saibaba, A. K., Gazzola, S., Español, M. I., & Sturler, E. (2023, January 1). ETNA - Electronic Transactions on Numerical Analysis, Vol. 58, pp. 486–516.

Efficient Algorithms for Bayesian Inverse Problems with Whittle–Matérn Priors

Antil, H., & Saibaba, A. K. (2023, July 19). SIAM Journal on Scientific Computing, Vol. 46, pp. S176–S198.

Hybrid Projection Methods for Solution Decomposition in Large-Scale Bayesian Inverse Problems

Chung, J., Jiang, J., Miller, S. M., & Saibaba, A. K. (2023, July 18). SIAM Journal on Scientific Computing, Vol. 46, pp. S97–S119.

Monte Carlo Methods for Estimating the Diagonal of a Real Symmetric Matrix

Hallman, E., Ipsen, I. C. F., & Saibaba, A. K. (2023, March 9). SIAM Journal on Matrix Analysis and Applications, Vol. 44, pp. 240–269.

Randomized Algorithms for Rounding in the Tensor-Train Format

Daas, H. A., Ballard, G., Cazeaux, P., Hallman, E., Międlar, A., Pasha, M., … Saibaba, A. K. (2023, January 24). SIAM Journal on Scientific Computing, Vol. 45, pp. A74–A95.

Randomized reduced basis methods for parameterized fractional elliptic PDEs

Antil, H., & Saibaba, A. K. (2023, September 21). Finite Elements in Analysis and Design, Vol. 227.

Tensor-based flow reconstruction from optimally located sensor measurements

Farazmand, M., & Saibaba, A. K. (2023, May 4). Journal of Fluid Mechanics, Vol. 962.

Computationally efficient methods for large-scale atmospheric inverse modeling

Cho, T., Chung, J., Miller, S. M., & Saibaba, A. K. (2022, July 20). Geoscientific Model Development, Vol. 7.

Efficient randomized tensor-based algorithms for function approximation and low-rank kernel interactions

Saibaba, A. K., Minster, R., & Kilmer, M. E. (2022, October 1). Advances in Computational Mathematics, Vol. 10.

Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods

Majumder, S., Guan, Y., Reich, B. J., & Saibaba, A. K. (2022, September 8). Statistics and Computing, Vol. 10.

Structured Matrix Approximations via Tensor Decompositions

Kilmer, M. E., & Saibaba, A. K. (2022, November 16). SIAM Journal on Matrix Analysis and Applications, Vol. 43, pp. 1599–1626.

EFFICIENT ALGORITHMS FOR EIGENSYSTEM REALIZATION USING RANDOMIZED SVD

SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 42(2), 1045–1072.

Monte Carlo estimators for the Schatten p-norm of symmetric positive semidefinite matrices

Dudley, E., Saibaba, A. K., & Alexanderian, A. (2021, January 1). ETNA - Electronic Transactions on Numerical Analysis, Vol. 55, pp. 213–241.

Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis

Saibaba, A. K., Hart, J., & Bloemen Waanders, B. (2021, February 24). Numerical Linear Algebra with Applications.

Randomized approaches to accelerate MCMC algorithms for Bayesian inverse problems

Saibaba, A. K., Prasad, P., Sturler, E., Miller, E., & Kilmer, M. E. (2021, May 10). Journal of Computational Physics, Vol. 9.

Efficient Krylov subspace methods for uncertainty quantification in large Bayesian linear inverse problems

Saibaba, A. K., Chung, J., & Petroske, K. (2020, August 4). Numerical Linear Algebra with Applications.

Geostatistical inverse modeling with very large datasets: an example from the Orbiting Carbon Observatory 2 (OCO-2) satellite

Miller, S. M., Saibaba, A. K., Trudeau, M. E., Mountain, M. E., & Andrews, A. E. (2020, April 2). Geoscientific Model Development, Vol. 13, pp. 1771–1785.

Randomization and Reweighted $\ell_1$-Minimization for A-Optimal Design of Linear Inverse Problems

Herman, E., Alexanderian, A., & Saibaba, A. K. (2020, January 1). SIAM Journal on Scientific Computing, Vol. 42, pp. A1714–A1740.

Randomized Algorithms for Low-Rank Tensor Decompositions in the Tucker Format

Minster, R., Saibaba, A. K., & Kilmer, M. E. (2020, January 1). SIAM Journal on Mathematics of Data Science.

Randomized Discrete Empirical Interpolation Method for Nonlinear Model Reduction

Saibaba, A. K. (2020, January 1). SIAM Journal on Scientific Computing.

Efficient Marginalization-Based MCMC Methods for Hierarchical Bayesian Inverse Problems

Saibaba, A. K., Bardsley, J., Brown, D. A., & Alexanderian, A. (2019, January 1). SIAM/ASA Journal on Uncertainty Quantification, Vol. 7, pp. 1105–1131.

Randomized Subspace Iteration: Analysis of Canonical Angles and Unitarily Invariant Norms

Saibaba, A. K. (2019, January 1). SIAM Journal on Matrix Analysis and Applications, Vol. 40, pp. 23–48.

A randomized tensor singular value decomposition based on the t‐product

Zhang, J., Saibaba, A. K., Kilmer, M. E., & Aeron, S. (2018, May 9). Numerical Linear Algebra with Applications, Vol. 25.

Efficient D-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems

Alexanderian, A., & Saibaba, A. K. (2018, January 1). SIAM Journal on Scientific Computing, Vol. 40, pp. A2956–2985.

Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems

Attia, A., Alexanderian, A., & Saibaba, A. K. (2018, July 9). Inverse Problems, Vol. 34.

Going Off the Grid: Iterative Model Selection for Biclustered Matrix Completion

Chi, E. C., Hu, L., Saibaba, A. K., & Rao, A. U. K. (2018, June 14). Journal of Computational and Graphical Statistics, Vol. 28, pp. 36–47.

Low-Rank Independence Samplers in Hierarchical Bayesian Inverse Problems

Brown, D. A., Saibaba, A., & Vallélian, S. (2018, January 1). SIAM/ASA Journal on Uncertainty Quantification, Vol. 6, pp. 1076–1100.

The Discrete Empirical Interpolation Method: Canonical Structure and Formulation in Weighted Inner Product Spaces

Drmač, Z., & Saibaba, A. K. (2018, January 1). SIAM Journal on Matrix Analysis and Applications, Vol. 39, pp. 1152–1180.

Efficient generalized Golub–Kahan based methods for dynamic inverse problems

Chung, J., Saibaba, A. K., Brown, M., & Westman, E. (2017, December 12). Inverse Problems, Vol. 34.

Generalized Hybrid Iterative Methods for Large-Scale Bayesian Inverse Problems

Chung, J., & Saibaba, A. K. (2017, January 1). SIAM Journal on Scientific Computing, Vol. 39, pp. S24–S46.

Multipreconditioned Gmres for Shifted Systems

Bakhos, T., Kitanidis, P., Ladenheim, S., Saibaba, A. K., & Szyld, D. (2017, January 1). SIAM Journal on Scientific Computing, Vol. 39, pp. S222–S247.

Randomized matrix-free trace and log-determinant estimators

Saibaba, A. K., Alexanderian, A., & Ipsen, I. C. F. (2017, April 6). Numerische Mathematik, Vol. 137, pp. 353–395.

HOID: Higher Order Interpolatory Decomposition for Tensors Based on Tucker Representation

Saibaba, A. K. (2016, January 1). SIAM Journal on Matrix Analysis and Applications, Vol. 37, pp. 1223–1249.

3D parameter reconstruction in hyperspectral diffuse optical tomography

Saibaba, A. K., Krishnamurthy, N., Anderson, P. G., Kainerstorfer, J. M., Sassaroli, A., Miller, E. L., … Kilmer, M. E. (2015, March 5). Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE, Vol. 9319.

A fast algorithm for parabolic PDE-based inverse problems based on Laplace transforms and flexible Krylov solvers

Bakhos, T., Saibaba, A. K., & Kitanidis, P. K. (2015, July 10). Journal of Computational Physics, Vol. 299, pp. 940–954.

Fast Algorithms for Hyperspectral Diffuse Optical Tomography

Saibaba, A. K., Kilmer, M., Miller, E. L., & Fantini, S. (2015, January 1). SIAM Journal on Scientific Computing, Vol. 37, pp. B712–B743.

Fast Kalman filter using hierarchical matrices and a low-rank perturbative approach

Saibaba, A. K., Miller, E. L., Kitanidis, P. K., Saibaba, A. K., Miller, E. L., & Kitanidis, P. K. (2015, January 1). Inverse Problems, Vol. 31.

Fast computation of uncertainty quantification measures in the geostatistical approach to solve inverse problems

Saibaba, A. K., & Kitanidis, P. K. (2015, May 9). Advances in Water Resources, Vol. 82, pp. 124–138.

Randomized algorithms for generalized Hermitian eigenvalue problems with application to computing Karhunen-Loève expansion

Numerical Linear Algebra with Applications, 23(2), 314–339.

A fast Kalman filter for time-lapse electrical resistivity tomography

Saibaba, A. K., Miller, E. L., & Kitandis, P. K. (2014, July 1). International Geoscience and Remote Sensing Symposium (IGARSS), pp. 3152–3155.

A Flexible Krylov Solver for Shifted Systems with Application to Oscillatory Hydraulic Tomography

Saibaba, A. K., Bakhos, T., & Kitanidis, P. K. (2013, January 1). SIAM Journal on Scientific Computing, Vol. 35.

Fast Algorithms for Bayesian Inversion

Ambikasaran, S., Saibaba, A. K., Darve, E. F., & Kitanidis, P. K. (2013, January 1). ˜The œIMA Volumes in Mathematics and Its Applications, pp. 101–142.

Application of Hierarchical Matrices to Linear Inverse Problems in Geostatistics

Saibaba, A. K., Ambikasaran, S., Li, J. Y., Kitanidis, P. K., & Darve, E. F. (2012, September 1). Oil & Gas Science and Technology – Revue d’IFP Energies Nouvelles, Vol. 67, pp. 857–875.

Efficient methods for large‐scale linear inversion using a geostatistical approach

Saibaba, A. K., & Kitanidis, P. K. (2012, April 2). Water Resources Research, Vol. 48.