| Randomized algorithms for low-rank tensor decompositions in the Tucker format R Minster, AK Saibaba, ME Kilmer SIAM journal on mathematics of data science 2 (1), 189-215, 2020 | 83 | 2020 |
| Randomized matrix-free trace and log-determinant estimators AK Saibaba, A Alexanderian, ICF Ipsen Numerische Mathematik 137 (2), 353-395, 2017 | 83 | 2017 |
| A randomized tensor singular value decomposition based on the t‐product J Zhang, AK Saibaba, ME Kilmer, S Aeron Numerical Linear Algebra with Applications 25 (5), e2179, 2018 | 80 | 2018 |
| Randomized algorithms for generalized Hermitian eigenvalue problems with application to computing Karhunen–Loève expansion AK Saibaba, J Lee, PK Kitanidis Numerical Linear Algebra with Applications 23 (2), 314-339, 2016 | 67 | 2016 |
| Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems A Attia, A Alexanderian, AK Saibaba Inverse Problems 34 (9), 095009, 2018 | 65 | 2018 |
| Efficient methods for large-scale linear inversion using a geostatistical approach AK Saibaba, PK Kitanidis Water Resources Research 48 (5), W05522, 2012 | 57 | 2012 |
| Efficient D-optimal design of experiments for infinite-dimensional Bayesian linear inverse problems A Alexanderian, AK Saibaba SIAM Journal on Scientific Computing 40 (5), A2956-A2985, 2018 | 55 | 2018 |
| A flexible Krylov solver for shifted systems with application to oscillatory hydraulic tomography AK Saibaba, T Bakhos, PK Kitanidis SIAM Journal on Scientific Computing 35 (6), A3001-A3023, 2013 | 53 | 2013 |
| The discrete empirical interpolation method: Canonical structure and formulation in weighted inner product spaces Z Drmac, AK Saibaba SIAM Journal on Matrix Analysis and Applications 39 (3), 1152-1180, 2018 | 50 | 2018 |
| Randomized subspace iteration: Analysis of canonical angles and unitarily invariant norms AK Saibaba SIAM Journal on Matrix Analysis and Applications 40 (1), 23-48, 2019 | 49 | 2019 |
| Fast computation of uncertainty quantification measures in the geostatistical approach to solve inverse problems AK Saibaba, PK Kitanidis Advances in water resources 82, 124-138, 2015 | 48 | 2015 |
| Application of hierarchical matrices to linear inverse problems in geostatistics AK Saibaba, S Ambikasaran, JY Li, PK Kitanidis, EF Darve Oil & Gas Science and Technology–Revue d’IFP Energies nouvelles 67 (5), 857-875, 2012 | 45 | 2012 |
| Generalized hybrid iterative methods for large-scale Bayesian inverse problems J Chung, AK Saibaba SIAM Journal on Scientific Computing 39 (5), S24-S46, 2017 | 43 | 2017 |
| Efficient generalized Golub–Kahan based methods for dynamic inverse problems J Chung, AK Saibaba, M Brown, E Westman Inverse Problems 34 (2), 024005, 2018 | 40 | 2018 |
| HOID: higher order interpolatory decomposition for tensors based on Tucker representation AK Saibaba SIAM Journal on Matrix Analysis and Applications 37 (3), 1223-1249, 2016 | 35 | 2016 |
| Geostatistical inverse modeling with very large datasets: an example from the Orbiting Carbon Observatory 2 (OCO-2) satellite SM Miller, AK Saibaba, ME Trudeau, ME Mountain, AE Andrews Geoscientific Model Development 13 (3), 1771-1785, 2020 | 32 | 2020 |
| Multipreconditioned GMRES for shifted systems T Bakhos, PK Kitanidis, S Ladenheim, AK Saibaba, DB Szyld SIAM Journal on Scientific Computing 39 (5), S222-S247, 2017 | 28 | 2017 |
| Randomized algorithms for rounding in the tensor-train format H Al Daas, G Ballard, P Cazeaux, E Hallman, A Międlar, M Pasha, ... SIAM Journal on Scientific Computing 45 (1), A74-A95, 2023 | 27 | 2023 |
| Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis AK Saibaba, J Hart, B van Bloemen Waanders Numerical linear algebra with applications 28 (4), e2364, 2021 | 24 | 2021 |
| Low-rank independence samplers in hierarchical Bayesian inverse problems DA Brown, A Saibaba, S Vallélian SIAM/ASA Journal on Uncertainty Quantification 6 (3), 1076-1100, 2018 | 23* | 2018 |
Peter K. KitanidisProfessor, Stanford UniversityVerified email at stanford.edu
