| A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems A Alexanderian, N Petra, G Stadler, O Ghattas SIAM Journal on Scientific Computing 38 (1), A243–A272, 2016 | 171 | 2016 |
| A-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems with Regularized -Sparsification A Alexanderian, N Petra, G Stadler, O Ghattas SIAM Journal on Scientific Computing 36 (5), A2122-A2148, 2014 | 166 | 2014 |
| Mean-variance risk-averse optimal control of systems governed by PDEs with random parameter fields using quadratic approximations A Alexanderian, N Petra, G Stadler, O Ghattas SIAM/ASA Journal on Uncertainty Quantification 5 (1), 1166-1192, 2017 | 101 | 2017 |
| On Bayesian A-and D-optimal experimental designs in infinite dimensions A Alexanderian, PJ Gloor, O Ghattas http://projecteuclid.org/euclid.ba/1440594948, 2016 | 97 | 2016 |
| Randomized Matrix-free Trace and Log-Determinant Estimators AK Saibaba, A Alexanderian, ICF Ipsen Numerische Mathematik, 2017 | 84 | 2017 |
| Optimal experimental design for infinite-dimensional Bayesian inverse problems governed by PDEs: A review A Alexanderian Inverse Problems, 2021 | 81 | 2021 |
| Global sensitivity analysis in an ocean general circulation model: a sparse spectral projection approach A Alexanderian, J Winokur, I Sraj, A Srinivasan, M Iskandarani, ... Computational Geosciences 16, 757-778, 2012 | 80 | 2012 |
| JHelioviewer: Visualizing large sets of solar images using JPEG 2000 D Muller, B Fleck, G Dimitoglou, BW Caplins, DE Amadigwe, JPG Ortiz, ... Computing in Science & Engineering 11 (5), 38-47, 2009 | 73 | 2009 |
| 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 | 71 | 2018 |
| A brief note on the Karhunen-Loève expansion A Alexanderian arXiv preprint arXiv:1509.07526, 2015 | 66 | 2015 |
| Variance-based sensitivity analysis for time-dependent processes A Alexanderian, PA Gremaud, RC Smith arXiv preprint arXiv:1711.08030, 2020 | 65 | 2020 |
| 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 | 59 | 2018 |
| An age-structured model for the spread of epidemic cholera: analysis and simulation A Alexanderian, MK Gobbert, KR Fister, H Gaff, S Lenhart, E Schaefer Nonlinear Analysis: Real World Applications 12 (6), 3483-3498, 2011 | 58 | 2011 |
| Efficient computation of Sobol'indices for stochastic models JL Hart, A Alexanderian, PA Gremaud SIAM Journal on Scientific Computing., 2017 | 54 | 2017 |
| Multiscale stochastic preconditioners in non-intrusive spectral projection A Alexanderian, OP Le Maître, HN Najm, M Iskandarani, OM Knio Journal of Scientific Computing 50, 306-340, 2012 | 37 | 2012 |
| Bayesian inference of drag parameters using AXBT data from Typhoon Fanapi I Sraj, M Iskandarani, A Srinivasan, WC Thacker, J Winokur, ... Monthly Weather Review 141 (7), 2347-2367, 2013 | 36 | 2013 |
| A-optimal encoding weights for nonlinear inverse problems, with applications to the Helmholtz inverse problem B Crestel, A Alexanderian, G Stadler, O Ghattas Inverse Problems, 2017 | 33 | 2017 |
| Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs K Koval, A Alexanderian, G Stadler Inverse Problems 36 (7), 075007, 2020 | 31 | 2020 |
| Hyper-differential sensitivity analysis for inverse problems constrained by partial differential equations I Sunseri, J Hart, B van Bloemen Waanders, A Alexanderian Inverse Problems 36 (12), 125001, 2020 | 28 | 2020 |
| Optimal design of large-scale Bayesian linear inverse problems under reducible model uncertainty: Good to know what you don't know A Alexanderian, N Petra, G Stadler, I Sunseri SIAM/ASA Journal on Uncertainty Quantification 9 (1), 163-184, 2021 | 25 | 2021 |
Georg StadlerCourant Institute, New York UniversityVerified email at cims.nyu.edu
