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 | 56 | 2018 |
The reduced‐order hybrid Monte Carlo sampling smoother A Attia, R Ştefănescu, A Sandu International Journal for Numerical Methods in Fluids 83 (1), 28-51, 2017 | 33 | 2017 |
A hybrid Monte Carlo sampling filter for non-gaussian data assimilation A Attia, A Sandu AIMS Geosciences 1, 41-78, 2015 | 30* | 2015 |
Cluster Sampling Filters for Non-Gaussian Data Assimilation A Attia, A Moosavi, A Sandu Atmosphere 9, 2018 | 25 | 2018 |
A Hybrid Monte‐Carlo sampling smoother for four‐dimensional data assimilation A Attia, V Rao, A Sandu International Journal for Numerical Methods in Fluids 83 (1), 90-112, 2017 | 25 | 2017 |
A machine learning approach to adaptive covariance localization A Moosavi, A Attia, A Sandu arXiv preprint arXiv:1801.00548, 2018 | 20 | 2018 |
A sampling approach for four dimensional data assimilation A Attia, V Rao, A Sandu International Conference on Dynamic Data-Driven Environmental Systems …, 2014 | 17 | 2014 |
DATeS: a highly extensible data assimilation testing suite v1. 0 A Attia, A Sandu Geoscientific Model Development 12 (2), 629-649, 2019 | 14* | 2019 |
An optimal experimental design framework for adaptive inflation and covariance localization for ensemble filters A Attia, E Constantinescu arXiv preprint arXiv:1806.10655, 2018 | 12 | 2018 |
Stochastic learning approach for binary optimization: Application to Bayesian optimal design of experiments A Attia, S Leyffer, TS Munson SIAM Journal on Scientific Computing 44 (2), B395-B427, 2022 | 11 | 2022 |
Tuning covariance localization using machine learning A Moosavi, A Attia, A Sandu Computational Science–ICCS 2019: 19th International Conference, Faro …, 2019 | 11 | 2019 |
Optimal experimental design for inverse problems in the presence of observation correlations A Attia, E Constantinescu SIAM Journal on Scientific Computing 44 (4), A2808-A2842, 2022 | 9 | 2022 |
PyOED: An extensible suite for data assimilation and model-constrained optimal design of experiments A Chowdhary, SE Ahmed, A Attia ACM Transactions on Mathematical Software, 2023 | 5 | 2023 |
Advanced Sampling Methods for Solving Large-Scale Inverse Problems A Attia Virginia Polytechnic Institute and State University, 2016 | 5 | 2016 |
Robust A-optimal experimental design for Bayesian inverse problems A Attia, S Leyffer, T Munson arXiv preprint arXiv:2305.03855, 2023 | 2 | 2023 |
Centralized calibration of power system dynamic models using variational data assimilation A Attia, DA Maldonado, E Constantinescu, M Anitescu arXiv preprint arXiv:2311.07676, 2023 | | 2023 |
Heuristic Algorithms for Placing Geomagnetically Induced Current Blocking Devices M Ryu, A Attia, A Barnes, R Bent, S Leyffer, A Mate arXiv preprint arXiv:2310.09409, 2023 | | 2023 |
Stochastic Learning Approach to Binary Optimization for Optimal Design of Experiments A Attia, S Leyffer, T Munson arXiv preprint arXiv:2101.05958, 2021 | | 2021 |
Computer Science Technical Report CSTR-1 A Moosavi, A Attia, A Sandu arXiv preprint arXiv:1801.00548, 2018 | | 2018 |
Interactive comment on “DATeS: A Highly-Extensible Data Assimilation Testing Suite” by Ahmed Attia and Adrian Sandu A Attia | | 2018 |