| Review of multi-fidelity models MG Fernández-Godino Advances in Computational Science and Engineering 1 (4), 351-400, 2023 | 322* | 2023 |
| Issues in Deciding Whether to Use Multifidelity Surrogates M Giselle Fernández-Godino, C Park, NH Kim, RT Haftka AIAA Journal 57 (5), 2039-2054, 2019 | 173 | 2019 |
| StressNet-Deep learning to predict stress with fracture propagation in brittle materials Y Wang, D Oyen, WG Guo, A Mehta, CB Scott, N Panda, ... npj Materials Degradation 5 (1), 1-10, 2021 | 37 | 2021 |
| Linear regression based multi-fidelity surrogate for disturbance amplification in multi-phase explosion MG Fernández-Godino, S Dubreuil, N Bartoli, C Gogu, S Balachandar, ... Structural and Multidisciplinary Optimization 60 (6), 2205-22220, 2019 | 15 | 2019 |
| Deep convolutional autoencoders as generic feature extractors in seismological applications Q Kong, A Chiang, AC Aguiar, MG Fernández-Godino, SC Myers, ... Artificial Intelligence in Geosciences 2, 96-106, 2021 | 14 | 2021 |
| Early time evolution of circumferential perturbation of initial particle volume fraction in explosive cylindrical multiphase dispersion MG Fernández-Godino, F Ouellet, RT Haftka, S Balachandar Journal of Fluids Engineering 141 (9), 091302, 2019 | 11 | 2019 |
| Anomaly Detection Using Groups of Simulations MG Fernández–Godino, A Diggs, C Park, NH Kim, RT Haftka 18th AIAA Non-Deterministic Approaches Conference, 1195, 2016 | 9 | 2016 |
| Accelerating high-strain continuum-scale brittle fracture simulations with machine learning MG Fernández-Godino, N Panda, D O’Malley, K Larkin, A Hunter, ... Computational Materials Science 186, 109959, 2021 | 8* | 2021 |
| Identifying entangled physics relationships through sparse matrix decomposition to inform plasma fusion design MG Fernández-Godino, MJ Grosskopf, JB Nakhleh, BM Wilson, JL Kline, ... IEEE Transactions on Plasma Science, 2021 | 7 | 2021 |
| Exploring sensitivity of icf outputs to design parameters in experiments using machine learning JB Nakhleh, MG Fernández-Godino, MJ Grosskopf, BM Wilson, J Kline, ... IEEE Transactions on Plasma Science 49 (7), 2238-2246, 2021 | 7 | 2021 |
| On the use of symmetries in building surrogate models M Giselle Fernández-Godino, S Balachandar, RT Haftka Journal of Mechanical Design 141 (6), 2019 | 7 | 2019 |
| Review of multi-fidelity models (2016) MG Fernández-Godino, C Park, NH Kim, RT Haftka arXiv preprint arXiv:1609.07196, 14, 2016 | 7 | 2016 |
| A data-driven non-linear assimilation framework with neural networks N Panda, MG Fernández-Godino, HC Godinez, C Dawson Computational Geosciences 25 (1), 233-242, 2021 | 5 | 2021 |
| Noise filtering and uncertainty quantification in surrogate based optimization MG Fernández-Godino, RT Haftka, S Balachandar, C Gogu, N Bartoli, ... 2018 AIAA Non-Deterministic Approaches Conference, 2176, 2018 | 5 | 2018 |
| Review of multi-fidelity models M Giselle Fernández-Godino, C Park, NH Kim, RT Haftka arXiv e-prints, arXiv: 1609.07196, 2016 | 5 | 2016 |
| Validation, Uncertainty Quantification and Uncertainty Reduction for a Shock Tube Simulation C Park, MG Fernández-Godino, NH Kim, RT Haftka 18th AIAA Non-Deterministic Approaches Conference, 1192, 2016 | 5 | 2016 |
| Review of multi-fidelity models. arXiv 2016 MG Fernández-Godino, C Park, NH Kim, RT Haftka arXiv preprint arXiv:1609.07196, 0 | 5 | |
| Predicting wind‑driven spatial deposition through simulated color images using deep autoencoders MG Fernández-Godino, DD Lucas, Q Kong Nature Scientific Reports 13 (1394), 12, 2023 | 3 | 2023 |
| StressNet—Deep Learning to Predict Stress with Fracture Propagation in Brittle Materials. npj Mater Y Wang, D Oyen, WG Guo, A Mehta, CB Scott, N Panda, ... Degrad 5 (1), 1-10, 2021 | 3* | 2021 |
| Quantifying Particle Departure from Axisymmetry in Multiphase Cylindrical Detonation MG Fernández-Godino University of Florida, 2018 | 3 | 2018 |
Raphael HaftkaUniversity of FloridaVerified email at ufl.edu
