| Deep learning predicts path-dependent plasticity M Mozaffar, R Bostanabad, W Chen, K Ehmann, J Cao, MA Bessa Proceedings of the National Academy of Sciences 116 (52), 26414-26420, 2019 | 655 | 2019 |
| A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality MA Bessa, R Bostanabad, Z Liu, A Hu, DW Apley, C Brinson, W Chen, ... Computer Methods in Applied Mechanics and Engineering 320, 633-667, 2017 | 635 | 2017 |
| Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques R Bostanabad, Y Zhang, X Li, T Kearney, LC Brinson, DW Apley, WK Liu, ... Progress in Materials Science 95, 1-41, 2018 | 507 | 2018 |
| Stochastic microstructure characterization and reconstruction via supervised learning R Bostanabad, AT Bui, W Xie, DW Apley, W Chen Acta Materialia 103, 89-102, 2016 | 257 | 2016 |
| Uncertainty quantification in multiscale simulation of woven fiber composites R Bostanabad, B Liang, J Gao, WK Liu, J Cao, D Zeng, X Su, H Xu, Y Li, ... Computer Methods in Applied Mechanics and Engineering 338, 506-532, 2018 | 164 | 2018 |
| Deep learning predicts boiling heat transfer Y Suh, R Bostanabad, Y Won Scientific reports 11 (1), 5622, 2021 | 129 | 2021 |
| Reconstruction of 3D microstructures from 2D images via transfer learning R Bostanabad Computer-Aided Design 128, 102906, 2020 | 110 | 2020 |
| Multi-fidelity cost-aware Bayesian optimization ZZ Foumani, M Shishehbor, A Yousefpour, R Bostanabad Computer Methods in Applied Mechanics and Engineering 407, 115937, 2023 | 98 | 2023 |
| Characterization and reconstruction of 3D stochastic microstructures via supervised learning R Bostanabad, W Chen, DW Apley Journal of microscopy 264 (3), 282-297, 2016 | 96 | 2016 |
| Leveraging the nugget parameter for efficient Gaussian process modeling R Bostanabad, T Kearney, S Tao, DW Apley, W Chen International journal for numerical methods in engineering 114 (5), 501-516, 2018 | 93 | 2018 |
| Mosaic flows: A transferable deep learning framework for solving PDEs on unseen domains H Wang, R Planas, A Chandramowlishwaran, R Bostanabad Computer Methods in Applied Mechanics and Engineering 389, 114424, 2022 | 83 | 2022 |
| Globally approximate gaussian processes for big data with application to data-driven metamaterials design R Bostanabad, YC Chan, L Wang, P Zhu, W Chen Journal of Mechanical Design 141 (11), 111402, 2019 | 83 | 2019 |
| A numerical Bayesian-calibrated characterization method for multiscale prepreg preforming simulations with tension-shear coupling W Zhang, R Bostanabad, B Liang, X Su, D Zeng, MA Bessa, Y Wang, ... Composites Science and Technology 170, 15-24, 2019 | 69 | 2019 |
| Latent map Gaussian processes for mixed variable metamodeling N Oune, R Bostanabad Computer Methods in Applied Mechanics and Engineering 387, 114128, 2021 | 55 | 2021 |
| Data fusion with latent map Gaussian processes JT Eweis-Labolle, N Oune, R Bostanabad Journal of Mechanical Design 144 (9), 091703, 2022 | 48 | 2022 |
| Enhanced Gaussian process metamodeling and collaborative optimization for vehicle suspension design optimization S Tao, K Shintani, R Bostanabad, YC Chan, G Yang, H Meingast, W Chen International design engineering technical conferences and computers and …, 2017 | 46 | 2017 |
| Data centric design: A new approach to design of microstructural material systems W Chen, A Iyer, R Bostanabad Engineering 10, 89-98, 2022 | 45 | 2022 |
| GP+: a python library for kernel-based learning via Gaussian Processes A Yousefpour, ZZ Foumani, M Shishehbor, C Mora, R Bostanabad Advances in Engineering Software 195, 103686, 2024 | 34 | 2024 |
| Data-driven calibration of multifidelity multiscale fracture models via latent map gaussian process S Deng, C Mora, D Apelian, R Bostanabad Journal of Mechanical Design 145 (1), 011705, 2023 | 29 | 2023 |
| Characterization of the optical properties of turbid media by supervised learning of scattering patterns I Hassaninia, R Bostanabad, W Chen, H Mohseni Scientific reports 7 (1), 15259, 2017 | 28 | 2017 |