| Efficient training of physics‐informed neural networks via importance sampling MA Nabian, RJ Gladstone, H Meidani Computer‐Aided Civil and Infrastructure Engineering 36 (8), 962-977, 2021 | 244 | 2021 |
| A deep learning solution approach for high-dimensional random differential equations MA Nabian, H Meidani Probabilistic Engineering Mechanics 57, 14-25, 2019 | 161* | 2019 |
| Deep Learning for Accelerated Seismic Reliability Analysis of Transportation Networks MA Nabian, H Meidani Computer‐Aided Civil and Infrastructure Engineering 33 (6), 443-458, 2018 | 159 | 2018 |
| Inverse uncertainty quantification using the modular Bayesian approach based on Gaussian process, Part 1: Theory X Wu, T Kozlowski, H Meidani, K Shirvan Nuclear Engineering and Design 335, 339-355, 2018 | 129 | 2018 |
| Physics-driven regularization of deep neural networks for enhanced engineering design and analysis MA Nabian, H Meidani Journal of Computing and Information Science in Engineering 20 (1), 011006, 2020 | 110* | 2020 |
| Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data X Wu, T Kozlowski, H Meidani Reliability Engineering & System Safety 169, 422-436, 2018 | 78 | 2018 |
| Gradient based design optimization under uncertainty via stochastic expansion methods V Keshavarzzadeh, H Meidani, DA Tortorelli Computer Methods in Applied Mechanics and Engineering 306, 47-76, 2016 | 72 | 2016 |
| Inverse uncertainty quantification using the modular Bayesian approach based on Gaussian Process, Part 2: Application to TRACE X Wu, T Kozlowski, H Meidani, K Shirvan Nuclear Engineering and Design 335, 417-431, 2018 | 65 | 2018 |
| Predicting Near-Term Train Schedule Performance and Delay Using Bi-Level Random Forests MA Nabian, N Alemazkoor, H Meidani Transportation Research Record 2673 (5), 564-573, 2019 | 52 | 2019 |
| Inverse uncertainty quantification of TRACE physical model parameters using sparse gird stochastic collocation surrogate model X Wu, T Mui, G Hu, H Meidani, T Kozlowski Nuclear Engineering and Design 319, 185-200, 2017 | 40 | 2017 |
| Wavelet approximation of earthquake strong ground motion-goodness of fit for a database in terms of predicting nonlinear structural response MI Todorovska, H Meidani, MD Trifunac Soil Dynamics and Earthquake Engineering 29 (4), 742-751, 2009 | 37 | 2009 |
| Divide and conquer: An incremental sparsity promoting compressive sampling approach for polynomial chaos expansions N Alemazkoor, H Meidani Computer Methods in Applied Mechanics and Engineering 318, 937-956, 2017 | 34 | 2017 |
| PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations W Zhong, H Meidani Computer Methods in Applied Mechanics and Engineering 403, 115664, 2023 | 32 | 2023 |
| Multiscale Markov models with random transitions for energy demand management H Meidani, R Ghanem Energy and Buildings 61, 267-274, 2013 | 31 | 2013 |
| A near-optimal sampling strategy for sparse recovery of polynomial chaos expansions N Alemazkoor, H Meidani Journal of Computational Physics 371, 137-151, 2018 | 29 | 2018 |
| Survival analysis at multiple scales for the modeling of track geometry deterioration N Alemazkoor, CJ Ruppert, H Meidani Proceedings of the Institution of Mechanical Engineers, Part F: Journal of …, 2018 | 27 | 2018 |
| Random Markov decision processes for sustainable infrastructure systems H Meidani, R Ghanem Structure and Infrastructure Engineering 11 (5), 655-667, 2015 | 26 | 2015 |
| IGANI: Iterative Generative Adversarial Networks for Imputation With Application to Traffic Data A Kazemi, H Meidani IEEE Access 9, 112966-112977, 2021 | 25* | 2021 |
| Physics-Informed Neural Networks for System Identification of Structural Systems with a Multiphysics Damping Model T Liu, H Meidani Journal of Engineering Mechanics 149 (10), 04023079, 2023 | 18 | 2023 |
| GNN-based physics solver for time-independent PDEs RJ Gladstone, H Rahmani, V Suryakumar, H Meidani, M D'Elia, A Zareei arXiv preprint arXiv:2303.15681, 2023 | 18 | 2023 |
