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Hadi Meidani
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Cited by
Year
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
1452021
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
1432018
A deep learning solution approach for high-dimensional random differential equations
MA Nabian, H Meidani
Probabilistic Engineering Mechanics 57, 14-25, 2019
134*2019
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
1082018
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
85*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
702018
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
662016
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
552018
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
452019
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
372017
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
372009
Multiscale Markov models with random transitions for energy demand management
H Meidani, R Ghanem
Energy and Buildings 61, 267-274, 2013
302013
A near-optimal sampling strategy for sparse recovery of polynomial chaos expansions
N Alemazkoor, H Meidani
Journal of Computational Physics 371, 137-151, 2018
282018
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
282017
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
242018
Random Markov decision processes for sustainable infrastructure systems
H Meidani, R Ghanem
Structure and Infrastructure Engineering 11 (5), 655-667, 2015
212015
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
202023
IGANI: Iterative Generative Adversarial Networks for Imputation With Application to Traffic Data
A Kazemi, H Meidani
IEEE Access 9, 112966-112977, 2021
17*2021
Spectral power iterations for the random eigenvalue problem
H Meidani, R Ghanem
AIAA journal 52 (5), 912-925, 2014
162014
Development of an overweight vehicle permit fee structure for Illinois
OE Gungor, AMA Petit, J Qiu, J Zhao, H Meidani, H Wang, Y Ouyang, ...
Transport Policy 82, 26-35, 2019
122019
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