An active learning kriging model for hybrid reliability analysis with both random and interval variables X Yang, Y Liu, Y Gao, Y Zhang, Z Gao Structural and Multidisciplinary Optimization 51, 1003-1016, 2015 | 194 | 2015 |
FEA-Net: A physics-guided data-driven model for efficient mechanical response prediction H Yao, Y Gao, Y Liu Computer Methods in Applied Mechanics and Engineering 363, 112892, 2020 | 74 | 2020 |
Unified reliability analysis by active learning Kriging model combining with random‐set based Monte Carlo simulation method X Yang, Y Liu, Y Gao International Journal for Numerical Methods in Engineering 108 (11), 1343-1361, 2016 | 52 | 2016 |
Ultra-efficient reconstruction of 3D microstructure and distribution of properties of random heterogeneous materials containing multiple phases Y Gao, Y Jiao, Y Liu Acta Materialia 204, 116526, 2021 | 30 | 2021 |
Multi-fidelity data aggregation using convolutional neural networks J Chen, Y Gao, Y Liu Computer methods in applied mechanics and engineering 391, 114490, 2022 | 21 | 2022 |
Reliability-based topology optimization with stochastic heterogeneous microstructure properties Y Gao, Y Liu Materials & Design 205, 109713, 2021 | 13 | 2021 |
Bayesian-entropy gaussian process for constrained metamodeling Y Wang, Y Gao, Y Liu, S Ghosh, W Subber, P Pandita, L Wang Reliability Engineering & System Safety 214, 107762, 2021 | 9 | 2021 |
Efficient high-dimensional material reliability analysis with explicit voxel-level stochastic microstructure representation Y Gao, Y Jiao, Y Liu Applied Mathematical Modelling 91, 1117-1140, 2021 | 8 | 2021 |
Physics-based deep learning for probabilistic fracture analysis of composite materials Y Gao, H Yao, H Wei, Y Liu AIAA Scitech 2020 Forum, 1860, 2020 | 8 | 2020 |
Multi-fidelity neural optimization machine for Digital Twins J Chen, C Meng, Y Gao, Y Liu Structural and Multidisciplinary Optimization 65 (12), 340, 2022 | 6 | 2022 |
Ultraefficient reconstruction of effectively hyperuniform disordered biphase materials via non-Gaussian random fields Y Gao, Y Jiao, Y Liu Physical Review E 105 (4), 045305, 2022 | 6 | 2022 |
Adjoint-FORM for efficient reliability analysis of large-scale structural problems Y Gao, Y Liu 2018 AIAA Non-Deterministic Approaches Conference, 0435, 2018 | 6 | 2018 |
Adjoint gradient-enhanced kriging model for time-dependent reliability analysis Y Gao, Y Liu AIAA Scitech 2019 Forum, 0441, 2019 | 3 | 2019 |
Convolutional neural networks for multi-fidelity data aggregation J Chen, Y Gao, Y Liu AIAA SCITECH 2022 Forum, 2144, 2022 | 1 | 2022 |
Active learning-based efficient separation risk assessment in national airspace system Y Gao, Y Liu, P Dutta, O Chen, H Iyer, BJ Yang AIAA Aviation 2019 Forum, 2942, 2019 | 1 | 2019 |
Ultra-efficient and Scalable Uncertainty Quantification and Probabilistic Analysis for Heterogeneous Materials Y Gao Arizona State University, 2021 | | 2021 |
A constrained semi-parametric gaussian process using bayesian-entropy regression Y Wang, Y Gao, Y Liu, S Ghosh, L Wang AIAA Scitech 2021 Forum, 0180, 2021 | | 2021 |
Probabilistic Failure Analysis for ICME Using An Adjoint-based Lattice Particle Method. Y Gao, Y Liu AIAA Scitech 2019 Forum, 0970, 2019 | | 2019 |
Multi-Fidelity Data Aggregation for Information Fusion in Simulation and Experiment J Chen, C Meng, Y Gao, Y Liu AIAA SCITECH 2023 Forum, 0 | | |
Adjoint Gradient-enhanced Kriging Model-based Method for Time-dependent Reliability Analysis Y Gao, Y Liu | | |