| D3M: A deep domain decomposition method for partial differential equations K Li, K Tang, T Wu, Q Liao Ieee Access 8, 5283-5294, 2019 | 109 | 2019 |
| Reduced basis collocation methods for partial differential equations with random coefficients HC Elman, Q Liao SIAM/ASA Journal on Uncertainty Quantification 1 (1), 192-217, 2013 | 79 | 2013 |
| Time-domain transmission line fault location method with full consideration of distributed parameters and line asymmetry D Lu, Y Liu, Q Liao, B Wang, W Huang, X Xi IEEE Transactions on Power Delivery 35 (6), 2651-2662, 2020 | 42 | 2020 |
| Adaptive deep density approximation for Fokker-Planck equations K Tang, X Wan, Q Liao Journal of Computational Physics 457, 111080, 2022 | 37 | 2022 |
| Multi-layer model enabled fault location for underground cables in MMC-HVDC grids considering distributed and frequency dependent line parameters D Lu, Y Liu, J Xie, B Wang, Q Liao IEEE Transactions on Power Delivery 37 (4), 3082-3096, 2021 | 29 | 2021 |
| An adaptive reduced basis ANOVA method for high-dimensional Bayesian inverse problems Q Liao, J Li Journal of Computational Physics 396, 364-380, 2019 | 28 | 2019 |
| A domain decomposition approach for uncertainty analysis Q Liao, K Willcox SIAM Journal on Scientific Computing 37 (1), A103-A133, 2015 | 28 | 2015 |
| Deep density estimation via invertible block-triangular mapping K Tang, X Wan, Q Liao Theoretical and Applied Mechanics Letters 10 (3), 143-148, 2020 | 23 | 2020 |
| Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs Q Liao, G Lin Journal of Computational Physics 317, 148-164, 2016 | 19 | 2016 |
| A deep domain decomposition method based on Fourier features S Li, Y Xia, Y Liu, Q Liao Journal of Computational and Applied Mathematics 423, 114963, 2023 | 18 | 2023 |
| Convergence analysis of Galerkin finite element approximations to shape gradients in eigenvalue optimization S Zhu, X Hu, Q Liao BIT Numerical Mathematics 60, 853-878, 2020 | 13 | 2020 |
| Robust stabilized Stokes approximation methods for highly stretched grids Q Liao, D Silvester IMA Journal of Numerical Analysis 33 (2), 413-431, 2013 | 13 | 2013 |
| A simple yet effective a posteriori estimator for classical mixed approximation of Stokes equations Q Liao, D Silvester Applied Numerical Mathematics 62 (9), 1242-1256, 2012 | 13 | 2012 |
| A hierarchical neural hybrid method for failure probability estimation K Li, K Tang, J Li, T Wu, Q Liao IEEE Access 7, 112087-112096, 2019 | 10 | 2019 |
| ANOVA Gaussian process modeling for high-dimensional stochastic computational models C Chen, Q Liao Journal of Computational Physics 416, 109519, 2020 | 9 | 2020 |
| Gaussian process based expected information gain computation for bayesian optimal design Z Xu, Q Liao Entropy 22 (2), 258, 2020 | 9 | 2020 |
| Rank adaptive tensor recovery based model reduction for partial differential equations with high-dimensional random inputs K Tang, Q Liao Journal of Computational Physics 409, 109326, 2020 | 8 | 2020 |
| Error estimation and stabilization for low order finite elements Q Liao Manchester Institute for Mathematical Sciences, The University of Manchester, 2010 | 7 | 2010 |
| A domain-decomposed VAE method for Bayesian inverse problems Z Xu, Y Xia, Q Liao International Journal for Uncertainty Quantification 14 (3), 2024 | 5 | 2024 |
| Efficient spectral stochastic finite element methods for Helmholtz equations with random inputs G Wang, Q Liao GLOBAL SCIENCE PRESS 9 (3), 2019 | 5 | 2019 |
Kejun Tang (唐科军)PKU-Changsha Institute for Computing and Digital Economy在 shanghaitech.edu.cn 的电子邮件经过验证
