D3M: A deep domain decomposition method for partial differential equations K Li, K Tang, T Wu, Q Liao Ieee Access 8, 5283-5294, 2019 | 107 | 2019 |
DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations K Tang, X Wan, C Yang Journal of Computational Physics 476, 111868, 2023 | 64* | 2023 |
Adaptive deep density approximation for Fokker-Planck equations K Tang, X Wan, Q Liao Journal of Computational Physics 457, 111080, 2022 | 32 | 2022 |
Deep density estimation via invertible block-triangular mapping K Tang, X Wan, Q Liao Theoretical and Applied Mechanics Letters 10 (3), 143-148, 2020 | 21 | 2020 |
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 |
AONN: An adjoint-oriented neural network method for all-at-once solutions of parametric optimal control problems P Yin, G Xiao, K Tang, C Yang SIAM Journal on Scientific Computing 46 (1), C127-C153, 2024 | 9 | 2024 |
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 |
Adversarial adaptive sampling: Unify PINN and optimal transport for the approximation of PDEs K Tang, J Zhai, X Wan, C Yang arXiv preprint arXiv:2305.18702, 2023 | 4 | 2023 |
Augmented KRnet for density estimation and approximation X Wan, K Tang arXiv preprint arXiv:2105.12866, 2021 | 4 | 2021 |
Dimension-reduced KRnet maps for high-dimensional Bayesian inverse problems Y Feng, K Tang, X Wan, Q Liao arXiv preprint arXiv:2303.00573, 2023 | 2 | 2023 |
Dimension-reduced KRnet maps for high-dimensional inverse problems Y Feng, K Tang, X Wan, Q Liao arXiv preprint arXiv:2303.00573, 2023 | 2 | 2023 |
Tensor Train Random Projection Y Feng, K Tang, L He, P Zhou, Q Liao Computer Modeling in Engineering & Sciences 134 (2), 1195–1218, 2023 | 2 | 2023 |
Deep adaptive sampling for surrogate modeling without labeled data X Wang, K Tang, J Zhai, X Wan, C Yang arXiv preprint arXiv:2402.11283, 2024 | | 2024 |