| D3M: A deep domain decomposition method for partial differential equations K Li, K Tang, T Wu, Q Liao Ieee Access 8, 5283-5294, 2019 | 133 | 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 | 130* | 2023 |
| Adaptive deep density approximation for Fokker-Planck equations K Tang, X Wan, Q Liao Journal of Computational Physics 457, 111080, 2022 | 47 | 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 | 27 | 2020 |
| 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 | 22 | 2024 |
| Adversarial adaptive sampling: Unify PINN and optimal transport for the approximation of PDEs K Tang, J Zhai, X Wan, C Yang The Twelfth International Conference on Learning Representations (ICLR 2024), 2024 | 14 | 2024 |
| 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 | 12 | 2019 |
| 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 |
| Augmented KRnet for density estimation and approximation X Wan, K Tang arXiv preprint arXiv:2105.12866, 2021 | 5 | 2021 |
| Deep Adaptive Sampling for Surrogate Modeling Without Labeled Data X Wang, K Tang, J Zhai, X Wan, C Yang Journal of Scientific Computing 101, 77, 2024 | 3 | 2024 |
| Tensor Train Random Projection Y Feng, K Tang, L He, P Zhou, Q Liao Computer Modeling in Engineering & Sciences 134 (2), 1195–1218, 2023 | 3 | 2023 |
| Dimension-reduced KRnet maps for high-dimensional inverse problems Y Feng, K Tang, X Wan, Q Liao arXiv preprint arXiv:2303.00573, 2023 | 3 | 2023 |
| 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 |
| Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths Y Wang, K Tang, X Wang, X Wan, W Ren, C Yang arXiv preprint arXiv:2501.15522, 2025 | | 2025 |
| Provable Low-Rank Tensor-Train Approximations in the Inverse of Large-Scale Structured Matrices C Xiao, K Tang, Z Zhu arXiv preprint arXiv:2501.07210, 2025 | | 2025 |
| APTT: An accuracy-preserved tensor-train method for the Boltzmann-BGK equation Z Zhu, C Xiao, K Tang, J Huang, C Yang arXiv preprint arXiv:2405.12524, 2024 | | 2024 |
