| A mesh-free method for interface problems using the deep learning approach Z Wang, Z Zhang Journal of Computational Physics 400, 108963, 2020 | 79 | 2020 |
| Computing effective diffusivity of chaotic and stochastic flows using structure-preserving schemes Z Wang, J Xin, Z Zhang SIAM Journal on Numerical Analysis 56 (4), 2322-2344, 2018 | 18 | 2018 |
| Proper orthogonal decomposition method to nonlinear filtering problems in medium-high dimension Z Wang, X Luo, SST Yau, Z Zhang IEEE Transactions on Automatic Control 65 (4), 1613-1624, 2019 | 17 | 2019 |
| Asymmetric transport computations in Dirac models of topological insulators G Bal, JG Hoskins, Z Wang Journal of Computational Physics 487, 112151, 2023 | 11 | 2023 |
| Sharp error estimates on a stochastic structure-preserving scheme in computing effective diffusivity of 3D chaotic flows Z Wang, J Xin, Z Zhang Multiscale Modeling & Simulation 19 (3), 1167-1189, 2021 | 10* | 2021 |
| DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method Z Wang, J Xin, Z Zhang Journal of Computational Physics 464, 111309, 2022 | 9 | 2022 |
| A convergent interacting particle method and computation of KPP front speeds in chaotic flows J Lyu, Z Wang, J Xin, Z Zhang SIAM Journal on Numerical Analysis 60 (3), 1136-1167, 2022 | 9 | 2022 |
| Convergence analysis of stochastic structure-preserving schemes for computing effective diffusivity in random flows J Lyu, Z Wang, J Xin, Z Zhang SIAM Journal on Numerical Analysis 58 (5), 3040-3067, 2020 | 9 | 2020 |
| Solving nonlinear filtering problems using a tensor train decomposition method S Li, Z Wang, SST Yau, Z Zhang IEEE Transactions on Automatic Control 68 (7), 4405-4412, 2022 | 6* | 2022 |
| A data-driven model reduction method for parabolic inverse source problems and its convergence analysis Z Wang, W Zhang, Z Zhang Journal of Computational Physics 487, 112156, 2023 | 5 | 2023 |
| A variational neural network approach for glacier modelling with nonlinear rheology T Cui, Z Wang, Z Zhang arXiv preprint arXiv:2209.02088, 2022 | 4 | 2022 |
| Computing effective diffusivities in 3D time-dependent chaotic flows with a convergent Lagrangian numerical method Z Wang, J Xin, Z Zhang ESAIM: Mathematical Modelling and Numerical Analysis 56 (5), 1521-1544, 2022 | 4 | 2022 |
| A DeepParticle method for learning and generating aggregation patterns in multi-dimensional Keller–Segel chemotaxis systems Z Wang, J Xin, Z Zhang Physica D: Nonlinear Phenomena 460, 134082, 2024 | 3 | 2024 |
| A convergent interacting particle method for computing KPP front speeds in random flows T Zhang, Z Wang, J Xin, Z Zhang arXiv preprint arXiv:2308.14479, 2023 | 2 | 2023 |
| Understanding the diffusion models by conditional expectations. Y Lu, Z Wang, G Bal arXiv preprint arXiv:2301.07882, 2023 | 1 | 2023 |
| Random block coordinate descent methods for computing optimal transport and convergence analysis Y Xie, Z Wang, Z Zhang arXiv preprint arXiv:2212.07046, 2022 | | 2022 |
| Long time asymptotics of mixed-type Kimura diffusions G Bal, B Chen, Z Wang arXiv preprint arXiv:2210.10037, 2022 | | 2022 |
| A class of robust numerical methods for solving dynamical systems with multiple time scales TY Hou, Z Wang, Z Zhang arXiv preprint arXiv:1909.04289, 2019 | | 2019 |
zhiwen zhangThe University of Hong Kong在 hku.hk 的电子邮件经过验证
