| DRVN (deep random vortex network): A new physics-informed machine learning method for simulating and inferring incompressible fluid flows R Zhang, P Hu, Q Meng, Y Wang, R Zhu, B Chen, ZM Ma, TY Liu Physics of Fluids 34 (10), 2022 | 7 | 2022 |
| Neural operator with regularity structure for modeling dynamics driven by spdes P Hu, Q Meng, B Chen, S Gong, Y Wang, W Chen, R Zhu, ZM Ma, TY Liu arXiv preprint arXiv:2204.06255, 2022 | 7 | 2022 |
| Deep latent regularity network for modeling stochastic partial differential equations S Gong, P Hu, Q Meng, Y Wang, R Zhu, B Chen, Z Ma, H Ni, TY Liu Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7740-7747, 2023 | 2 | 2023 |
| Better Neural PDE Solvers Through Data-Free Mesh Movers P Hu, Y Wang, ZM Ma International Conference on Learning Representations (ICLR 2024), 2023 | 1 | 2023 |
| A Generative Approach to Control Complex Physical Systems L Wei, P Hu, R Feng, H Feng, Y Du, T Zhang, R Wang, Y Wang, ZM Ma, ... arXiv preprint arXiv:2407.06494, 2024 | | 2024 |
| Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations R Zhang, P Hu, Q Meng, Y Wang, R Zhu, B Chen, ZM Ma, TY Liu arXiv preprint arXiv:2206.09571, 2022 | | 2022 |
| Generative PDE Control L Wei, P Hu, R Feng, Y Du, T Zhang, R Wang, Y Wang, ZM Ma, T Wu ICLR 2024 Workshop on AI4DifferentialEquations In Science, 0 | | |
