| PROSE: Predicting multiple operators and symbolic expressions using multimodal transformers Y Liu, Z Zhang, H Schaeffer Neural Networks, 106707, 2024 | 9* | 2024 |
| Random feature models for learning interacting dynamical systems Y Liu, SG McCalla, H Schaeffer Proceedings of the Royal Society A 479 (2275), 20220835, 2023 | 7 | 2023 |
| Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and Extrapolation J Sun, Y Liu, Z Zhang, H Schaeffer arXiv preprint arXiv:2404.12355, 2024 | 5 | 2024 |
| PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid Dynamics Y Liu, J Sun, X He, G Pinney, Z Zhang, H Schaeffer arXiv preprint arXiv:2409.09811, 2024 | 1 | 2024 |
| Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey H Wang, Y Cao, Z Huang, Y Liu, P Hu, X Luo, Z Song, W Zhao, J Liu, ... arXiv preprint arXiv:2408.12171, 2024 | | 2024 |
| SURFACTANT DYNAMICS FROM THE ARNOLD PERSPECTIVE J JENKINS, C LEE, Y LIU, E LU, D REED | | 2021 |
