| Transformer for Partial Differential Equations’ Operator Learning Z Li, K Meidani, AB Farimani Transaction on Machine Learning Research, 2023 | 61 | 2023 |
| Graph neural network-accelerated Lagrangian fluid simulation Z Li, AB Farimani Computers & Graphics 103, 201-211, 2022 | 60 | 2022 |
| A physics-informed diffusion model for high-fidelity flow field reconstruction D Shu, Z Li, AB Farimani Journal of Computational Physics 478, 111972, 2023 | 50 | 2023 |
| Graph neural networks accelerated molecular dynamics Z Li, K Meidani, P Yadav, A Barati Farimani The Journal of Chemical Physics 156 (14), 2022 | 48 | 2022 |
| Denoise pretraining on nonequilibrium molecules for accurate and transferable neural potentials Y Wang, C Xu, Z Li, A Barati Farimani Journal of Chemical Theory and Computation 19 (15), 5077-5087, 2023 | 13 | 2023 |
| Prototype memory and attention mechanisms for few shot image generation T Li, Z Li, H Rockwell, A Farimani, TS Lee Proceedings of the Eleventh International Conference on Learning …, 2022 | 13 | 2022 |
| Graph neural networks for molecules Y Wang, Z Li, A Barati Farimani Machine Learning in Molecular Sciences, 21-66, 2023 | 11 | 2023 |
| Scalable Transformer for PDE Surrogate Modeling Z Li, D Shu, AB Farimani Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 10 | 2023 |
| Latent Neural PDE Solver: a reduced-order modelling framework for partial differential equations Z Li, S Patil, F Ogoke, D Shu, W Zhen, M Schneier, JR Buchanan Jr, ... arXiv preprint arXiv:2402.17853, 2024 | 4* | 2024 |
| Hyena neural operator for partial differential equations S Patil, Z Li, A Barati Farimani APL Machine Learning 1 (4), 2023 | 2* | 2023 |
| TPU-GAN: Learning temporal coherence from dynamic point cloud sequences Z Li, T Li, AB Farimani International Conference on Learning Representations, 2021 | 2 | 2021 |
