| Can a Machine-Learning-Enabled Numerical Model Help Extend Effective Forecast Range through Consistently Trained Subgrid-Scale Models? Y Qu, X Shi Artificial Intelligence for the Earth Systems 2 (1), 2023 | 12 | 2023 |
| Chaosbench: A multi-channel, physics-based benchmark for subseasonal-to-seasonal climate prediction J Nathaniel, Y Qu, T Nguyen, S Yu, J Busecke, A Grover, P Gentine Advances in Neural Information Processing Systems 37, 43715--43729, 2024 | 8 | 2024 |
| Deep generative data assimilation in multimodal setting Y Qu, J Nathaniel, S Li, P Gentine Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 8 | 2024 |
| Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming Y Qu, MA Bhouri, P Gentine ICLR 2024 Workshop on AI4DifferentialEquations In Science, 2024 | 4 | 2024 |
| Physically Consistent Global Atmospheric Data Assimilation with Machine Learning in a Latent Space H Fan, B Fei, P Gentine, Y Xiao, K Chen, Y Liu, Y Qu, F Ling, L Bai arXiv preprint arXiv:2502.02884, 2025 | | 2025 |
| Machine‐assisted physical closure for coarse suspended sediments in vegetated turbulent channel flows S Li, Y Qu, T Zheng, P Gentine Geophysical Research Letters 51 (20), e2024GL110475, 2024 | | 2024 |
