Research / Publications

Publications

• Structural Blindness in Latent Data Assimilation: Representation Geometry Misleads Sensor Design
  Yongquan Qu, Pierre Gentine (2026)
  Advances in Neural Information Processing Systems (NeurIPS), 2026. Accepted.

• Data-driven subgrid-scale turbulence parameterization: methods for improving model efficiency
  Xingyu Zhu, Yongquan Qu, Naigeng Wu, Hualong Zhang, Xiaoming Shi (2026)
  Machine Learning: Earth 2 (2), 025002. paper

• Video Diffusion for Satellite-based High-Dynamical-Fidelity Precipitation (HiDFiP) Field Generation
  Runze Li, Yan Xia, Yongquan Qu, Dongwei Fu, Clement Guilloteau, Judy Hoffman, Stephan Mandt, Pierre Gentine, Efi Foufoula-Georgiou (2026)
  Preprint. arXiv

• Physically consistent global atmospheric data assimilation with machine learning in latent space
  Hang Fan, Ben Fei, Pierre Gentine, Yi Xiao, Kun Chen, Yubao Liu, Yongquan Qu, Fenghua Ling, Lei Bai (2026)
  Science Advances 12, eaea4248. paper arXiv

• Strictly Constrained Generative Modeling via Split Augmented Langevin Sampling
  Matthieu Blanke, Yongquan Qu, Sara Shamekh, Pierre Gentine (2026)
  International Conference on Learning Representations (ICLR), 2026 paper

• LEX v1.6.0: a new large-eddy simulation model in JAX with GPU acceleration and automatic differentiation
  Xingyu Zhu, Yongquan Qu, Xiaoming Shi (2026)
  Geoscientific Model Development 19, 1103–1120. paper

• Incorporating Multivariate Consistency in ML-Based Weather Forecasting with Latent-space Constraints
  Hang Fan, Yi Xiao, Yongquan Qu, Fenghua Ling, Ben Fei, Lei Bai, Pierre Gentine (2025)
  Preprint arXiv

• PnP-DA: Towards Principled Plug-and-Play Integration of Variational Data Assimilation and Generative Models
  Yongquan Qu, Matthieu Blanke, Sara Shamekh, Pierre Gentine (2025)
  Preprint arXiv

• Machine-Assisted Physical Closure for Coarse Suspended Sediments in Vegetated Turbulent Channel Flows
  Shuolin Li, Yongquan Qu, Tian Zheng, Pierre Gentine (2024)
  Geophysical Research Letters 51 (20), e2024GL110475, paper

• Deep Generative Data Assimilation in Multimodal Setting
  Yongquan Qu*, Juan Nathaniel*, Shuolin Li, Pierre Gentine (2024)
  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 449-459. CVPR EarthVision 2024 Workshop Best Student Paper Award. *Equal contribution. paper code

• Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming
  Yongquan Qu, Mohamed Aziz Bhouri, Pierre Gentine (2024)
  ICLR 2024 Workshop on AI4DifferentialEquations in Science paper

• ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction
  Juan Nathaniel, Yongquan Qu, Tung Nguyen, Sungduk Yu, Julius Busecke, Aditya Grover, Pierre Gentine (2024)
  Advances in Neural Information Processing Systems 37, 43715–43729. homepage arXiv

• Can a Machine-Learning-Enabled Numerical Model Help Extend Effective Forecast Range through Consistently Trained Subgrid-Scale Models?
  Yongquan Qu, Xiaoming Shi (2023)
  Artificial Intelligence for the Earth Systems, 2 (1), e220050. paper code