CGKN: A deep learning framework for modeling complex dynamical systems and efficient data assimilation. - Chuanqi Chen; Nan Chen; Yinling Zhang; Jin-Long Wu (J. Comput. Phys., 2025)

Neural dynamical operator: Continuous spatial-temporal model with gradient-based and derivative-free optimization methods. - Chuanqi Chen; Jin-Long Wu (J. Comput. Phys., 2025)

Data-driven stochastic closure modeling via conditional diffusion model and neural operator. - Xinghao Dong; Chuanqi Chen; Jin-Long Wu (J. Comput. Phys., 2025)

Active Learning of Model Discrepancy with Bayesian Experimental Design. - Huchen Yang; Chuanqi Chen; Jin-Long Wu (CoRR, 2025)

Bayesian Experimental Design for Model Discrepancy Calibration: An Auto-Differentiable Ensemble Kalman Inversion Approach. - Huchen Yang; Xinghao Dong; Jin-Long Wu (CoRR, 2025)

Stochastic and Non-local Closure Modeling for Nonlinear Dynamical Systems via Latent Score-based Generative Models. - Xinghao Dong; Huchen Yang; Jin-Long Wu (CoRR, 2025)

Modeling Partially Observed Nonlinear Dynamical Systems and Efficient Data Assimilation via Discrete-Time Conditional Gaussian Koopman Network. - Chuanqi Chen; Zhongrui Wang; Nan Chen; Jin-Long Wu (CoRR, 2025)