3 papers
cs.CE2026
A Lagrangian Conditional Gaussian Koopman Network for Data Assimilation and Prediction
Zhongrui Wang, Chuanqi Chen, Jin-Long Wu +1
Lagrangian data assimilation aims to recover hidden Eulerian flow fields from sparse, indirect observations of moving tracers. This problem is challenging because tracer trajectori…
physics.flu-dyn2025
A Closed-Form Nonlinear Data Assimilation Algorithm for Multi-Layer Flow Fields
Zhongrui Wang, Nan Chen, Di Qi
State estimation in multi-layer turbulent flow fields with only a single layer of partial observation remains a challenging yet practically important task. Applications include inf…
cs.LG2025
Modeling Partially Observed Nonlinear Dynamical Systems and Efficient Data Assimilation via Discrete-Time Conditional Gaussian Koopman Network
Chuanqi Chen, Zhongrui Wang, Nan Chen +1
A discrete-time conditional Gaussian Koopman network (CGKN) is developed in this work to learn surrogate models that can perform efficient state forecast and data assimilation (DA)…