14 citations · 47 across the 7 of their papers we have counts for
7 papers
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…
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)…
Active Learning of Model Discrepancy with Bayesian Experimental Design
Huchen Yang, Chuanqi Chen, Jin-Long Wu
Digital twins have been actively explored in many engineering applications, such as manufacturing and autonomous systems. However, model discrepancy is ubiquitous in most digital t…
CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data Assimilation
Chuanqi Chen, Nan Chen, Yinling Zhang +1
Deep learning is widely used to predict complex dynamical systems in many scientific and engineering areas. However, the black-box nature of these deep learning models presents sig…
Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator
Xinghao Dong, Chuanqi Chen, Jin-Long Wu
Closure models are widely used in simulating complex multiscale dynamical systems such as turbulence and the earth system, for which direct numerical simulation that resolves all s…
CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation
Chuanqi Chen, Nan Chen, Jin-Long Wu
A new knowledge-based and machine learning hybrid modeling approach, called conditional Gaussian neural stochastic differential equation (CGNSDE), is developed to facilitate modeli…
Neural Dynamical Operator: Continuous Spatial-Temporal Model with Gradient-Based and Derivative-Free Optimization Methods
Chuanqi Chen, Jin-Long Wu
Data-driven modeling techniques have been explored in the spatial-temporal modeling of complex dynamical systems for many engineering applications. However, a systematic approach i…