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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…
cs.LG2026★ 2 cited
Bayesian Experimental Design for Model Discrepancy Calibration: A Rivalry between Kullback--Leibler Divergence and Wasserstein Distance
Huchen Yang, Xinghao Dong, Jin-Long Wu
Designing experiments that systematically gather data from complex physical systems is central to accelerating scientific discovery. While Bayesian experimental design (BED) provid…