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Ensemble generative filtering for sequential data assimilation in dynamical systems
Sequential data assimilation (DA) faces a fundamental trade-off: particle filters capture non-Gaussian cycling priors but require prohibitively large ensembles, whereas the ensemble Kalman filter (EnKF) is computationally efficient but constrained by its Gaussian assumption. As machine learning enab
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