A derivative-free ensemble Kalman-Bucy smoother is developed for continuous-time data assimilation that supports Bayesian causal inference and iterative model structure identification with small ensemble sizes under partial observations.
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DATO and QMDA represent substantially different assimilation paradigms with distinct advantages and limitations in interpretability, robustness, and scalability.
This is an introductory review of the linear algebraic subproblems and contemporary solvers in variational data assimilation for geophysical applications.
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A Continuous-Time Ensemble Kalman-Bucy Smoother for Causal Inference and Model Discovery
A derivative-free ensemble Kalman-Bucy smoother is developed for continuous-time data assimilation that supports Bayesian causal inference and iterative model structure identification with small ensemble sizes under partial observations.
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From Classical to Quantum-Mechanical Data Assimilation: A Comparison between DATO and QMDA
DATO and QMDA represent substantially different assimilation paradigms with distinct advantages and limitations in interpretability, robustness, and scalability.
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An Introduction to Solving the Least-Squares Problem in Variational Data Assimilation
This is an introductory review of the linear algebraic subproblems and contemporary solvers in variational data assimilation for geophysical applications.