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A Machine Learning Approach to Adaptive Covariance Localization
In typical weather forecasting applications, the model state space has dimension $10^{9}-10^{12}$, while the ensemble size typically ranges between $30-100$ members.
Efficient Construction of Local Parametric Reduced Order Models Using Machine Learning Techniques
Reduced order models are computationally inexpensive approximations that capture the important dynamical characteristics of large, high-fidelity computer models of physical systems.
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