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math.NA2024
Bayesian inference for geophysical fluid dynamics using generative models
Alexander Lobbe, Dan Crisan, Oana Lang
Data assimilation plays a crucial role in numerical modeling, enabling the integration of real-world observations into mathematical models to enhance the accuracy and predictive ca…
math.NA2024
Data assimilation for the stochastic Camassa-Holm equation using particle filtering: a numerical investigation
Colin John Cotter, Dan Crisan, Maneesh Kumar Singh
In this study, we explore data assimilation for the Stochastic Camassa-Holm equation through the application of the particle filtering framework. Specifically, our approach integra…