An introduction to the stochastic modeling of dynamical systems. Methods for the application of stochastic differential equations in various domains including target tracking and mechanical vibrations and their use in parameter estimation, filtering, smoothing, and inverse problems. Introduction to popular methods for machine learning in scientific applications. Main emphasis is put on solution methods rather than analysis and theoretical properties of equations.
This course may not be repeated for credit.

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