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Explore sequential Bayesian approaches for parameter estimation in deterministic dynamical systems through this comprehensive seminar talk delivered at the INI Seminar Room. Learn about cutting-edge methods for estimating time-varying parameters and their practical applications in imaging data analysis. Discover how to tackle challenging inverse problems related to estimating and quantifying uncertainty in unknown system parameters from limited data sets. Gain insights from Dr. Andrea Arnold of Worcester Polytechnic Institute as she demonstrates the capabilities and practical implementations of these approaches across various imaging applications during this Rich and Nonlinear Tomography series presentation.
