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Applied Mathematics Graduate Student Association Seminar: William Anderson, Fast and Scalable Computation of Reduced-Order Nonlinear Solutions for PDEs, Abhijit Chowdhary, Sensitivity Analysis of the Information Gain in Infinite-Dimensional Bayesian Linear Inverse Problems
Applied Mathematics Graduate Student Association Seminar: William Anderson, Fast and Scalable Computation of Reduced-Order Nonlinear Solutions for PDEs, Abhijit Chowdhary, Sensitivity Analysis of the Information Gain in Infinite-Dimensional Bayesian Linear Inverse Problems
- Presenter: William Anderson - Title:Â Fast and Scalable Computation of Reduced-Order Nonlinear Solutions for PDEs - Abstract: We develop a method for fast and scalable computation of reduced-order nonlinear solutions (RONS). RONS is a framework to build reduced-order models for time-dependent partial differential equations (PDEs), where the reduced-order solution depends nonlinearly on time-varying parameters. With…