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Dynamic System Discovery With Recursive Physics-Informed Neural Networks, Jarrod Mau
Dynamic System Discovery With Recursive Physics-Informed Neural Networks, Jarrod Mau
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
This thesis presents a novel method, recursive Physics informed neural network, to learn the right hand side of differential equations. The neural network takes in data, then trains, and then acts as a proxy for the differential equation which can be used for modeling. We show the theoretical superiority of the recursive approach. We also use computer simulations to demonstrate the proved properties.