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physics.comp-ph2018
Interplay of Sensor Quantity, Placement and System Dimensionality on Energy Sparse Reconstruction of Fluid Flows
Chen Lu, Balaji Jayaraman
Reconstruction of fine-scale information from sparse data is relevant to many practical fluid dynamic applications where the sensing is typically sparse. Fluid flows in an ideal se…
physics.comp-ph2018
Assessment of End-to-End and Sequential Data-driven Learning of Fluid Flows
Shivakanth Chary Puligilla, Balaji Jayaraman
In this work we explore the advantages of end-to-end learning of multilayer maps offered by feed forward neural-networks (FFNN) for learning and predicting dynamics from transient…