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cs.LG2024
Adjoint Sensitivities of Chaotic Flows without Adjoint Solvers: A Data-Driven Approach
Defne E. Ozan, Luca Magri
In one calculation, adjoint sensitivity analysis provides the gradient of a quantity of interest with respect to all system's parameters. Conventionally, adjoint solvers need to be…
physics.flu-dyn2024
Data-driven computation of adjoint sensitivities without adjoint solvers: An application to thermoacoustics
Defne E. Ozan, Luca Magri
Adjoint methods have been the pillar of gradient-based optimization for decades. They enable the accurate computation of a gradient (sensitivity) of a quantity of interest with res…