A neural network dynamics emulator trained on data yields stability eigenmodes and resolvent modes via automatic differentiation of its Jacobian, enabling equation-free analysis of nonlinear systems.
Nonlinearly induced low- frequency variability in a midlatitude coupled ocean–atmosphere model of intermediate complexity
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A neural operator framework for data-driven discovery of stability and receptivity in physical systems
A neural network dynamics emulator trained on data yields stability eigenmodes and resolvent modes via automatic differentiation of its Jacobian, enabling equation-free analysis of nonlinear systems.