Resolvent PNAS
A neural operator framework for data-driven discovery of stability and receptivity in physical systems
Paper title A neural operator framework for data-driven discovery of stability and receptivity in physical systems
Paper arXiv 2604.19465PDF
A neural network trained to emulate a system's dynamics is differentiated to give its eigenmodes and forcing-response modes, without the governing equations.
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