The Kuramoto Neural Operator represents PDE solution operators as learned dynamics of spherical oscillators and achieves competitive accuracy together with an internal error-localization signal.
Continuous versus discontinuous transitions in the d-dimensional generalized kuramoto model: Odd d is different
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The Kuramoto Neural Operator: Learning to Solve PDEs via Coupled Oscillator Dynamics
The Kuramoto Neural Operator represents PDE solution operators as learned dynamics of spherical oscillators and achieves competitive accuracy together with an internal error-localization signal.