Under a small-angle approximation, the stationary phase covariance of a noisy Kuramoto oscillator network equals the inverse of the encoded matrix up to known constants.
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Thermodynamics-Inspired Computing with Oscillatory Neural Networks for Inverse Matrix Computation
Under a small-angle approximation, the stationary phase covariance of a noisy Kuramoto oscillator network equals the inverse of the encoded matrix up to known constants.