A novel identity connects reduced-model drift and diffusion to the conditional score of the finite-time transition density, turning calibration into a least-squares problem over stationary lagged pairs that preserves invariant statistics and dynamical correlations.
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A geometric indicator from the normal width of the stochastic separatrix in a random two-state ecosystem model scales linearly with noise intensity and yields an affine relation to the logarithm of mean transition time.
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Conditional Score-Based Modeling of Effective Langevin Dynamics
A novel identity connects reduced-model drift and diffusion to the conditional score of the finite-time transition density, turning calibration into a least-squares problem over stationary lagged pairs that preserves invariant statistics and dynamical correlations.
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Geometric early warning indicator from stochastic separatrix structure in a random two-state ecosystem model
A geometric indicator from the normal width of the stochastic separatrix in a random two-state ecosystem model scales linearly with noise intensity and yields an affine relation to the logarithm of mean transition time.