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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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
A graph neural network learns to simulate 1D sea ice floe collisions and trajectories using data assimilation on synthetic data.
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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.
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Graph neural network for colliding particles with an application to sea ice floe modeling
A graph neural network learns to simulate 1D sea ice floe collisions and trajectories using data assimilation on synthetic data.