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.
Siegert , author R
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Derives and tests ULI, a method to infer underdamped Langevin dynamics from realistic experimental trajectories with discrete sampling and measurement errors.
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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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Inferring the dynamics of underdamped stochastic systems
Derives and tests ULI, a method to infer underdamped Langevin dynamics from realistic experimental trajectories with discrete sampling and measurement errors.