A two-phase sparse-regression method recovers interaction kernels of stochastic many-particle systems by fitting the residual of the mean-field PDE to kernel-density-estimated densities.
Learning hydrodynamic equations for active matter from particle simulations and experiments
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Extracting Interaction Kernels for Many-Particle Systems by a Two-Phase Approach
A two-phase sparse-regression method recovers interaction kernels of stochastic many-particle systems by fitting the residual of the mean-field PDE to kernel-density-estimated densities.