Two-parameter flows learn base-to-marginal transports via conditional flow matching then extract unique physics-time velocities by regression on synthetic trajectories, inheriting regularity and scaling to high dimensions while permitting non-gradient dynamics.
URL http://link.springer.com/10.1007/ s10208-019-09425-z
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Two-Parameter Flows for Learning Population Dynamics of Physical Systems
Two-parameter flows learn base-to-marginal transports via conditional flow matching then extract unique physics-time velocities by regression on synthetic trajectories, inheriting regularity and scaling to high dimensions while permitting non-gradient dynamics.