Two new algorithm families (controlled transport on path space and Wasserstein/JKO density evolution) for sampling posterior path measures without trajectory data, with theoretical consistency equations and toy experiments.
Sampling the posterior: An approach to non-Gaussian data assimilation.Physica D: Nonlinear Phenomena, 230(1-2):50–64, 2007
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Machine-Learned Sampling of Conditioned Path Measures
Two new algorithm families (controlled transport on path space and Wasserstein/JKO density evolution) for sampling posterior path measures without trajectory data, with theoretical consistency equations and toy experiments.