SDE Matching trains latent SDEs by parameterizing posterior marginal distributions directly, so the variational objective is estimated with Monte Carlo samples instead of numerical SDE simulation.
Variational inference for diffusion processes
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SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
SDE Matching trains latent SDEs by parameterizing posterior marginal distributions directly, so the variational objective is estimated with Monte Carlo samples instead of numerical SDE simulation.