Conditional Mean Flows: Few-Step Densities for Simulation-Based Inference

We develop conditional mean flows for fast posterior and likelihood approximation in simulation-based inference, combining few-step sampling with tractable density evaluation. With a single inference step, the method matches the estimation error of standard flow matching while making downstream MCMC sampling about 200 times faster.