Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching 事件

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching arXiv:2605.00941v4 Announce Type: replace-cross Abstract: Flow matching has become a leading framework for generative modeling, but quantifying the uncertainty of its samples remains an open problem. Existing approaches retrain the model with auxiliary variance heads, maintain costly ensembles, or propagate approximate covariance through many integration steps, trading off training cost, inference cost, or accuracy.