Augmented Generalized Meanflows for Few Step Generation and Evaluation
A framework for learning augmented Riemannian flow maps that enables both fast sampling and tractable likelihood evaluation on curved manifolds and provides a scalable, geometry-consistent approach for generative modeling and likelihood evaluation in these regimes.
Justin Lin December
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