Long HC Pham

Decomposing Out-of-Distribution Error in Conditional Flow Matching via Wasserstein Geometry

Conditional flow matching has emerged as a powerful generative modeling framework that learns a vector field to transport an initial distribution toward a target data distribution. However, theoretical understanding of its out-of-distribution (OOD) performance under unseen conditions remains limited…