Twisted Schrödinger Bridge Matching
Over the past few years, diffusion-based Schrödinger bridge models have been proposed to approximate optimal transport dynamics between two prescribed boundary distributions, with successful applications to generative modeling. More precisely, these methods aim to estimate a path measure whose initial and terminal marginals match the two boundary distributions, while minimizing the Kullback-Leibler divergence with respect to a reference Markov process. In this work, we consider the generalized Schrödinger bridge problem, in which the reference process is a twisted Brownian motion, that is, a Feynman-Kac transform of a Brownian motion induced by a time-dependent differentiable potential. B...
| Authors | Maxence Noble, Marie Scheid, Yazid Janati et al. |
|---|---|
| Primary category | stat.ML |
| Published | 18 July 2026 |
| Last updated at source | 18 July 2026 |
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