The expected minibatch OT plan converges to the true OT plan with quantifiable bias and convergence rates, yielding a regular velocity field for unique flows from source to discrete target in flow matching.
Y ., Klein, M., and Cu- turi, M
3 Pith papers cite this work. Polarity classification is still indexing.
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Introduces Wasserstein-on-Wasserstein flow matching that realizes metameasure flows via nested Wasserstein geometry and scalable sliced/linear approximations for generative modeling of transport plans.
A geometric latent-subspace model on Riemannian manifolds of categorical distributions enables low-dimensional generative modeling of discrete data via isometries and geometric PCA for flow matching.
citing papers explorer
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Expected Batch Optimal Transport Plans and Consequences for Flow Matching
The expected minibatch OT plan converges to the true OT plan with quantifiable bias and convergence rates, yielding a regular velocity field for unique flows from source to discrete target in flow matching.
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Generalized Wasserstein Flow Matching: Transport Plans, Everywhere, All at Once
Introduces Wasserstein-on-Wasserstein flow matching that realizes metameasure flows via nested Wasserstein geometry and scalable sliced/linear approximations for generative modeling of transport plans.
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Generative Modeling of Discrete Data Using Geometric Latent Subspaces
A geometric latent-subspace model on Riemannian manifolds of categorical distributions enables low-dimensional generative modeling of discrete data via isometries and geometric PCA for flow matching.