Search Results for author:
Found 3 papers, 0 papers with code
Learning normalizing flows from Entropy-Kantorovich potentials
We approach the problem of learning continuous normalizing flows from a dual perspective motivated by entropy-regularized optimal transport, in which continuous normalizing flows are cast as gradients of scalar potential functions.
Entropy-Regularized $2$-Wasserstein Distance between Gaussian Measures
As the geometries change by varying the regularization magnitude, we study the limiting cases of vanishing and infinite magnitudes, reconfirming well-known results on the limits of the Sinkhorn divergence.
How Well Do WGANs Estimate the Wasserstein Metric?
Generative modelling is often cast as minimizing a similarity measure between a data distribution and a model distribution.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
