Basics

This section will cover the basic ideas behind this package. We introduce the Fused Unbalanced Gromov Wasserstein loss and its dense solvers. Then we show how a large, low-rank geometry can be approximated with by computing an embedding, resulting in much less memory usage. Finally, we show how these embeddings can be used in combination with sparse solvers for the FUGW loss.

Transport distributions using dense solvers

Transport distributions using dense solvers

Generate embeddings from mesh

Generate embeddings from mesh

Transport distributions using sparse solvers

Transport distributions using sparse solvers