2 papers
cs.LG2026
Gromov-Wasserstein Methods for Multi-View Relational Embedding and Clustering
Rafael Pereira Eufrazio, Eduardo Fernandes Montesuma, Charles Casimiro Cavalcante
Learning low-dimensional representations from multi-view relational data is challenging when underlying geometries differ across views. We propose Bary-GWMDS, a Gromov-Wasserstein-…
stat.ML2026
Structure-Preserving Multi-View Embedding Using Gromov-Wasserstein Optimal Transport
Rafael Pereira Eufrazio, Eduardo Fernandes Montesuma, Charles Casimiro Cavalcante
Multi-view data analysis seeks to integrate multiple representations of the same samples in order to recover a coherent low-dimensional structure. Classical approaches often rely o…