89 citations · 240 across the 20 of their papers we have counts for
3 papers · 1 filter
Sliced Wasserstein Distance for Learning Gaussian Mixture Models
Soheil Kolouri, Gustavo K. Rohde, Heiko Hoffmann
Gaussian mixture models (GMM) are powerful parametric tools with many applications in machine learning and computer vision. Expectation maximization (EM) is the most popular algori…
Discovery and visualization of structural biomarkers from MRI using transport-based morphometry
Shinjini Kundu, Soheil Kolouri, Kirk I Erickson +3
Disease in the brain is often associated with subtle, spatially diffuse, or complex tissue changes that may lie beneath the level of gross visual inspection, even on magnetic reson…
An optimal transport model for imaging in atmospheric turbulence
Jonathan M. Nichols, Abbie T. Watnik, Timothy Doster +4
We describe a new model for image propagation through open air in the presence of changes in the index of refraction (e.g. due to turbulence) using the theory of optimal transport.…