89 citations · 388 across the 81 of their papers we have counts for
4 papers · 1 filter
Wasserstein Embedding for Graph Learning
Soheil Kolouri, Navid Naderializadeh, Gustavo K. Rohde +1
We present Wasserstein Embedding for Graph Learning (WEGL), a novel and fast framework for embedding entire graphs in a vector space, in which various machine learning models are a…
Radon cumulative distribution transform subspace modeling for image classification
Mohammad Shifat-E-Rabbi, Xuwang Yin, Abu Hasnat Mohammad Rubaiyat +5
We present a new supervised image classification method applicable to a broad class of image deformation models. The method makes use of the previously described Radon Cumulative D…
Statistical and Topological Properties of Sliced Probability Divergences
Kimia Nadjahi, Alain Durmus, Lénaïc Chizat +3
The idea of slicing divergences has been proven to be successful when comparing two probability measures in various machine learning applications including generative modeling, and…
Generalized Sliced Distances for Probability Distributions
Soheil Kolouri, Kimia Nadjahi, Umut Simsekli +1
Probability metrics have become an indispensable part of modern statistics and machine learning, and they play a quintessential role in various applications, including statistical…