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Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and Graphs

This repository contains code and data for the experiments in the paper

Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and Graphs

Raif Rustamov and Subhabrata Majumdar

International Conference on Machine Learning (ICML), 2023.

Setup

You should have the R statistical software installed in your system. To install the dependencies, run the following in bash:

Rscript install_dependencies.R

Contents

Below are the the contents of this repository.

Subdirectory Method
scripts/sim_line.R ISW implementation on real line, synthetic experiments
scripts/sim_circle.R ISW implementation on a circle, synthetic experiments
scripts/sim_cyl.R ISW implementation on a cylinder, synthetic experiments
scripts/chicago_crime.R ISW implementation on graph data, Chicago Crime
data/chicago_theft2018.RData The Chicago Crime dataset

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Please feel free to email with questions of comments.

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