Search Results for author:
Found 2 papers, 1 papers with code
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances
The goal of this work is to quantify this scalability from three key aspects: (i) empirical convergence rates; (ii) robustness to data contamination; and (iii) efficient computational methods.
Limit Distribution Theory for the Smooth 1-Wasserstein Distance with Applications
This result is then used to derive new empirical convergence rates for classic $W_1$ in terms of the intrinsic dimension.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
