Keehyoung Joo

On the Information Processing of One-Dimensional Wasserstein Distances with Finite Samples

Leveraging the Wasserstein distance—a summation of sample-wise transport distances in data space—is advantageous in many applications for measuring support differences between two underlying density functions. However, when supports significantly overlap while densities exhibit substantial pointwise