1 citations · 2 across the 4 of their papers we have counts for
4 papers
Wasserstein -Centers Clustering for Distributional Data
Ryo Okano, Masaaki Imaizumi
We develop a novel clustering method for distributional data, where each data point is regarded as a probability distribution on the real line. For distributional data, it has been…
Uniform Confidence Band for Optimal Transport Map on One-Dimensional Data
Donlapark Ponnoprat, Ryo Okano, Masaaki Imaizumi
We develop a statistical inference method for an optimal transport map between distributions on real numbers with uniform confidence bands. The concept of optimal transport (OT) is…
Distribution-on-Distribution Regression with Wasserstein Metric: Multivariate Gaussian Case
Ryo Okano, Masaaki Imaizumi
Distribution data refers to a data set where each sample is represented as a probability distribution, a subject area receiving burgeoning interest in the field of statistics. Alth…
Inference for Projection-Based Wasserstein Distances on Finite Spaces
Ryo Okano, Masaaki Imaizumi
The Wasserstein distance is a distance between two probability distributions and has recently gained increasing popularity in statistics and machine learning, owing to its attracti…