23 citations · 26 across the 3 of their papers we have counts for
5 papers
A Linear Transportation Distance for Pattern Recognition
Oliver M. Crook, Mihai Cucuringu, Tim Hurst +3
The transportation distance, denoted , has been proposed as a generalisation of Wasserstein distances motivated by the property that it…
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates
Jeff Calder, Brendan Cook, Matthew Thorpe +1
We propose a new framework, called Poisson learning, for graph based semi-supervised learning at very low label rates. Poisson learning is motivated by the need to address the dege…
PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds
Oliver M. Crook, Tim Hurst, Carola-Bibiane Schönlieb +2
Given a data set and a subset of labels the problem of semi-supervised learning on point clouds is to extend the labels to the entire data set. In this paper we extend the labels b…
A Transportation Distance for Signal Analysis
Matthew Thorpe, Serim Park, Soheil Kolouri +2
Transport based distances, such as the Wasserstein distance and earth mover's distance, have been shown to be an effective tool in signal and image analysis. The success of transpo…
Transport-based analysis, modeling, and learning from signal and data distributions
Soheil Kolouri, Serim Park, Matthew Thorpe +2
Transport-based techniques for signal and data analysis have received increased attention recently. Given their abilities to provide accurate generative models for signal intensiti…