29 citations · 79 across the 18 of their papers we have counts for
21 papers
Consistency of Fractional Graph-Laplacian Regularization in Semi-Supervised Learning with Finite Labels
Adrien Weihs, Matthew Thorpe
Laplace learning is a popular machine learning algorithm for finding missing labels from a small number of labelled feature vectors using the geometry of a graph. More precisely, L…
Sliced Optimal Partial Transport
Yikun Bai, Berhnard Schmitzer, Mathew Thorpe +1
Optimal transport (OT) has become exceedingly popular in machine learning, data science, and computer vision. The core assumption in the OT problem is the equal total amount of mas…
Rates of Convergence for Regression with the Graph Poly-Laplacian
Nicolás García Trillos, Ryan Murray, Matthew Thorpe
In the (special) smoothing spline problem one considers a variational problem with a quadratic data fidelity penalty and Laplacian regularisation. Higher order regularity can be ob…
-Convergence of an Ambrosio-Tortorelli approximation scheme for image segmentation
Irene Fonseca, Lisa Maria Kreusser, Carola-Bibiane Schönlieb +1
Given an image , the aim of minimising the Mumford-Shah functional is to find a decomposition of the image domain into sub-domains and a piecewise smooth approximation of…
Robust Certification for Laplace Learning on Geometric Graphs
Matthew Thorpe, Bao Wang
Graph Laplacian (GL)-based semi-supervised learning is one of the most used approaches for classifying nodes in a graph. Understanding and certifying the adversarial robustness of…
The Linearized Hellinger--Kantorovich Distance
Tianji Cai, Junyi Cheng, Bernhard Schmitzer +1
In this paper we study the local linearization of the Hellinger--Kantorovich distance via its Riemannian structure. We give explicit expressions for the logarithmic and exponential…