Manifold Learning with Sparse Regularised Optimal Transport

no code implementations • 19 Jul 2023 • Stephen Zhang, Gilles Mordant, Tetsuya Matsumoto, Geoffrey Schiebinger

Manifold learning is a central task in modern statistics and data science.

Quadratically Regularized Optimal Transport: nearly optimal potentials and convergence of discrete Laplace operators

no code implementations • 20 Nov 2022 • Gilles Mordant, Stephen Zhang

We consider the conjecture proposed in Matsumoto, Zhang and Schiebinger (2022) suggesting that optimal transport with quadratic regularisation can be used to construct a graph whose discrete Laplace operator converges to the Laplace--Beltrami operator.