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.
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.
no code implementations • 1 Aug 2022 • Tetsuya Matsumoto, Stephen Zhang, Geoffrey Schiebinger
One of the most common strategies to construct such a graph is based on selecting a fixed number k of nearest neighbours (kNN) for each point.
1 code implementation • 14 May 2022 • Lénaïc Chizat, Stephen Zhang, Matthieu Heitz, Geoffrey Schiebinger
Trajectory inference aims at recovering the dynamics of a population from snapshots of its temporal marginals.
1 code implementation • 18 Feb 2021 • Hugo Lavenant, Stephen Zhang, Young-Heon Kim, Geoffrey Schiebinger
We devise a theoretical framework and a numerical method to infer trajectories of a stochastic process from samples of its temporal marginals.