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Optimal Transport Meets Reinforcement Learning: A Survey
Yujie Zhu, Charles A. Hepburn, Matthew Thorpe +1
Reinforcement learning (RL) algorithms frequently compare probability distributions, such as state visitation distributions induced by policies and experts, action distributions fr…
Gradient Descent on Point Clouds and Applications in Learned Operator Correction
Andreas Hauptmann, Yury Korolev, Matthew Thorpe
We consider the problem of minimising an energy over an unknown manifold that is given implicitly by a point cloud. For a known manifold one can define a gradient descent scheme an…
Large Data Limits of Laplace Learning for Gaussian Measure Data in Infinite Dimensions
Zhengang Zhong, Yury Korolev, Matthew Thorpe
Laplace learning is a semi-supervised method, a solution for finding missing labels from a partially labeled dataset utilizing the geometry given by the unlabeled data points. The…