22 citations · 84 across the 21 of their papers we have counts for
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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…
Approximation of Maximally Monotone Operators : A Graph Convergence Perspective
Takashi Furuya, Yury Korolev, Takaharu Yaguchi
Operator learning has been highly successful for continuous mappings between infinite-dimensional spaces, such as PDE solution operators. However, many operators of interest-includ…
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…