Convergence of the graph Allen-Cahn scheme

DOI10.1007/s10955-017-1772-4zbMath1375.82023OpenAlexW2603818650WikidataQ59612512 ScholiaQ59612512MaRDI QIDQ2403245

Xiyang Luo, Andrea L. Bertozzi

Publication date: 8 September 2017

Published in: Journal of Statistical Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10955-017-1772-4

zbMATH Keywords

machine learningnumerical analysisdiffuse interface methods

Mathematics Subject Classification ID

Related Items (14)

Uncertainty Quantification in Graph-Based Classification of High Dimensional Data ⋮ Mass-conserving diffusion-based dynamics on graphs ⋮ Partial differential equations and variational methods for geometric processing of images ⋮ Preconditioned Algorithm for Difference of Convex Functions with Applications to Graph Ginzburg–Landau Model ⋮ Efficient quantum algorithm for nonlinear reaction-diffusion equations and energy estimation ⋮ Joint Reconstruction-Segmentation on Graphs ⋮ Graph Merriman--Bence--Osher as a SemiDiscrete Implicit Euler Scheme for Graph Allen--Cahn Flow ⋮ Generalizing Diffuse Interface Methods on Graphs: Nonsmooth Potentials and Hypergraphs ⋮ An MBO scheme for minimizing the graph Ohta-Kawasaki functional ⋮ Stochastic block models are a discrete surface tension ⋮ Semi-supervised Learning for Aggregated Multilayer Graphs Using Diffuse Interface Methods and Fast Matrix-Vector Products ⋮ Diffuse Interface Models on Graphs for Classification of High Dimensional Data ⋮ An explicit stable finite difference method for the Allen-Cahn equation ⋮ Introduction: Big data and partial differential equations

Uses Software

• MNIST

Cites Work

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