Pages that link to "Item:Q1927706"

The following pages link to \(\Gamma\)-convergence of graph Ginzburg-Landau functionals (Q1927706):

Displaying 38 items.

• Continuum limit of total variation on point clouds (Q261295) (← links)
• Large data and zero noise limits of graph-based semi-supervised learning algorithms (Q778036) (← links)
• The graph limit of the minimizer of the Onsager-Machlup functional and its computation (Q829447) (← links)
• Global binary optimization on graphs for classification of high-dimensional data (Q890097) (← links)
• Consistency of modularity clustering on random geometric graphs (Q1617118) (← links)
• Convex variational methods on graphs for multiclass segmentation of high-dimensional data and point clouds (Q1702637) (← links)
• Graph clustering, variational image segmentation methods and Hough transform scale detection for object measurement in images (Q2014485) (← links)
• An MBO scheme for minimizing the graph Ohta-Kawasaki functional (Q2022733) (← links)
• Stochastic block models are a discrete surface tension (Q2022738) (← links)
• The Łojasiewicz inequality for free energy functionals on a graph (Q2087545) (← links)
• Topology optimization subject to additive manufacturing constraints (Q2138191) (← links)
• From graph cuts to isoperimetric inequalities: convergence rates of Cheeger cuts on data clouds (Q2138635) (← links)
• Partial differential equations and variational methods for geometric processing of images (Q2178663) (← links)
• Convergence of the graph Allen-Cahn scheme (Q2403245) (← links)
• Proximal gradient methods for general smooth graph total variation model in unsupervised learning (Q2674267) (← links)
• Deep limits of residual neural networks (Q2679108) (← links)
• Continuum limit of Lipschitz learning on graphs (Q2697392) (← links)
• Diffuse interface models on graphs for classification of high dimensional data (Q2805269) (← links)
• \(\Gamma\)-convergence analysis for discrete topological singularities: the anisotropic triangular lattice and the long range interaction energy (Q2805926) (← links)
• Introduction: Big data and partial differential equations (Q3133605) (← links)
• Uncertainty Quantification in Graph-Based Classification of High Dimensional Data (Q3176234) (← links)
• Multiresolution Parameter Choice Method for Total Variation Regularized Tomography (Q3188212) (← links)
• Consistency of Dirichlet Partitions (Q4592868) (← links)
• Simplified Energy Landscape for Modularity Using Total Variation (Q4686633) (← links)
• A Graph Framework for Manifold-Valued Data (Q4686918) (← links)
• Large data limit for a phase transition model with the <i>p</i>-Laplacian on point clouds (Q5056700) (← links)
• Γ-limit of the cut functional on dense graph sequences (Q5109198) (← links)
• Continuum Limits of Nonlocal $p$-Laplacian Variational Problems on Graphs (Q5109272) (← links)
• Nonlocal gradient operators with a nonspherical interaction neighborhood and their applications (Q5110257) (← links)
• Graph Merriman--Bence--Osher as a SemiDiscrete Implicit Euler Scheme for Graph Allen--Cahn Flow (Q5124631) (← links)
• Modified Cheeger and ratio cut methods using the Ginzburg–Landau functional for classification of high-dimensional data (Q5348005) (← links)
• Asymptotic analysis of the Ginzburg–Landau functional on point clouds (Q5383346) (← links)
• Classification and image processing with a semi‐discrete scheme for fidelity forced Allen–Cahn on graphs (Q6068273) (← links)
• Efficient quantum algorithm for nonlinear reaction-diffusion equations and energy estimation (Q6089324) (← links)
• Joint Reconstruction-Segmentation on Graphs (Q6113269) (← links)
• Consistency of fractional graph-Laplacian regularization in semisupervised learning with finite labels (Q6571355) (← links)
• The Potts model with different piecewise constant representations and fast algorithms: a survey (Q6606497) (← links)
• Double-well net for image segmentation (Q6669799) (← links)