Stochastic block models are a discrete surface tension
DOI10.1007/s00332-019-09541-8zbMath1471.65058arXiv1806.02485OpenAlexW3102534014WikidataQ128028836 ScholiaQ128028836MaRDI QIDQ2022738
Mason A. Porter, Zachary M. Boyd, Andrea L. Bertozzi
Publication date: 29 April 2021
Published in: Journal of Nonlinear Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1806.02485
networksdata clusteringcommunity structuregeometric partial differential equationsstochastic block modelsMerriman-Bence-Osher scheme
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Clustering in the social and behavioral sciences (91C20) Social networks; opinion dynamics (91D30) Numerical optimization and variational techniques (65K10) Applications of graph theory to circuits and networks (94C15) Numerical methods of relaxation type (49M20) Ginzburg-Landau equations (35Q56)
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- Pseudo-likelihood methods for community detection in large sparse networks
- Nonlinear total variation based noise removal algorithms
- Lecture notes on mean curvature flow
- A variational approach to the consistency of spectral clustering
- Global binary optimization on graphs for classification of high-dimensional data
- Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
- An introduction to \(\Gamma\)-convergence
- Estimation and prediction for stochastic blockmodels for graphs with latent block structure
- Auction dynamics: a volume constrained MBO scheme
- A discrete theory and efficient algorithms for forward-and-backward diffusion filtering
- The gradient theory of phase transitions and the minimal interface criterion
- \(\Gamma\)-convergence of graph Ginzburg-Landau functionals
- Mean curvature, threshold dynamics, and phase field theory on finite graphs
- Convergence of the graph Allen-Cahn scheme
- Diffuse Interface Models on Graphs for Classification of High Dimensional Data
- Consistency of Cheeger and Ratio Graph Cuts
- Uncertainty Quantification in Graph-Based Classification of High Dimensional Data
- Nonlocal Operators with Applications to Image Processing
- The Split Bregman Method for L1-Regularized Problems
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- A Variational Approach to Modeling and Simulation of Grain Growth
- Communities in Networks
- Multidimensional binary search trees used for associative searching
- An Efficient Heuristic Procedure for Partitioning Graphs
- Networks
- Consistency of Dirichlet Partitions
- Configuring Random Graph Models with Fixed Degree Sequences
- Community Detection in Networks via Nonlinear Modularity Eigenvectors
- Simplified Energy Landscape for Modularity Using Total Variation
- Cluster Inference by Using Transitivity Indices in Empirical Graphs
- Diffuse Interface Models on Graphs for Classification of High Dimensional Data
- Threshold Dynamics for Networks with Arbitrary Surface Tensions
- Core-Periphery Structure in Networks (Revisited)
- A Method Based on Total Variation for Network Modularity Optimization Using the MBO Scheme
- A Review of Image Denoising Algorithms, with a New One
