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Stochastic Block Model
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Community detection in complex networks via node similarity, graph representation learning, and hierarchical clustering
Effective Stimulus Propagation in Neural Circuits: Driver Node Selection
Spectral clustering for dependent community Hawkes process models of temporal networks
Unsupervised Learning for Optimal Transport plan prediction between unbalanced graphs
Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening
Community and hyperedge inference in multiple hypergraphs
Consensus on Open Multi-Agent Systems Over Graphs Sampled from Graphons
Communities in the Kuramoto Model: Dynamics and Detection via Path Signatures
Multi-Agent Q-Learning Dynamics in Random Networks: Convergence due to Exploration and Sparsity
Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model
Low degree conjecture implies sharp computational thresholds in stochastic block model
Algorithmic contiguity from low-degree conjecture and applications in correlated random graphs
Heterogeneous Multi-agent Multi-armed Bandits on Stochastic Block Models
Community Detection for Contextual-LSBM: Theoretical Limitations of Misclassification Rate and Efficient Algorithms
Exact Matching in Correlated Networks with Node Attributes for Improved Community Recovery
Low coordinate degree algorithms II: Categorical signals and generalized stochastic block models
Matrix Concentration for Random Signed Graphs and Community Recovery in the Signed Stochastic Block Model
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks
On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models
Multiplex Dirichlet stochastic block model for clustering multidimensional compositional networks
Community Detection with Heterogeneous Block Covariance Model
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs
Convergence Guarantees for the DeepWalk Embedding on Block Models
A Semidefinite Relaxation Approach for Fair Graph Clustering
Learning Communities from Equilibria of Nonlinear Opinion Dynamics
A computational transition for detecting correlated stochastic block models by low-degree polynomials
A Dirichlet stochastic block model for composition-weighted networks
Sharp Bounds for Poly-GNNs and the Effect of Graph Noise
Estimating the number of clusters of a Block Markov Chain
Bayesian modelling of VAR precision matrices using stochastic block networks
Modularity aided consistent attributed graph clustering via coarsening
What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
Introducing the modularity graph: an application to brain functional networks
Optimal Bailouts in Diversified Financial Networks
Exact Community Recovery under Side Information: Optimality of Spectral Algorithms
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