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Stochastic Block Model

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/junipertcy/bipartiteSBM

공식 코드

Community Detection in Bipartite Networks with Stochastic Blockmodels

https://github.com/kazuibasou/hyperneo

공식 코드

Inference and Visualization of Community Structure in Attributed Hypergraphs Using Mixed-Membership Stochastic Block Models

https://github.com/krishnaswamylab/dymag

공식 코드

DYMAG: Rethinking Message Passing Using Dynamical-systems-based Waveforms

https://github.com/kvignesh1420/gnn_collapse

공식 코드

A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks

https://github.com/lichen11/LSGMcode

공식 코드

Spectral Clustering for Divide-and-Conquer Graph Matching

https://github.com/lingdawang/joint_community_detection_and_phase_synchronization

공식 코드

Multi-Frequency Joint Community Detection and Phase Synchronization

https://github.com/lorenzodallamico/CoDeBetHe.jl

공식 코드

Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian

https://github.com/lucylgao/mv-network-test-code

공식 코드

Testing for Association in Multi-View Network Data

https://github.com/magical-seven/mhsbm

공식 코드

Community and hyperedge inference in multiple hypergraphs

https://github.com/mahalakshmi-sabanayagam/NTK_GCN

공식 코드

Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel

https://github.com/martingerlach/hSBM_Topicmodel

공식 코드

A network approach to topic models

https://github.com/matthklein/fair_spectral_clustering

공식 코드

Guarantees for Spectral Clustering with Fairness Constraints

https://github.com/mdreveton/clusteringnonbinaryandtemporalsbm

공식 코드

Community recovery in non-binary and temporal stochastic block models

https://github.com/mdreveton/ssl-sbm

공식 코드

Almost exact recovery in noisy semi-supervised learning

https://github.com/michaelschaub/HierarchicalCommunityDetection

공식 코드

Hierarchical community structure in networks

https://github.com/ningz97/mle-dsbm

공식 코드

Spectral Clustering for Directed Graphs via Likelihood Estimation on Stochastic Block Models

https://github.com/nkeriven/random-graph-gnn

공식 코드

On the Universality of Graph Neural Networks on Large Random Graphs

https://github.com/peng8wang/mp-exact-recovery-in-sbm

공식 코드

Non-Convex Exact Community Recovery in Stochastic Block Model

https://github.com/peterwmacd/multiness

공식 코드

Latent space models for multiplex networks with shared structure

https://github.com/quentin-duchemin/inference-markovian-SBM

공식 코드

Reliable Time Prediction in the Markov Stochastic Block Model

https://github.com/riti4538/SBM-Metric-Dimension

공식 코드

Multilateration of Random Networks with Community Structure

https://github.com/sadrasabouri/sdp-fair-graph-clustering

공식 코드

A Semidefinite Relaxation Approach for Fair Graph Clustering

https://github.com/saeyoon17/code-structure-aware-transformer

공식 코드

CSA-Trans: Code Structure Aware Transformer for AST

https://github.com/sc782/sbm-transformer

공식 코드

Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost

https://github.com/seonghyun26/nba-gnn

공식 코드

Non-backtracking Graph Neural Networks

https://github.com/sherylhyx/msgnn

공식 코드

MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian

https://github.com/sherylhyx/sssnet_signed_clustering

공식 코드

SSSNET: Semi-Supervised Signed Network Clustering

https://github.com/shuangtongli/scool

공식 코드

Structured Cooperative Learning with Graphical Model Priors

https://github.com/slubold/Network_GOF

공식 코드

Spectral goodness-of-fit tests for complete and partial network data

https://github.com/smaityumich/cl-representation-harm

공식 코드

An Investigation of Representation and Allocation Harms in Contrastive Learning

https://github.com/vasile-paskardlgm/cpf

공식 코드

Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening

https://github.com/vidalt/Optimal-SBM

공식 코드

Community Detection in the Stochastic Block Model by Mixed Integer Programming

https://github.com/yixuanli/lemon

공식 코드

Generative models for local network community detection

https://github.com/youngser/dhatkhat

공식 코드

Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering

https://github.com/yunchuankong/SharedClustering

공식 코드

A Bayesian Method for Joint Clustering of Vectorial Data and Network Data

https://github.com/zhengdao-chen/GNN4CD

공식 코드

Supervised Community Detection with Line Graph Neural Networks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.