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Graph Clustering

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하위 태스크: 1
평가표: 10
보존된 평가 기록: 32

Graph Clustering is the process of grouping the nodes of the graph into clusters, taking into account the edge structure of the graph in such a way that there are several edges within each cluster and very few between clusters. Graph Clustering intends to partition the nodes in the graph into disjoint groups.

Source: Clustering for Graph Datasets via Gumbel Softmax

코드

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

https://bitbucket.org/LizhenShi/graph_clustering_toolkit

공식 코드

Comparison and Benchmark of Graph Clustering Algorithms

https://github.com/Cloudy1225/NS4GC

공식 코드

Reliable Node Similarity Matrix Guided Contrastive Graph Clustering

https://github.com/EsiksonX/RDSA

공식 코드

RDSA: A Robust Deep Graph Clustering Framework via Dual Soft Assignment

https://github.com/FeijiangLi/Code-k-HyperEdge-Medoids-for-Clustering-Ensemble-AAAI-24

공식 코드

k-HyperEdge Medoids for Clustering Ensemble

https://github.com/FilippoMB/Benchmark_dataset_for_graph_classification

공식 코드

Spectral Clustering with Graph Neural Networks for Graph Pooling

https://github.com/FilippoMB/Spectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling

공식 코드

Spectral Clustering with Graph Neural Networks for Graph Pooling

https://github.com/HaoranZ99/laca

공식 코드

Adaptive Local Clustering over Attributed Graphs

https://github.com/HongtengXu/Relational-Factorization-Model

공식 코드

Gromov-Wasserstein Factorization Models for Graph Clustering

https://github.com/InterpretableClustering/InterpretableClustering

공식 코드

Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks

https://github.com/JinheonBaek/GMT

공식 코드

Accurate Learning of Graph Representations with Graph Multiset Pooling

https://github.com/KaHIP/KaHIP

공식 코드

Parallel Graph Partitioning for Complex Networks

https://github.com/Kalashi-Saed-Collaborations/SentimentDrivenCommunityDetection

공식 코드

Sentiment-Driven Community Detection in a Network of Perfume Preferences

https://github.com/LUOyk1999/NodeID

공식 코드

Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning

https://github.com/MaKaili/Contrast-Reg

공식 코드

Calibrating and Improving Graph Contrastive Learning

https://github.com/MarEe0/TBGC

공식 코드

Template-Based Graph Clustering

https://github.com/Marigoldwu/SynC

공식 코드

Synergistic Deep Graph Clustering Network

https://github.com/MengLiuPurdue/SLQ

공식 코드

Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering

https://github.com/MysteryVaibhav/DW-GAE

공식 코드

RWR-GAE: Random Walk Regularization for Graph Auto Encoders

https://github.com/Oxfordblue7/GCFL

공식 코드

Federated Graph Classification over Non-IID Graphs

https://github.com/PhilChodrow/HypergraphModularity

공식 코드

Generative hypergraph clustering: from blockmodels to modularity

https://github.com/RingBDStack/KPGNN

공식 코드

Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs

https://github.com/Sharpenb/python_paris

공식 코드

Hierarchical Graph Clustering using Node Pair Sampling

https://github.com/Stalence/erdos_neu

공식 코드

Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs

https://github.com/VieClus/VieClus

공식 코드

Memetic Graph Clustering

https://github.com/Violet24K/HyperACL

공식 코드

Provably Extending PageRank-based Local Clustering Algorithm to Weighted Directed Graphs with Self-Loops and to Hypergraphs

https://github.com/Wangyuwen0627/GIP-Framework

공식 코드

Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks

https://github.com/WxTu/DFCN

공식 코드

Deep Fusion Clustering Network

https://github.com/YF-W/Tri-GFN

공식 코드

Tri-Learn Graph Fusion Network for Attributed Graph Clustering

https://github.com/Yuan-Jinghui/Riemannian-Optimization-on-Relaxed-Indicator-Matrix-Manifold

공식 코드

Riemannian Optimization on Relaxed Indicator Matrix Manifold

https://github.com/ZhenhHuang/LSEnet

공식 코드

LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering

https://github.com/ZhihaoPENG-CityU/AGCN

공식 코드

Attention-driven Graph Clustering Network

https://github.com/aabbas90/cluster-fug

공식 코드

ClusterFuG: Clustering Fully connected Graphs by Multicut

https://github.com/ahollocou/graph-streaming

공식 코드

A Streaming Algorithm for Graph Clustering

https://github.com/ajgates42/clusim

공식 코드

The Impact of Random Models on Clustering Similarity

https://github.com/alishakiba/correlation-clustering-algorithm-for-dynamic-complete-signed-graphs-an-index-based-approach

공식 코드

Correlation Clustering Algorithm for Dynamic Complete Signed Graphs: An Index-based Approach

https://github.com/camilapsan/MOSpecG_SpecG

공식 코드

An ensemble based on a bi-objective evolutionary spectral algorithm for graph clustering

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