Community Detection
State-of-the-art leaderboards
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Subtasks
Greatest papers with code
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters
• SeongokRyu/Graph-neural-networks
• 
The rise of graph-structured data such as social networks, regulatory networks, citation graphs, and functional brain networks, in combination with resounding success of deep learning in various applications, has brought the interest in generalizing deep learning models to non-Euclidean domains.
COMMUNITY DETECTION IMAGE CLASSIFICATION MATRIX COMPLETION NODE CLASSIFICATION
CANE: Context-Aware Network Embedding for Relation Modeling
ACL 2017
• thunlp/CANE
•
Network embedding (NE) is playing a critical role in network analysis, due to its ability to represent vertices with efficient low-dimensional embedding vectors.
COMMUNITY DETECTION LINK PREDICTION MACHINE TRANSLATION NETWORK EMBEDDING
Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection
CIKM 2018 • benedekrozemberczki/DANMF
Considering the complicated and diversified topology structures of real-world networks, it is highly possible that the mapping between the original network and the community membership space contains rather complex hierarchical information, which cannot be interpreted by classic shallow NMF-based approaches.
SOTA for Node Classification on Wiki
LOCAL COMMUNITY DETECTION NETWORK COMMUNITY PARTITION NODE CLASSIFICATION REPRESENTATION LEARNING
GEMSEC: Graph Embedding with Self Clustering
ASONAM 2019
• benedekrozemberczki/GEMSEC
•
In this paper we propose GEMSEC - a graph embedding algorithm which learns a clustering of the nodes simultaneously with the embedding.
COMMUNITY DETECTION GRAPH EMBEDDING NETWORK EMBEDDING NODE CLASSIFICATION
Signed Graph Convolutional Network
ICDM 2018
• benedekrozemberczki/SGCN
• 
However, since previous GCN models have primarily focused on unsigned networks (or graphs consisting of only positive links), it is unclear how they could be applied to signed networks due to the challenges presented by negative links.
COMMUNITY DETECTION LINK PREDICTION LINK SIGN PREDICTION NODE CLASSIFICATION REPRESENTATION LEARNING
Efficient discovery of overlapping communities in massive networks
PNAS 2013 2013 • premgopalan/svinet
Our approach is based on a Bayesian model of networks that allows nodes to participate in multiple communities, and a corresponding algorithm that naturally interleaves subsampling from the network and updating an estimate of its communities.
Font Size: Community Preserving Network Embedding
AAAI 2017
• benedekrozemberczki/M-NMF
•
While previous network embedding methods primarily preserve the microscopic structure, such as the first- and second-order proximities of nodes, the mesoscopic community structure, which is one of the most prominent feature of networks, is largely ignored.
Improving Coarsening Schemes for Hypergraph Partitioning by Exploiting Community Structure
SEA 2017 2017 • SebastianSchlag/kahypar
We present an improved coarsening process for multilevel hypergraph partitioning that incorporates global information about the community structure.
COMMUNITY DETECTION GRAPH PARTITIONING HYPERGRAPH PARTITIONING
Community Detection with Graph Neural Networks
ICLR 2018
• joanbruna/GNN_community
•
This graph inference task can be recast as a node-wise graph classification problem, and, as such, computational detection thresholds can be translated in terms of learning within appropriate models.
COMMUNITY DETECTION GRAPH CLASSIFICATION GRAPH NEURAL NETWORK
Supervised Community Detection with Line Graph Neural Networks
ICLR 2019
• joanbruna/GNN_community
•
This graph inference task can be recast as a node-wise graph classification problem, and, as such, computational detection thresholds can be translated in terms of learning within appropriate models.
SOTA for Community Detection on Amazon (using extra training data)