Trending repositories for topic community-detection
A curated list of community detection research papers with implementations.
A curated list of community detection research papers with implementations.
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
A curated list of community detection research papers with implementations.
Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.
Library of community detection algorithms and visualization tools
A curated list of community detection research papers with implementations.
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
A python library to compute the graph Ricci curvature and Ricci flow on NetworkX graph.
Deep and conventional community detection related papers, implementations, datasets, and tools.
Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.
A curated list of community detection research papers with implementations.
A repository of pretty cool datasets that I collected for network science and machine learning research.
Codes and data for KDD 2022 Research Track paper "CLARE: A Semi-supervised Community Detection Algorithm"
A NetworkX implementation of "Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters" (KDD 2017).
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
A python library to compute the graph Ricci curvature and Ricci flow on NetworkX graph.
Codes and data for KDD 2022 Research Track paper "CLARE: A Semi-supervised Community Detection Algorithm"
Deep and conventional community detection related papers, implementations, datasets, and tools.
A NetworkX implementation of "Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters" (KDD 2017).
Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Library of community detection algorithms and visualization tools
A repository of pretty cool datasets that I collected for network science and machine learning research.
A curated list of community detection research papers with implementations.
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.
A curated list of community detection research papers with implementations.
Deep and conventional community detection related papers, implementations, datasets, and tools.
Library of community detection algorithms and visualization tools
A repository of pretty cool datasets that I collected for network science and machine learning research.
A python library to compute the graph Ricci curvature and Ricci flow on NetworkX graph.
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
Implementation of the Louvain algorithm for community detection with various methods for use with igraph in python.
Java package that provides data structures and algorithms for network analysis.
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Codes and data for KDD 2022 Research Track paper "CLARE: A Semi-supervised Community Detection Algorithm"
:sparkler: Network/Graph Analysis with NetworkX in Python. Topics range from network types, statistics, link prediction measures, and community detection.
A NetworkX implementation of Label Propagation from a "Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks" (Physical Review E 2008).
A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).
The TensorFlow reference implementation of 'GEMSEC: Graph Embedding with Self Clustering' (ASONAM 2019).
Codes and data for KDD 2022 Research Track paper "CLARE: A Semi-supervised Community Detection Algorithm"
Deep and conventional community detection related papers, implementations, datasets, and tools.
Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.
:sparkler: Network/Graph Analysis with NetworkX in Python. Topics range from network types, statistics, link prediction measures, and community detection.
A python library to compute the graph Ricci curvature and Ricci flow on NetworkX graph.
Library of community detection algorithms and visualization tools
A repository of pretty cool datasets that I collected for network science and machine learning research.
A NetworkX implementation of Label Propagation from a "Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks" (Physical Review E 2008).
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
A NetworkX implementation of "Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters" (KDD 2017).
Java package that provides data structures and algorithms for network analysis.
Implementation of the Louvain algorithm for community detection with various methods for use with igraph in python.
A curated list of community detection research papers with implementations.
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).