External resources

Overlapping Community Detection

  • Alessandro Epasto, Silvio Lattanzi, Renato Paes Leme: Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters Paper, Slides, Video, Code
  • Fanghua Ye, Chuan Chen, Zibin Zheng: Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection Paper, Code
  • Xiao Wang, Peng Cui, Jing Wang, Jian Pei, Wenwu Zhu, Shiqiang Yang: Community Preserving Network Embedding Paper, Code
  • Bing-Jie Sun, Huawei Shen, Jinhua Gao, Wentao Ouyang, Xueqi Cheng: A Non-negative Symmetric Encoder-Decoder Approach for Community Detection Paper
  • Jaewon Yang and Jure Leskovec: Overlapping Community Detection at Scale: A Nonnegative Matrix Factorization Approach Paper, Slides, Video, Video
  • Da Kuang, Chris Ding, Haesun Park: Symmetric Nonnegative Matrix Factorization for Graph Clustering Paper

Non-Overlapping Community Detection

  • Benedek Rozemberczki, Ryan Davies, Rik Sarkar, and Charles Sutton: GEMSEC: Graph Embedding with Self Clustering Paper, Code
  • Pei-Zhen Li, Ling Huang, Chang-Dong Wang, and Jian-Huang Lai: EdMot: An Edge Enhancement Approach for Motif-aware Community Detection Paper, Video, Code
  • Arnau Prat-Perez, David Dominguez-Sal, Joseph-Luis Larriba-Pey: High Quality, Scalable and Parallel Community Detectionfor Large Real Graphs Paper
  • Usha Nandini Raghavan, Reka Albert, Soundar Kumara: Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks Paper, Code

Neighbourhood-Based Node Embedding

  • Lei Tang, Huan Liu: Relational Learning via Latent Social Dimensions Paper
  • Leo Torres, Kevin S Chan, Tina Eliassi-Rad: GLEE: Geometric Laplacian Eigenmap Embedding Paper, Code
  • Jundong Li, Liang Wu, and Huan Liu: Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation Paper
  • Dingqi Yang, Paolo Rosso, Bin Li, and Philippe Cudre-Mauroux: NodeSketch: Highly-Efficient Graph Embeddingsvia Recursive Sketching Paper
  • Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, and Jie Tang: Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and Node2Vec Paper
  • Ziwei Zhang, Peng Cui, Haoyang Li, Xiao Wang, Wenwu Zhu: Billion-scale Network Embedding with Iterative Random Projection Paper, Code
  • Benedek Rozemberczki and Rik Sarkar: Fast Sequence Based Embedding with Diffusion Graphs Paper, Code
  • Bryan Perozzi, Vivek Kulkarni, Haochen Chen, Steven Skiena: Don’t Walk, Skip! Online Learning of Multi-scale Network Embeddings Paper, Code
  • Mingdong Ou, Peng Cui, Jian Pei, Ziwei Zhang, Wenwu Zhu: Asymmetric Transitivity Preserving Graph Embedding Paper
  • Shaosheng Cao, Wei Lu, Qiongkai Xu: GraRep: Learning Graph Representations with Global Structural Information Paper, Code
  • Aditya Grover and Jure Leskovec: Node2Vec: Scalable Feature Learning for Networks Paper, Video
  • Bryan Perozzi, Rami Al-Rfou, Steven Skiena: DeepWalk: Online Learning of Social Representations Paper, Slides, Video, Video
  • Dennis L. Sun and Cédric Févotte: Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence Paper, Code
  • Mikhail Belkin and Partha Niyogi: Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering Paper, Video

Structural Node Embedding

  • Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec: Learning Structural Node Embeddings Via Diffusion Wavelets Paper, Video, Code
  • Nesreen K. Ahmed, Ryan Rossi, John Boaz Lee, Theodore L. Willke, Rong Zhou, Xiangnan Kong, Hoda Eldardiry: Learning Role-based Graph Embeddings Paper, Code

Attributed Node Embedding

  • Benedek Rozemberczki, Rik Sarkar: Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models Paper, Code
  • Benedek Rozemberczki, Carl Allen, Rik Sarkar: Multi-Scale Attributed Node Embedding Paper, Code
  • Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang: SINE: Scalable Incomplete Network Embedding Paper, Code
  • Hong Yang, Shirui Pan, Peng Zhang, Ling Chen, Defu Lian, Chengqi Zhang: Binarized Attributed Network Embedding Paper, Code
  • Shuang Yang, Bo Yang: Enhanced Network Embedding with Text Information Paper, Code
  • Lizi Liao, Xiangnan He, Hanwang Zhang, Tat-Seng Chua: Attributed Social Network Embedding Paper, Code
  • Cheng Yang, Zhiyuan Liu, Deli Zhao, Maosong Sun, Edward Y. Chang: Network Representation Learning with Rich Text Information Paper, Code
  • Sambaran Bandyopadhyay, Harsh Kara, Aswin Kannan, M N Murty: Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks Paper, Code

Meta Node Embedding

  • Cheng Yang, Maosong Sun, Zhiyuan Liu, Cunchao Tu: Fast Network Embedding Enhancement via High Order Proximity Approximation Paper

Whole Graph Embedding

  • Lili Wang, Chenghan Huang, Weicheng Ma, Xinyuan Cao, Soroush Vosoughi: Graph Embedding via Diffusion-Wavelets-Based Node Feature Distribution Characterization Paper
  • Benedek Rozemberczki, Rik Sarkar: Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models Paper, Code
  • Chen Cai, Yusu Wang: A Simple Yet Effective Baseline for Non-Attributed Graph Classification Paper, Code
  • Alexis Galland, Marc Lelarge: Invariant Embedding for Graph Classification Paper, Code
  • Feng Gao, Guy Wolf, Matthew Hirn: Geometric Scattering for Graph Data Analysis Paper
  • Hong Chen, Hisashi Koga: GL2Vec: Graph Embedding Enriched by Line Graphs with Edge Features Paper
  • Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alex Bronstein, Emmanuel Müller: NetLSD: Hearing the Shape of a Graph Paper, Video
  • Nathan de Lara, Edouard Pineau: A Simple Baseline Algorithm for Graph Classification Paper
  • Saurabh Verma, Zhi-Li Zhang: Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs Paper
  • Annamalai Narayanan, Mahinthan Chandramohan, Rajasekar Venkatesan, Lihui Chen, Yang Liu, Shantanu Jaiswal: graph2vec: Learning Distributed Representations of Graphs Paper, Code