Key papers

• Forced condensation and anti-condensation on heavy-tailed networks (2026)
  T. Ashwin Bhattathiripad et al.
  4.39
• Governing Well in the Algorithmic Age: The Foundations of Digital Statecraft (2026)
  Zeynep Engin et al.
  4.39
• A knowledge extrapolation model for attack inference based on graph attention networks and relation mapping (2026)
  Weiwu Ren et al.
  4.20
• Community Concealment from Unsupervised Graph Learning-Based Clustering (2026)
  Dalyapraz Manatova et al.
  1.72
• Adversarial Signed Graph Learning with Differential Privacy (2025)
  Haobin Ke et al.
  1.61
• Unsupervised Learning for the Elementary Shortest Path Problem (2025)
  Jingyi Chen et al.
  1.39
• Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation (2025)
  Yaowen Hu et al.
  1.33
• iN2V: Bringing Transductive Node Embeddings to Inductive Graphs (2025)
  Nicolas Lell et al.
  1.28
• Towards Unbiased Federated Graph Learning: Label and Topology Perspectives (2025)
  Zhengyu Wu et al.
  1.17
• Robust Deep Signed Graph Clustering via Weak Balance Theory (2025)
  Peiyao Zhao et al.
  1.06
• Mapping urban segregation through co-residence network reconstruction (2025)
  Marc Sadurn\'i et al.
  1.00
• RDSA: A Robust Deep Graph Clustering Framework via Dual Soft Assignment (2024)
  Yang Xiang et al.
  0.89
• Robustness of graph embedding methods for community detection (2024)
  Zhi-Feng Wei et al.
  0.61
• Mining Statistically Significant Attribute Associations in Attributed Graphs (2016)
  Jihwan Lee et al.
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• SNE: Signed Network Embedding (2017)
  Shuhan Yuan et al.
  —
• Attributed Social Network Embedding (2017)
  Lizi Liao et al.
  —
• Active Learning for Graph Embedding (2017)
  Hongyun Cai et al.
  —
• Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking (2017)
  Aleksandar Bojchevski et al.
  —
• Graph Embedding with Rich Information through Heterogeneous Network (2017)
  Guolei Sun et al.
  —
• GEMSEC: Graph Embedding with Self Clustering (2018)
  Benedek Rozemberczki et al.
  —
• Multi-View Network Embedding Via Graph Factorization Clustering and Co-Regularized Multi-View Agreement (2018)
  Yiwei Sun et al.
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• A simple yet effective baseline for non-attributed graph classification (2018)
  Chen Cai et al.
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• Node Embedding with Adaptive Similarities for Scalable Learning over Graphs (2018)
  Dimitris Berberidis and Georgios B. Giannakis
  —
• Attributed Network Embedding for Incomplete Attributed Networks (2018)
  Chengbin Hou et al.
  —
• GLEE: Geometric Laplacian Eigenmap Embedding (2019)
  Leo Torres et al.
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• Deep Hashing for Signed Social Network Embedding (2019)
  Jia-Nan Guo et al.
  —
• Benchmarks for Graph Embedding Evaluation (2019)
  Palash Goyal et al.
  —
• Parallel Computation of Graph Embeddings (2019)
  Chi Thang Duong et al.
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• Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks (2019)
  Guillaume Salha et al.
  —
• Collective Link Prediction Oriented Network Embedding with Hierarchical Graph Attention (2019)
  Yizhu Jiao et al.
  —
• Which way? Direction-Aware Attributed Graph Embedding (2020)
  Zekarias T. Kefato et al.
  —
• Novel Edge and Density Metrics for Link Cohesion (2020)
  Cetin Savkli et al.
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• Approximating Network Centrality Measures Using Node Embedding and Machine Learning (2020)
  Matheus R. F. Mendon\c{c}a et al.
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• Faster Graph Embeddings via Coarsening (2020)
  Matthew Fahrbach et al.
  —
• Integrating Network Embedding and Community Outlier Detection via Multiclass Graph Description (2020)
  Sambaran Bandyopadhyay et al.
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• Inductive Graph Embeddings through Locality Encodings (2020)
  Nurudin Alvarez-Gonzalez et al.
  —
• Joint Use of Node Attributes and Proximity for Semi-Supervised Classification on Graphs (2020)
  Arpit Merchant et al.
  —
• AttrE2vec: Unsupervised Attributed Edge Representation Learning (2020)
  Piotr Bielak et al.
  —
• NEMR: Network Embedding on Metric of Relation (2021)
  Luodi Xie et al.
  —
• Dual Side Deep Context-aware Modulation for Social Recommendation (2021)
  Bairan Fu and Wenming Zhang and Guangneng Hu and Xinyu Dai and Shujian Huang and Jiajun Chen
  —
• Scalable Hypergraph Embedding System (2021)
  Sepideh Maleki et al.
  —
• An efficient scheme based on graph centrality to select nodes for training for effective learning (2021)
  CR Sandeep et al.
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• One-Hot Graph Encoder Embedding (2021)
  Cencheng Shen et al.
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• Identifying and Mitigating Instability in Embeddings of the Degenerate Core (2022)
  David Liu et al.
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• Region2Vec: Community Detection on Spatial Networks Using Graph Embedding with Node Attributes and Spatial Interactions (2022)
  Yunlei Liang et al.
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• Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection (2023)
  Hezhe Qiao and Guansong Pang
  —
• Dual Node and Edge Fairness-Aware Graph Partition (2023)
  Tingwei Liu et al.
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• Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node Classification (2023)
  Arpit Merchant et al.
  —
• Privacy-Preserving Graph Embedding based on Local Differential Privacy (2023)
  Zening Li et al.
  —
• Heterophily-Aware Fair Recommendation using Graph Convolutional Networks (2024)
  Nemat Gholinejad and Mostafa Haghir Chehreghani
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• Robust Graph Structure Learning under Heterophily (2024)
  Xuanting Xie et al.
  —
• Towards Deeper Understanding of PPR-based Embedding Approaches: A Topological Perspective (2024)
  Xingyi Zhang et al.
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• Generating Human Understandable Explanations for Node Embeddings (2024)
  Zohair Shafi et al.
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• Weighted Embeddings for Low-Dimensional Graph Representation (2024)
  Thomas Bl\"asius et al.
  —
• Multi-Scale Node Embeddings for Graph Modeling and Generation (2024)
  Riccardo Milocco et al.
  —