mlsanityData to 7 Oct 2026

N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification

arXiv 1802.08888 ↗First posted 24 Feb 2018cs.LG cs.SI stat.MLcited by 54

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Abstract (arXiv)

Graph Convolutional Networks (GCNs) have shown significant improvements in semi-supervised learning on graph-structured data. Concurrently, unsupervised learning of graph embeddings has benefited from the information contained in random walks. In this paper, we propose a model: Network of GCNs (N-GCN), which marries these two lines of work. At its core, N-GCN trains multiple instances of GCNs over node pairs discovered at different distances in random walks, and learns a combination of the instance outputs which optimizes the classification objective. Our experiments show that our proposed N-GCN model improves state-of-the-art baselines on all of the challenging node classification tasks we consider: Cora, Citeseer, Pubmed, and PPI. In addition, our proposed method has other desirable properties, including generalization to recently proposed semi-supervised learning methods such as GraphSAGE, allowing us to propose N-SAGE, and resilience to adversarial input perturbations.

Key facts. Cited by 54 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Feb 2018.

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Citing papers per year: 2021: 17; 2022: 11; 2023: 14; 2024: 8; 2025: 4.

54 papers.

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  1. 2023DRew: Dynamically Rewired Message Passing with Delaycited by 81
  2. 2021Graph-based Semi-supervised Learning: A Comprehensive Reviewcited by 79
  3. 2023Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modelingcited by 63
  4. 2021Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depthcited by 55
  5. 2021Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentationcited by 47
  6. 2022Shortest Path Networks for Graph Property Predictioncited by 46
  7. 2021p-Laplacian Based Graph Neural Networkscited by 39
  8. 2021SPAGAN: Shortest Path Graph Attention Networkcited by 28
  9. 2021Topological Relational Learning on Graphscited by 27
  10. 2022MGNNI: Multiscale Graph Neural Networks with Implicit Layerscited by 19
  11. 2025Graph2text or Graph2token: A Perspective of Large Language Models for Graph Learningcited by 12
  12. 2023The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive fieldcited by 11
38 more
  1. 2024The Effectiveness of Curvature-Based Rewiring and the Role of Hyperparameters in GNNs Revisitedcited by 11
  2. 2021Boosting-GNN: Boosting Algorithm for Graph Networks on Imbalanced Node Classificationcited by 10
  3. 2021SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networkscited by 10
  4. 2022Towards Digital Twin Oriented Modelling of Complex Networked Systems and Their Dynamics: A Comprehensive Surveycited by 8
  5. 2023DRIN: Dynamic Relation Interactive Network for Multimodal Entity Linkingcited by 8
  6. 2024Redesigning graph filter-based GNNs to relax the homophily assumptioncited by 8
  7. 2021A Piece-wise Polynomial Filtering Approach for Graph Neural Networkscited by 7
  8. 2023Simplifying Subgraph Representation Learning for Scalable Link Predictioncited by 7
  9. 2023From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisitedcited by 6
  10. 2024The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphscited by 6
  11. 2021Multiscale Laplacian Learningcited by 5
  12. 2021Haar Wavelet Feature Compression for Quantized Graph Convolutional Networkscited by 5
  13. 2023A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospectscited by 5
  14. 2023Digital Twin-Oriented Complex Networked Systems based on Heterogeneous Node Features and Interaction Rulescited by 4
  15. 2024EMP: Effective Multidimensional Persistence for Graph Representation Learningcited by 4
  16. 2021SMASH: Sparse Matrix Atomic Scratchpad Hashingcited by 3
  17. 2022A Top-down Supervised Learning Approach to Hierarchical Multi-label Classification in Networkscited by 3
  18. 2024Simplified PCNet with Robustnesscited by 3
  19. 2024Enhancing the Resilience of Graph Neural Networks to Topological Perturbations in Sparse Graphscited by 3
  20. 2021HMSG: Heterogeneous Graph Neural Network based on Metapath Subgraph Learningcited by 2
  21. 2022Graph Neural Diffusion Networks for Semi-supervised Learningcited by 2
  22. 2022G3SR: Global Graph Guided Session-based Recommendationcited by 2
  23. 2022How Powerful is Implicit Denoising in Graph Neural Networkscited by 2
  24. 2022Demystifying Bitcoin Address Behavior via Graph Neural Networkscited by 2
  25. 2023Dual Policy Learning for Aggregation Optimization in Graph Neural Network-based Recommender Systemscited by 2
  26. 2023GANN: Graph Alignment Neural Network for Semi-Supervised Learningcited by 2
  27. 2023Benchmarking Machine Learning Models for Quantum Error Correctioncited by 2
  28. 2025Hybrid-Hierarchical Fashion Graph Attention Network for Compatibility-Oriented and Personalized Outfit Recommendationcited by 2
  29. 2021Relational Graph Neural Network Design via Progressive Neural Architecture Searchcited by 1
  30. 2021Dual GNNs: Graph Neural Network Learning with Limited Supervisioncited by 1
  31. 2022Hierarchy exploitation to detect missing annotations on hierarchical multi-label classificationcited by 1
  32. 2022GPNet: Simplifying Graph Neural Networks via Multi-channel Geometric Polynomialscited by 1
  33. 2023Renormalized Graph Representations for Node Classificationcited by 1
  34. 2023Torsion Graph Neural Networkscited by 1
  35. 2024ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networkscited by 1
  36. 2024Decoding Climate Disagreement: A Graph Neural Network-Based Approach to Understanding Social Media Dynamicscited by 1
  37. 2021Effective Eigendecomposition based Graph Adaptation for Heterophilic Networkscited by 0
  38. 2021RRLFSOR: An Efficient Self-Supervised Learning Strategy of Graph Convolutional Networkscited by 0

50 most cited of 54 All 54 (JSON)