mlsanityData to 7 Oct 2026

Learning Graph Representations with Embedding Propagation

arXiv 1710.03059 ↗First posted 9 Oct 2017cs.LGcited by 38

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Abstract (arXiv)

We propose Embedding Propagation (EP), an unsupervised learning framework for graph-structured data. EP learns vector representations of graphs by passing two types of messages between neighboring nodes. Forward messages consist of label representations such as representations of words and other attributes associated with the nodes. Backward messages consist of gradients that result from aggregating the label representations and applying a reconstruction loss. Node representations are finally computed from the representation of their labels. With significantly fewer parameters and hyperparameters an instance of EP is competitive with and often outperforms state of the art unsupervised and semi-supervised learning methods on a range of benchmark data sets.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Oct 2017.

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Citing papers per year: 2021: 15; 2022: 12; 2023: 5; 2024: 2; 2025: 4.

38 papers.

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  1. 2021Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gaugescited by 1,131
  2. 2022GraphMAE: Self-Supervised Masked Graph Autoencoderscited by 443
  3. 2021Large-Scale Representation Learning on Graphs via Bootstrappingcited by 184
  4. 2021Self-supervised Graph-level Representation Learning with Local and Global Structurecited by 125
  5. 2023Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modelingcited by 63
  6. 2021Local Augmentation for Graph Neural Networkscited by 52
  7. 2022Heterogeneous Graph Masked Autoencoderscited by 47
  8. 2021SDGNN: Learning Node Representation for Signed Directed Networkscited by 44
  9. 2022Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNNcited by 34
  10. 2022Dynamic-Group-Aware Networks for Multi-Agent Trajectory Prediction with Relational Reasoningcited by 28
  11. 2022Fair Node Representation Learning via Adaptive Data Augmentationcited by 27
  12. 2021Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspectivecited by 23
26 more
  1. 2023SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Maskingcited by 23
  2. 2021Predicting Patient Outcomes with Graph Representation Learningcited by 21
  3. 2021TC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUscited by 17
  4. 2022MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platformscited by 16
  5. 2021Fairness-Aware Node Representation Learningcited by 14
  6. 2022Learning Graph Augmentations to Learn Graph Representationscited by 14
  7. 2022Graph Contrastive Learning with Personalized Augmentationcited by 14
  8. 2023FairGAT: Fairness-aware Graph Attention Networkscited by 12
  9. 2021BlockGNN: Towards Efficient GNN Acceleration Using Block-Circulant Weight Matricescited by 11
  10. 2022Geometric Graph Representation Learning via Maximizing Rate Reductioncited by 9
  11. 2021Communication-Efficient Sampling for Distributed Training of Graph Convolutional Networkscited by 7
  12. 2021GNNear: Accelerating Full-Batch Training of Graph Neural Networks with Near-Memory Processingcited by 6
  13. 2022Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learningcited by 5
  14. 2021Computing Graph Descriptors on Edge Streamscited by 4
  15. 2022Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspectivecited by 4
  16. 2023PiPAD: Pipelined and Parallel Dynamic GNN Training on GPUscited by 4
  17. 2023A Contrastive Variational Graph Auto-Encoder for Node Clusteringcited by 4
  18. 2021Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learningcited by 2
  19. 2022DGI: Easy and Efficient Inference for GNNscited by 2
  20. 2024UGMAE: A Unified Framework for Graph Masked Autoencoderscited by 2
  21. 2025AirRadar: Inferring Nationwide Air Quality in China with Deep Neural Networkscited by 2
  22. 2025BIGNet: Pretrained Graph Neural Network for Embedding Semantic, Spatial, and Topological Data in BIM Modelscited by 2
  23. 2024ExGRG: Explicitly-Generated Relation Graph for Self-Supervised Representation Learningcited by 1
  24. 2025Libra: Unleashing GPU Heterogeneity for High-Performance Sparse Matrix Multiplicationcited by 1
  25. 2021Interferometric Graph Transform for Community Labelingcited by 0
  26. 2025Fast online node labeling with graph subsamplingcited by 0