mlsanityData to 13 Oct 2026

A Hypergraph Neural Network Framework for Learning Hyperedge-Dependent Node Embeddings

arXiv 2212.14077 ↗First posted 28 Dec 2022cs.LG cs.DM cs.SIcited by 9

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Abstract (arXiv)

In this work, we introduce a hypergraph representation learning framework called Hypergraph Neural Networks (HNN) that jointly learns hyperedge embeddings along with a set of hyperedge-dependent embeddings for each node in the hypergraph. HNN derives multiple embeddings per node in the hypergraph where each embedding for a node is dependent on a specific hyperedge of that node. Notably, HNN is accurate, data-efficient, flexible with many interchangeable components, and useful for a wide range of hypergraph learning tasks. We evaluate the effectiveness of the HNN framework for hyperedge prediction and hypergraph node classification. We find that HNN achieves an overall mean gain of 7.72% and 11.37% across all baseline models and graphs for hyperedge prediction and hypergraph node classification, respectively.

Key facts. Cited by 9 papers in the map (data through 13 Oct 2026). Builds on 36 of its 80 references that are in the map. First posted on arXiv 28 Dec 2022.

Builds on

36 of 80 references.

References · 36

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,318
  2. 2019A Comprehensive Survey on Graph Neural Networkscited by 2,911
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  9. 2019Hypergraph Convolution and Hypergraph Attentioncited by 227
  10. 2017struc2vec: Learning Node Representations from Structural Identitycited by 214
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24 more
  1. 2021You are AllSet: A Multiset Function Framework for Hypergraph Neural Networkscited by 126
  2. 2020HNHN: Hypergraph Networks with Hyperedge Neuronscited by 108
  3. 2020Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendationcited by 75
  4. 2017Graph Convolutional Encoders for Syntax-aware Neural Machine Translationcited by 70
  5. 2022Hypergraph Contrastive Collaborative Filteringcited by 63
  6. 2020HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphscited by 54
  7. 2020Heterogeneous Hypergraph Embedding for Graph Classificationcited by 52
  8. 2019Random Walks on Hypergraphs with Edge-Dependent Vertex Weightscited by 45
  9. 2018Attention Models in Graphs: A Surveycited by 41
  10. 2022Graph Neural Networks Designed for Different Graph Types: A Surveycited by 21
  11. 2021Hierarchical Hyperedge Embedding-based Representation Learning for Group Recommendationcited by 17
  12. 2021Learnable Hypergraph Laplacian for Hypergraph Learningcited by 16
  13. 2022Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphscited by 15
  14. 2021Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networkscited by 13
  15. 2022HEAT: Hyperedge Attention Networkscited by 13
  16. 2021A nonlinear diffusion method for semi-supervised learning on hypergraphscited by 11
  17. 2017Classification in biological networks with hypergraphlet kernelscited by 9
  18. 2018Higher-order Graph Convolutional Networkscited by 8
  19. 2021Principled Hyperedge Prediction with Structural Spectral Features and Neural Networkscited by 7
  20. 2022Deep Hypergraph Structure Learningcited by 7
  21. 2017Deep Feature Learning for Graphscited by 6
  22. 2021Inhomogeneous Social Recommendation with Hypergraph Convolutional Networkscited by 4
  23. 2021Motifs-based Recommender System via Hypergraph Convolution and Contrastive Learningcited by 3
  24. 2020Learning with Molecules beyond Graph Neural Networkscited by 1

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2023: 4; 2024: 3; 2025: 1; 2026: 1.

9 papers.

  1. 2023From Hypergraph Energy Functions to Hypergraph Neural Networkscited by 17
  2. 2023Classification of Edge-dependent Labels of Nodes in Hypergraphscited by 14
  3. 2023Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture Designcited by 13
  4. 2023Molecular Hypergraph Neural Networkscited by 7
  5. 2024Ada-HGNN: Adaptive Sampling for Scalable Hypergraph Neural Networkscited by 4
  6. 2024Demystifying Higher-Order Graph Neural Networkscited by 4
  7. 2024Modeling Edge-Specific Node Features through Co-Representation Neural Hypergraph Diffusioncited by 2
  8. 2025Identifying Group Anchors in Real-World Group Interactions Under Label Scarcitycited by 0
  9. 2026Hypergraph Neural Stochastic Diffusion: An SDE Framework for Uncertainty Estimationcited by 0