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HNHN: Hypergraph Networks with Hyperedge Neurons

arXiv 2006.12278 ↗First posted 22 Jun 2020cs.LG stat.MLcited by 104

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Abstract (arXiv)

Hypergraphs provide a natural representation for many real world datasets. We propose a novel framework, HNHN, for hypergraph representation learning. HNHN is a hypergraph convolution network with nonlinear activation functions applied to both hypernodes and hyperedges, combined with a normalization scheme that can flexibly adjust the importance of high-cardinality hyperedges and high-degree vertices depending on the dataset. We demonstrate improved performance of HNHN in both classification accuracy and speed on real world datasets when compared to state of the art methods.

Key facts. Cited by 104 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Jun 2020.

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Citing papers per year: 2021: 9; 2022: 10; 2023: 17; 2024: 23; 2025: 25; 2026: 20.

104 papers.

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  1. 2021You are AllSet: A Multiset Function Framework for Hypergraph Neural Networkscited by 124
  2. 2022Equivariant Hypergraph Diffusion Neural Operatorscited by 45
  3. 2023Architectures of Topological Deep Learning: A Survey of Message-Passing Topological Neural Networkscited by 43
  4. 2023Sheaf Hypergraph Networkscited by 33
  5. 2024TopoBench: A Framework for Benchmarking Topological Deep Learningcited by 24
  6. 2024A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guidecited by 22
  7. 2022I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphscited by 20
  8. 2022Preventing Over-Smoothing for Hypergraph Neural Networkscited by 19
  9. 2021Characterization Multimodal Connectivity of Brain Network by Hypergraph GAN for Alzheimer's Disease Analysiscited by 18
  10. 2023From Hypergraph Energy Functions to Hypergraph Neural Networkscited by 17
  11. 2021Learnable Hypergraph Laplacian for Hypergraph Learningcited by 16
  12. 2022Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphscited by 15
38 more
  1. 2024HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphscited by 15
  2. 2024Topological Neural Networks go Persistent, Equivariant, and Continuouscited by 15
  3. 2022Equivariant Hypergraph Neural Networkscited by 14
  4. 2023Classification of Edge-dependent Labels of Nodes in Hypergraphscited by 14
  5. 2021Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networkscited by 13
  6. 2023Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture Designcited by 13
  7. 2022AHP: Learning to Negative Sample for Hyperedge Predictioncited by 12
  8. 2021A nonlinear diffusion method for semi-supervised learning on hypergraphscited by 11
  9. 2021DecGAN: Decoupling Generative Adversarial Network detecting abnormal neural circuits for Alzheimer's diseasecited by 11
  10. 2025HyperG: Hypergraph-Enhanced LLMs for Structured Knowledgecited by 11
  11. 2021Adaptive Neural Message Passing for Inductive Learning on Hypergraphscited by 10
  12. 2022A Survey on Hyperlink Predictioncited by 9
  13. 2022A Hypergraph Neural Network Framework for Learning Hyperedge-Dependent Node Embeddingscited by 9
  14. 2021Principled Hyperedge Prediction with Structural Spectral Features and Neural Networkscited by 7
  15. 2023ICML 2023 Topological Deep Learning Challenge : Design and Resultscited by 7
  16. 2023Hypergraph Transformer for Semi-Supervised Classificationcited by 7
  17. 2024Training-Free Message Passing for Learning on Hypergraphscited by 7
  18. 2024HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphscited by 7
  19. 2024DE-HNN: An effective neural model for Circuit Netlist representationcited by 7
  20. 2024GraphBPE: Molecular Graphs Meet Byte-Pair Encodingcited by 7
  21. 2025Recent Advances in Hypergraph Neural Networkscited by 7
  22. 2024From Graphs to Hypergraphs: Hypergraph Projection and its Remediationcited by 6
  23. 2024LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100× Faster Inferencecited by 5
  24. 2025Hypergraph Foundation Modelcited by 5
  25. 2025DHG-Bench: A Comprehensive Benchmark for Deep Hypergraph Learningcited by 5
  26. 2023UniG-Encoder: A Universal Feature Encoder for Graph and Hypergraph Node Classificationcited by 4
  27. 2024Temporal Graph Networks for Graph Anomaly Detection in Financial Networkscited by 4
  28. 2024Ada-HGNN: Adaptive Sampling for Scalable Hypergraph Neural Networkscited by 4
  29. 2024Demystifying Higher-Order Graph Neural Networkscited by 4
  30. 2025HyperGCL: Multi-Modal Graph Contrastive Learning via Learnable Hypergraph Viewscited by 4
  31. 2023CHGNN: A Semi-Supervised Contrastive Hypergraph Learning Networkcited by 3
  32. 2024DPHGNN: A Dual Perspective Hypergraph Neural Networkscited by 3
  33. 2024SPHINX: Structural Prediction using Hypergraph Inference Networkcited by 3
  34. 2025HyGEN: Regularizing Negative Hyperedge Generation for Accurate Hyperedge Predictioncited by 3
  35. 2025Inductive Link Prediction on N-ary Relational Facts via Semantic Hypergraph Reasoningcited by 3
  36. 2025Hypergraph Neural Sheaf Diffusion: A Symmetric Simplicial Set Framework for Higher-Order Learningcited by 3
  37. 2025Implicit Hypergraph Neural Networks: A Stable Framework for Higher-Order Relational Learning with Provable Guaranteescited by 3
  38. 2022A Simple Hypergraph Kernel Convolution based on Discounted Markov Diffusion Processcited by 2

50 most cited of 104 All 104 (JSON)