Hypergraph Neural Networks

Overview

Hypergraph neural networks study how to learn from data where one relationship can connect several entities at once, such as a group of brain regions, items, or clinical concepts. Common approaches propagate messages through node–hyperedge incidence, use attention or spectral operators, and increasingly add dynamic hypergraphs, diffusion models, or self-supervised learning. They are applied to tasks including node classification, recommendation, forecasting, medical analysis, and scientific modeling, with evaluations spanning standard hypergraph benchmarks and domain-specific datasets. A central open question is whether gains come from genuine higher-order information rather than stronger propagation or other modeling choices; efficiency, over-smoothing, heterophily, and incomplete or noisy structure also remain challenges.

Latest papers

CardsList

58 papers7 papers in the last four weeks, down 30% on the four weeks before. 0.0% of all new papers.

  1. PANDA: Prior-guided Attentional Dual-path Architecture

    Oct 9, 2026Rishabh Jain, Federico Belotti, Stefano Coniglio +2Hypergraph Neural NetworksHigher-Order GNNs

  2. Interpretable Hypergraph Learning via Neural Additive Models

    Oct 5, 2026Shihan Feng, Xin Zheng, Shiyi Yang +3Neural Network InterpretabilityHypergraph Neural Networks

  3. HyperFuse: Fast Self-Supervised Node Embeddings for Attributed Hypergraphs

    Oct 2, 2026Megha P, Harshit Kumar, Srajan Agarwal +3Hypergraph LearningHypergraph Neural Networks

  4. Spatiotemporal Hyperedges for EEG Seizure Detection and Prediction

    Sep 29, 2026Hyunju Kim, Sheo Yon Jhin, Noseong Park +1EEG Seizure DetectionGraph Neural Networks

  5. AutoHGNN: Robust and Efficient Neural Architecture Search for Hypergraph Neural Networks

    Sep 27, 2026Sirui Li, Pietro Liò b, Xinsheng Li +2Hypergraph Neural NetworksNeural Architecture Search

  6. CalibHyper: Chance-Corrected Relational Hypergraphs for Few-Shot Molecular Property Prediction

    Sep 27, 2026Linyu Li, Zhi Jin, Yuanpeng He +7Multi-Label ClassificationFew-Shot Learning

  7. HyperReCo: Retrieving and Connecting Evidence with Hypergraph Neural Networks for LLM Multi-hop Reasoning

    Sep 26, 2026Zicheng Zhao, Linhao Luo, Junnan Dong +4Graph Retrieval-Augmented GenerationMulti-Hop QA

  8. HyperAMS-Net: Adaptive Multi-Scale Spatial Hypergraph Network for Brain Disorder Classification

    Sep 17, 2026Proloy Kumar Mondal, Md Kamran Hussin Chowdhury, Hoi Leong LeeMedical DiagnosisMulti-Scale Feature Fusion

  9. Hypergraph-Regularized Gramian Volumes for Multimodal Retrieval

    Sep 14, 2026Anindya Nag, Ambuj Mehrish, Sebastiano VasconMultimodal IRCross-Modal Alignment

  10. Multi-granularity Adaptive Hypergraph Representation Learning via Granular-ball

    Sep 4, 2026Sen Zhao, Yifan Guan, Jinyuan Ni +6Hypergraph LearningHypergraph Neural Networks

  11. H2Table: Hierarchical Hypergraph-Enhanced Large Language Models for Complex Table Reasoning

    Sep 1, 2026Jia Ling, Yangfan Wang, Chen Tang +4Table QAHierarchical Representation Learning

  12. Why Multi-Layer Message Passing Works: Completeness Theory for Graph Neural Network Interatomic Potentials

    Sep 1, 2026Pingbing Ming, Han WangMachine Learning Interatomic PotentialsGNN Expressivity

  13. Higher Structures in Deep Learning

    Aug 31, 2026Michael L. Roberts, Carlos Zapata Carratalá. Nicholas J. Cooper, Lijun Chen +2Multilayer PerceptronsHypergraph Neural Networks

  14. Hyper-Fold: Exploring the Expressive Limit of Sequence-Geometry Learning for Proteins via Hypergraph Modeling

    Aug 29, 2026Yifan Feng, Guanjie Cheng, Shihui Ying +2Protein Function PredictionHypergraph Neural Networks

  15. Beyond Pairwise Graphs in Science: Hypergraph Adaptive Wavelet Operators for Parametric PDEs

    Aug 28, 2026Rajat Sarkar, Venkataramana Runkana, Souvik ChakrabortyPDE Operator LearningHypergraph Neural Networks

  16. Towards Trustworthy Hypergraph Neural Networks under Label Noise

    Aug 5, 2026Mengyao Zhou, Zhiheng Zhou, Xiao Han +1Graph Structure LearningHypergraph Neural Networks

  17. FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model

    Jul 28, 2026Tresor Y. Koffi, Youssef Mourchid, Yohan DupuisFall DetectionHypergraph Neural Networks

  18. MissHyper: Restoring Clinical Synchronicity in Missingness-Guided Hypergraph Forecasting

    Jul 24, 2026Mingyi Ma, Qingxiong TanIrregular Time-Series ModelingMultivariate Time Series Forecasting

  19. AUCH-Net: Action Unit-Based Consistency-Aware Hypergraph Network for Cross-Domain Few-Shot Facial Expression Recognition

    Jul 23, 2026Xinhan Qiu, Yan Yan, Rui Zhu +2Few-Shot LearningCross-Domain Transfer Learning

  20. Spectral Higher-Order Neural Networks Have Sharp Expressivity Bounds

    Jul 21, 2026Gianluca Peri, Diego Febbe, Duccio FanelliHypergraph Neural NetworksNeural Network Expressivity

  21. From Diffusion to Reaction-Diffusion: A Dynamical-Systems View of Oversmoothing in Hypergraph Neural Networks

    Jul 17, 2026Zhiheng Zhou, Mengyao Zhou, Yancheng Chen +3Hypergraph Neural NetworksHypergraph Learning

  22. Dynamic Manipulation Hypergraphs for HAR: Beyond Pairwise Relations: Dynamic Manipulation Hypergraphs for Vision-Based Human Activity Recognition

    Jul 15, 2026Fatemeh ZiaeetabarHuman Activity RecognitionHypergraph Neural Networks

  23. Dual-Correlation Hypergraph Network for Unaligned RGBT Video Object Detection and A Large-scale Benchmark

    Jul 9, 2026Qishun Wang, Yapeng Li, Zhengzheng Tu +2Cross-Modal AlignmentVideo Object Detection

  24. Hypergraph Neural Stochastic Diffusion: An SDE Framework for Uncertainty Estimation

    Jul 8, 2026Zhiheng Zhou, Mengyao Zhou, Dengyi Zhao +2Stochastic Differential EquationsUncertainty Quantification

  25. SABER: A Semantic-Aligned Brain Network Analysis Framework via Multi-scale Hypergraphs

    Jul 2, 2026Yidan Xu, Xiangmin Han, Rundong Xue +1Medical DiagnosisHypergraph Neural Networks

  26. EHHN: An Event-driven Heterogeneous Hypergraph Network for Object-Centric Next Activity Prediction

    Jul 2, 2026Jiaxing Wang, Kaitao Chen, Zhubin Han +4Temporal GNNsProcess Mining