One paper has been accepted by IEEE TPAMI 🎉

Title: Hypergraph Neural Networks: Theoretical Foundations and Applications

Authors: Yue Gao, Yifan Feng, Xiangmin Han, Shihui Ying, Juan Wang, and Shaoyi Du

Our comprehensive review has been accepted for publication in IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI) (Gao et al., 2026).

In this paper, we systematically present the theoretical foundations of hypergraph neural networks and provide a detailed overview of their principal methodological paradigms. We further review how hypergraph neural networks are developed and applied across computer vision, brain network analysis, and computational pathology, connecting higher-order representation learning with domain-specific modeling strategies.

Applications of hypergraph neural networks in phenotype ontology, interaction prediction, computational pathology, and brain network analysis

References

IEEE TPAMI

Hypergraph Neural Networks: Theoretical Foundations and Applications

Yue Gao, Yifan Feng, Xiangmin Han, Shihui Ying, Juan Wang, and Shaoyi Du

IEEE Transactions on Pattern Analysis and Machine Intelligence, Sep 2026

Accepted for publication

Bib

@article{gao2026hgnn-foundations,
  title = {Hypergraph Neural Networks: Theoretical Foundations and Applications},
  author = {Gao, Yue and Feng, Yifan and Han, Xiangmin and Ying, Shihui and Wang, Juan and Du, Shaoyi},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2026},
  month = sep,
  note = {Accepted for publication},
}