mlsanityData to 7 Oct 2026

Hyperbolic Heterogeneous Graph Attention Networks

arXiv 2404.09456 ↗First posted 15 Apr 2024cs.LGcited by 5

Not on the map. Why?

Abstract (arXiv)

Most previous heterogeneous graph embedding models represent elements in a heterogeneous graph as vector representations in a low-dimensional Euclidean space. However, because heterogeneous graphs inherently possess complex structures, such as hierarchical or power-law structures, distortions can occur when representing them in Euclidean space. To overcome this limitation, we propose Hyperbolic Heterogeneous Graph Attention Networks (HHGAT) that learn vector representations in hyperbolic spaces with meta-path instances. We conducted experiments on three real-world heterogeneous graph datasets, demonstrating that HHGAT outperforms state-of-the-art heterogeneous graph embedding models in node classification and clustering tasks.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 10 of its 14 references that are in the map. First posted on arXiv 15 Apr 2024.

Builds on

10 of 14 references.

References · 10

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  2. 2017Graph Attention Networkscited by 8,854
  3. 2019Heterogeneous Graph Attention Networkcited by 732
  4. 2020Heterogeneous Graph Transformercited by 581
  5. 2019Graph Transformer Networkscited by 520
  6. 2019Hyperbolic Graph Convolutional Neural Networkscited by 400
  7. 2020MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embeddingcited by 304
  8. 2021Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networkscited by 176
  9. 2019An Attention-based Graph Neural Network for Heterogeneous Structural Learningcited by 71
  10. 2021Embedding Heterogeneous Networks into Hyperbolic Space Without Meta-pathcited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 2.

5 papers.

  1. 2024Non-Euclidean Mixture Model for Social Network Embeddingcited by 4
  2. 2024Multi-Hyperbolic Space-based Heterogeneous Graph Attention Networkcited by 2
  3. 2025Metapath-based Hyperbolic Contrastive Learning for Heterogeneous Graph Embeddingcited by 0
  4. 2026Hyperbolic Heterogeneous Graph Transformercited by 0
  5. 2026GCN-MPPR: Enhancing the Propagation of Message Passing Neural Networks via Motif-Based Personalized PageRankcited by 0