mlsanityData to 7 Oct 2026

Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network

arXiv 2202.09177 ↗First posted 18 Feb 2022cs.LG cs.AIcited by 8

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Abstract (arXiv)

Heterogeneous Graph Neural Network (HGNN) has been successfully employed in various tasks, but we cannot accurately know the importance of different design dimensions of HGNNs due to diverse architectures and applied scenarios. Besides, in the research community of HGNNs, implementing and evaluating various tasks still need much human effort. To mitigate these issues, we first propose a unified framework covering most HGNNs, consisting of three components: heterogeneous linear transformation, heterogeneous graph transformation, and heterogeneous message passing layer. Then we build a platform Space4HGNN by defining a design space for HGNNs based on the unified framework, which offers modularized components, reproducible implementations, and standardized evaluation for HGNNs. Finally, we conduct experiments to analyze the effect of different designs. With the insights found, we distill a condensed design space and verify its effectiveness.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 38 of its 63 references that are in the map. First posted on arXiv 18 Feb 2022.

Builds on

38 of 63 references.

References · 38

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  3. 2017Graph Attention Networkscited by 8,854
  4. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 6,979
  5. 2016Densely Connected Convolutional Networkscited by 6,691
  6. 2017Inductive Representation Learning on Large Graphscited by 6,284
  7. 2018How Powerful are Graph Neural Networks?cited by 4,355
  8. 2017Neural Message Passing for Quantum Chemistrycited by 3,460
  9. 2017Modeling Relational Data with Graph Convolutional Networkscited by 1,684
  10. 2018Pitfalls of Graph Neural Network Evaluationcited by 994
  11. 2020Designing Network Design Spacescited by 954
  12. 2018Representation Learning on Graphs with Jumping Knowledge Networkscited by 875
26 more
  1. 2020Geom-GCN: Geometric Graph Convolutional Networkscited by 821
  2. 2019Heterogeneous Graph Attention Networkcited by 732
  3. 2019Graph Neural Networks for Social Recommendationcited by 711
  4. 2020Benchmarking Graph Neural Networkscited by 672
  5. 2019Neural Graph Collaborative Filteringcited by 660
  6. 2020Heterogeneous Graph Transformercited by 581
  7. 2019DeepGCNs: Can GCNs Go as Deep as CNNs?cited by 527
  8. 2019Graph Transformer Networkscited by 520
  9. 2020MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embeddingcited by 304
  10. 2019A Fair Comparison of Graph Neural Networks for Graph Classificationcited by 244
  11. 2020Design Space for Graph Neural Networkscited by 182
  12. 2019Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approachescited by 181
  13. 2021Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networkscited by 176
  14. 2020A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sourcescited by 126
  15. 2021Sequential Recommendation with Graph Neural Networkscited by 89
  16. 2019An Attention-based Graph Neural Network for Heterogeneous Structural Learningcited by 71
  17. 2019On Network Design Spaces for Visual Recognitioncited by 68
  18. 2019GraphNAS: Graph Neural Architecture Search with Reinforcement Learningcited by 41
  19. 2020DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networkscited by 34
  20. 2020Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous Viewcited by 30
  21. 2020Bundle Recommendation with Graph Convolutional Networkscited by 24
  22. 2019IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendationcited by 19
  23. 2020A Heterogeneous Information Network based Cross Domain Insurance Recommendation System for Cold Start Userscited by 14
  24. 2020Hybrid Micro/Macro Level Convolution for Heterogeneous Graph Learningcited by 9
  25. 2018Cross-language Citation Recommendation via Hierarchical Representation Learning on Heterogeneous Graphcited by 6
  26. 2020Heterogeneous Graph Collaborative Filteringcited by 3

Built on by

Cited by year

Citing papers per year: 2023: 6; 2024: 2.

8 papers.

  1. 2023HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformercited by 35
  2. 2023Homophily-oriented Heterogeneous Graph Rewiringcited by 18
  3. 2024SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Networkcited by 11
  4. 2024Heterogeneous Sheaf Neural Networkscited by 10
  5. 2023Link Prediction on Latent Heterogeneous Graphscited by 5
  6. 2023HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networkscited by 4
  7. 2023Long-range Meta-path Search on Large-scale Heterogeneous Graphscited by 4
  8. 2023Beyond Prediction: On-street Parking Recommendation using Heterogeneous Graph-based List-wise Rankingcited by 1