Research map / Graph learning / Graph algorithms and clustering
Hard Sample Aware Network for Contrastive Deep Graph Clustering
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use HSAN instead of the strongest ACC baseline | Deep graph clustering · CORA | ACC: 77.07±1.56 vs 73.50±1.83 | Helped |
| Use HSAN instead of the strongest ACC baseline | Deep graph clustering · CITE | ACC: 71.15±0.80 vs 70.86±0.18 | Helped |
| Use HSAN instead of the strongest ACC baseline | Deep graph clustering · AMAP | ACC: 77.02±0.33 vs 76.82±0.23 | Helped |
| Use HSAN instead of the strongest ACC baseline | Deep graph clustering · BAT | ACC: 77.15±0.72 vs 67.94±1.45 | Helped |
| Use HSAN instead of the strongest ACC baseline | Deep graph clustering · EAT | ACC: 56.69±0.34 vs 52.13±0.00 | Helped |
| Use HSAN instead of the strongest ACC baseline | Deep graph clustering · UAT | ACC: 56.04±0.67 vs 52.37±0.42 | Helped |
| Add attribute-structure similarity to the baseline (ablation) | HSAN · Six benchmark datasets | Clustering performance | Helped |
| Add dynamic sample weighting to the baseline (ablation) | HSAN · Six benchmark datasets | Clustering performance | Helped |
| Add both attribute-structure similarity and dynamic sample weighting (ablation) | HSAN · CORA | NMI: 8.48 % | Helped |
| Increase the focusing factor β (ablation) | HSAN · Experiments analyzed in Appendix | Clustering performance | No clear effect |
Closest papers by meaning
- Hybrid-Collaborative Augmentation and Contrastive Sample Adaptive-Differential Awareness for Robust Attributed Graph Clustering (NeurIPS 2025 · similarity 0.88)
- Deep Contrastive Graph Learning with Clustering-Oriented Guidance (AAAI 2024 · similarity 0.88)
- THESAURUS: Contrastive Graph Clustering by Swapping Fused Gromov-Wasserstein Couplings (AAAI 2025 · similarity 0.88)
- Attribute-Missing Graph Clustering Network (AAAI 2024 · similarity 0.87)
- Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation (ICML 2025 · similarity 0.87)
- DGCLUSTER: A Neural Framework for Attributed Graph Clustering via Modularity Maximization (AAAI 2024 · similarity 0.86)
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