Research map / Graph learning / Graph algorithms and clustering
Dink-Net: Neural Clustering on Large Graphs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Adding the node discriminate module plus neural clustering module (full Dink-Net) vs. removing the node discriminate module (ablation) | Dink-Net · four ablation datasets (Figure) | clustering performance | Helped |
| Adding the neural clustering module (unifying representation learning and clustering) vs. removing it (ablation) | Dink-Net · four ablation datasets (Figure) | clustering performance | Helped |
| Replace whole-graph clustering optimization with mini-batch cluster dilation and shrink losses | Dink-Net · ogbn-papers100M | NMI: +9.62% NMI vs runner-up S3GC | Helped |
| Scale to mini-batch training with dilation/shrink losses | Dink-Net · Cora memory/time (Table 3) | GPU memory and time per run: 1248 MB vs S3GC 1474 MB; 35.09 s vs 508.21 s | Helped |
| Scalable mini-batch deep graph clustering vs. methods that process full N x N diffusion or whole-data KL clustering | Deep graph clustering baselines · Reddit and ogbn-papers100M | runnable (OOM) | Hurt |
| Adding a learned end-to-end clustering objective versus separating representation learning and clustering (S3GC) | Dink-Net · Cora ACC | ACC: 78.10 vs 74.20 (BGRL) baseline | Helped |
Closest papers by meaning
- DGCBench: A Deep Graph Clustering Benchmark (NeurIPS 2025 · similarity 0.90)
- LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering (ICML 2024 · similarity 0.88)
- DGCLUSTER: A Neural Framework for Attributed Graph Clustering via Modularity Maximization (AAAI 2024 · similarity 0.88)
- Deep Temporal Graph Clustering (ICLR 2024 · similarity 0.87)
- Deep Multi-modal Graph Clustering via Graph Transformer Network (AAAI 2025 · similarity 0.87)
- Deep Contrastive Graph Learning with Clustering-Oriented Guidance (AAAI 2024 · similarity 0.87)
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