Node Classification On Citeseer 1
المقاييس
Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | Accuracy |
|---|---|
| convolutional-networks-on-graphs-for-learning | 54.3% |
| gated-graph-sequence-neural-networks | 56.0% |
| break-the-ceiling-stronger-multi-scale-deep | 69.03% |
| lanczosnet-multi-scale-deep-graph | 63.3 ± 1.8 |
| break-the-ceiling-stronger-multi-scale-deep | 64.23% |
| graph-attention-networks | 46.5% |
| break-the-ceiling-stronger-multi-scale-deep | 67.07% |
| diffusion-convolutional-neural-networks | 62.2% |
| lanczosnet-multi-scale-deep-graph | 61.3 ± 3.9 |
| break-the-ceiling-stronger-multi-scale-deep | 65.85% |
| mutual-teaching-for-graph-convolutional | 68.9% |
| inductive-representation-learning-on-large | 51.0% |
| view-consistent-heterogeneous-network-on | 70.1% |
| convolutional-neural-networks-on-graphs-with | 59.4% |