Node Classification On Reddit
المقاييس
Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | Accuracy |
|---|---|
| decoupling-the-depth-and-scope-of-graph-1 | 97.03% |
| bns-gcn-efficient-full-graph-training-of | 97.17% |
| fastgcn-fast-learning-with-graph | 93.70% |
| a-comprehensive-study-on-large-scale-graph | 96.65% |
| communication-free-distributed-gnn-training | 97.14±0.02% |
| adaptive-sampling-towards-fast-graph | 96.27% |
| tackling-oversmoothing-of-gnns-with-1 | 81.06±1.18% |
| inductive-representation-learning-on-large | 94.32% |
| simple-spectral-graph-convolution | 95.3 |
| sign-scalable-inception-graph-neural-networks | 96.60% |
| deep-graph-contrastive-representation | - |
| graphsaint-graph-sampling-based-inductive | 97.0% |
| the-truly-deep-graph-convolutional-networks | 97.02% |
| vq-gnn-a-universal-framework-to-scale-up | 94.5 ± .0024 |
| dimensionality-reduction-meets-message | 96.26 ± 0.02% |
| decoupling-the-depth-and-scope-of-graph-1 | 97.13% |