Node Classification On Citeseer 48 32 20
المقاييس
1:1 Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | 1:1 Accuracy |
|---|---|
| neural-sheaf-diffusion-a-topological | 76.70 ± 1.57 |
| neural-sheaf-diffusion-a-topological | 77.14 ± 1.85 |
| revisiting-heterophily-for-graph-neural | 77.12 ± 1.58 |
| large-scale-learning-on-non-homophilous | 73.19 ± 0.99 |
| non-local-graph-neural-networks | 75.2 ± 1.4 |
| mixhop-higher-order-graph-convolution | 76.26 ± 1.33 |
| joint-adaptive-feature-smoothing-and-topology | 77.13 ± 1.67 |
| revisiting-heterophily-for-graph-neural | 77.67 ± 1.19 |
| finding-global-homophily-in-graph-neural | 77.22 ± 1.78 |
| addressing-heterophily-in-node-classification | 74.51 ± 2.14 |
| two-sides-of-the-same-coin-heterophily-and | 77.14 ± 1.45 |
| revisiting-heterophily-for-graph-neural | 76.73 ± 1.59 |
| geom-gcn-geometric-graph-convolutional-1 | 78.02 ± 1.15 |
| finding-global-homophily-in-graph-neural | 77.41 ± 1.65 |
| revisiting-heterophily-for-graph-neural | 76.59 ± 1.69 |
| simple-and-deep-graph-convolutional-networks-1 | 77.33 ± 1.48 |
| beyond-low-frequency-information-in-graph | 77.07 ± 2.05 |
| non-local-graph-neural-networks | 76.2 ± 1.6 |
| breaking-the-limit-of-graph-neural-networks | 76.81 ± 1.89 |
| revisiting-heterophily-for-graph-neural | 77.2 ± 1.61 |
| neural-sheaf-diffusion-a-topological | 76.32 ± 1.65 |
| gread-graph-neural-reaction-diffusion | - |
| generalizing-graph-neural-networks-beyond | 77.11 ± 1.57 |
| revisiting-heterophily-for-graph-neural | 77.46 ± 1.65 |
| non-local-graph-neural-networks | 73.4 ± 1.9 |
| revisiting-heterophily-for-graph-neural | 77.15 ± 1.45 |