Node Classification On Cora 48 32 20 Fixed
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 | 87.30 ± 1.15 |
| non-local-graph-neural-networks | 88.5 ± 1.8 |
| revisiting-heterophily-for-graph-neural | 88.01 ± 1.08 |
| geom-gcn-geometric-graph-convolutional-1 | 85.35 ± 1.57 |
| revisiting-heterophily-for-graph-neural | 88.19 ± 1.17 |
| addressing-heterophily-in-node-classification | 86.04 ± 1.01 |
| revisiting-heterophily-for-graph-neural | 86.9 ± 1.38 |
| two-sides-of-the-same-coin-heterophily-and | 87.95 ± 1.05 |
| joint-adaptive-feature-smoothing-and-topology | 87.95 ± 1.18 |
| revisiting-heterophily-for-graph-neural | 87.69 ± 1.07 |
| neural-sheaf-diffusion-a-topological | 86.90 ± 1.13 |
| gread-graph-neural-reaction-diffusion | - |
| revisiting-heterophily-for-graph-neural | 88.11 ± 0.96 |
| non-local-graph-neural-networks | 88.1 ± 1.0 |
| large-scale-learning-on-non-homophilous | 84.64 ± 1.13 |
| revisiting-heterophily-for-graph-neural | 88.25 ± 0.96 |
| generalizing-graph-neural-networks-beyond | 87.87 ± 1.20 |
| finding-global-homophily-in-graph-neural | 88.33 ± 1.09 |
| finding-global-homophily-in-graph-neural | 88.31 ± 1.13 |
| non-local-graph-neural-networks | 76.9 ± 1.8 |
| beyond-low-frequency-information-in-graph | 88.05 ± 1.57 |
| simple-and-deep-graph-convolutional-networks-1 | 88.37 ± 1.25 |
| mixhop-higher-order-graph-convolution | 87.61 ± 0.85 |
| breaking-the-limit-of-graph-neural-networks | 88.20 ± 2.26 |
| neural-sheaf-diffusion-a-topological | 87.14 ± 1.06 |
| revisiting-heterophily-for-graph-neural | 88.05 ± 0.99 |