Node Classification On Pubmed 48 32 20 Fixed
المقاييس
1:1 Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
اسم النموذج | 1:1 Accuracy |
---|---|
simple-and-deep-graph-convolutional-networks-1 | 90.15 ± 0.43 |
finding-global-homophily-in-graph-neural | 89.62 ± 0.35 |
neural-sheaf-diffusion-a-topological | 89.42 ± 0.43 |
non-local-graph-neural-networks | 88.2 ± 0.3 |
revisiting-heterophily-for-graph-neural | 89.78 ± 0.49 |
revisiting-heterophily-for-graph-neural | 89.82 ± 0.41 |
mixhop-higher-order-graph-convolution | 85.31 ± 0.61 |
neural-sheaf-diffusion-a-topological | 89.33 ± 0.35 |
finding-global-homophily-in-graph-neural | 89.24 ± 0.39 |
neural-sheaf-diffusion-a-topological | 89.49 ± 0.40 |
revisiting-heterophily-for-graph-neural | 89.65 ± 0.58 |
revisiting-heterophily-for-graph-neural | 89.01 ± 0.6 |
breaking-the-limit-of-graph-neural-networks | 88.52 ± 0.92 |
large-scale-learning-on-non-homophilous | 87.86 ± 0.77 |
two-sides-of-the-same-coin-heterophily-and | 89.15 ± 0.37 |
geom-gcn-geometric-graph-convolutional-1 | 89.95 ± 0.47 |
revisiting-heterophily-for-graph-neural | 89.89 ± 0.43 |
joint-adaptive-feature-smoothing-and-topology | 87.54 ± 0.38 |
non-local-graph-neural-networks | 88.2 ± 0.5 |
generalizing-graph-neural-networks-beyond | 89.49 ± 0.38 |
non-local-graph-neural-networks | 89.0 ± 0.5 |
revisiting-heterophily-for-graph-neural | 88.49 ± 0.51 |
addressing-heterophily-in-node-classification | 89.20 ± 0.34 |
beyond-low-frequency-information-in-graph | 88.09 ± 1.38 |
gread-graph-neural-reaction-diffusion | - |
revisiting-heterophily-for-graph-neural | 89.71 ± 0.48 |