Node Classification On Cornell 60 20 20
المقاييس
1:1 Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | 1:1 Accuracy |
|---|---|
| half-hop-a-graph-upsampling-approach-for | 72.7 ± 4.26 |
| revisiting-heterophily-for-graph-neural | 93.77 ± 2.17 |
| graph-attention-networks | 76.00 ± 1.01 |
| inductive-representation-learning-on-large | 71.41 ± 1.24 |
| break-the-ceiling-stronger-multi-scale-deep | 82.95 ± 2.1 |
| revisiting-heterophily-for-graph-neural | 94.75 ± 3.8 |
| semi-supervised-classification-with-graph | 82.46 ± 3.11 |
| half-hop-a-graph-upsampling-approach-for | 74.6 ± 6.06 |
| simple-and-deep-graph-convolutional-networks-1 | 90.49 ± 4.45 |
| revisiting-heterophily-for-graph-neural | 93.93 ± 1.05 |
| revisiting-heterophily-for-graph-neural | 95.9 ± 1.83 |
| revisiting-heterophily-for-graph-neural | 94.92 ± 2.79 |
| revisiting-heterophily-for-graph-neural | 95.08 ± 3.11 |
| revisiting-heterophily-for-graph-neural | 93.44 ± 2.74 |
| revisiting-heterophily-for-graph-neural | 91.30 ± 0.70 |
| simplifying-graph-convolutional-networks | 70.98 ± 8.39 |
| beyond-low-frequency-information-in-graph | 88.03 ± 5.6 |
| simplifying-graph-convolutional-networks | 72.62 ± 9.92 |
| generalizing-graph-neural-networks-beyond | 86.23 ± 4.71 |
| geom-gcn-geometric-graph-convolutional-1 | 60.81 |
| revisiting-heterophily-for-graph-neural | 92.62 ± 2.57 |
| revisiting-heterophily-for-graph-neural | 66.56 ± 13.82 |
| joint-adaptive-feature-smoothing-and-topology | 91.36 ± 0.70 |
| break-the-ceiling-stronger-multi-scale-deep | 82.62 ± 2.34 |
| bernnet-learning-arbitrary-graph-spectral | 92.13 ± 1.64 |
| revisiting-heterophily-for-graph-neural | 93.93 ± 3.03 |
| revisiting-heterophily-for-graph-neural | 92.62 ± 3.13 |
| predict-then-propagate-graph-neural-networks | 91.80 ± 0.63 |
| revisiting-heterophily-for-graph-neural | 94.26 ± 2.57 |
| revisiting-heterophily-for-graph-neural | 93.61 ± 2.79 |
| simple-and-deep-graph-convolutional-networks-1 | 89.18 ± 3.96 |
| revisiting-heterophily-for-graph-neural | 93.77 ± 1.91 |
| revisiting-heterophily-for-graph-neural | 95.25 ± 1.55 |
| revisiting-heterophily-for-graph-neural | 74.43 ± 10.24 |
| mixhop-higher-order-graph-convolution | 60.33 ± 28.53 |
| half-hop-a-graph-upsampling-approach-for | 63.24 ± 5.43 |