Node Classification On Squirrel 60 20 20
المقاييس
1:1 Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | 1:1 Accuracy |
|---|---|
| semi-supervised-classification-with-graph | 44.76 ± 1.39 |
| revisiting-heterophily-for-graph-neural | 40.91 ± 1.39 |
| inductive-representation-learning-on-large | 41.26 ± 0.26 |
| revisiting-heterophily-for-graph-neural | 46.4 ± 1.13 |
| graph-attention-networks | 42.72 ± 0.33 |
| revisiting-heterophily-for-graph-neural | 55.73 ± 2.39 |
| node-oriented-spectral-filtering-for-graph | 58.9±0.35 |
| revisiting-heterophily-for-graph-neural | 55.97 ± 2.03 |
| half-hop-a-graph-upsampling-approach-for | 47.19 ± 1.21 |
| joint-adaptive-feature-smoothing-and-topology | 49.93 ± 0.53 |
| simplifying-graph-convolutional-networks | 41.25 ± 1.4 |
| revisiting-heterophily-for-graph-neural | 69.98 ± 1.53 |
| break-the-ceiling-stronger-multi-scale-deep | 47.88 ± 1.23 |
| gnndld-graph-neural-network-with-directional | 77.72±0.84 |
| revisiting-heterophily-for-graph-neural | 53.40 ± 1.90 |
| predict-then-propagate-graph-neural-networks | 34.77 ± 0.34 |
| revisiting-heterophily-for-graph-neural | 52.28 ± 3.61 |
| bernnet-learning-arbitrary-graph-spectral | 51.35 ± 0.73 |
| revisiting-heterophily-for-graph-neural | 31.28 ± 0.27 |
| half-hop-a-graph-upsampling-approach-for | 45.25 ± 1.52 |
| revisiting-heterophily-for-graph-neural | 68.56 ± 1.33 |
| simple-and-deep-graph-convolutional-networks-1 | 38.81 ± 1.97 |
| half-hop-a-graph-upsampling-approach-for | 46.35 ± 1.86 |
| revisiting-heterophily-for-graph-neural | 53.48 ± 0.6 |
| beyond-low-frequency-information-in-graph | 42.24 ± 1.2 |
| revisiting-heterophily-for-graph-neural | 69.81 ± 1.11 |
| simple-and-deep-graph-convolutional-networks-1 | 38.31 ± 1.3 |
| simplifying-graph-convolutional-networks | 47.62 ± 1.27 |
| revisiting-heterophily-for-graph-neural | 38.32 ± 1.5 |
| geom-gcn-geometric-graph-convolutional-1 | 38.14 |
| break-the-ceiling-stronger-multi-scale-deep | 48.25 ± 0.94 |
| generalizing-graph-neural-networks-beyond | 30.39 ± 1.22 |
| revisiting-heterophily-for-graph-neural | 40.9 ± 1.58 |
| mixhop-higher-order-graph-convolution | 24.55 ± 2.60 |
| revisiting-heterophily-for-graph-neural | 52.31 ± 1.57 |
| revisiting-heterophily-for-graph-neural | 54.53 ± 2.09 |
| revisiting-heterophily-for-graph-neural | 69.26 ± 1.11 |