Node Classification On Texas 60 20 20 Random
المقاييس
1:1 Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | 1:1 Accuracy |
|---|---|
| revisiting-heterophily-for-graph-neural | 92.26 ± 0.71 |
| simple-and-deep-graph-convolutional-networks-1 | 88.52 ± 3.02 |
| geom-gcn-geometric-graph-convolutional-1 | 67.57 |
| revisiting-heterophily-for-graph-neural | 95.08 ± 2.07 |
| revisiting-heterophily-for-graph-neural | 93.44 ± 2.54 |
| predict-then-propagate-graph-neural-networks | 91.18 ± 0.70 |
| bernnet-learning-arbitrary-graph-spectral | 93.12 ± 0.65 |
| revisiting-heterophily-for-graph-neural | 92.46 ± 1.97 |
| revisiting-heterophily-for-graph-neural | 96.56 ± 2 |
| node-oriented-spectral-filtering-for-graph | 94.03±0.82 |
| revisiting-heterophily-for-graph-neural | 80.66 ± 1.91 |
| simplifying-graph-convolutional-networks | 81.31 ± 3.3 |
| inductive-representation-learning-on-large | 79.03 ± 1.20 |
| simple-and-deep-graph-convolutional-networks-1 | 82.46 ± 4.58 |
| revisiting-heterophily-for-graph-neural | 94.92 ± 2.79 |
| joint-adaptive-feature-smoothing-and-topology | 92.92 ± 0.61 |
| revisiting-heterophily-for-graph-neural | 93.61 ± 1.55 |
| revisiting-heterophily-for-graph-neural | 95.25 ± 1.55 |
| half-hop-a-graph-upsampling-approach-for | 80.54 ± 4.80 |
| revisiting-heterophily-for-graph-neural | 75.41 ± 7.18 |
| half-hop-a-graph-upsampling-approach-for | 71.89 ± 3.46 |
| revisiting-heterophily-for-graph-neural | 94.75 ± 3.09 |
| break-the-ceiling-stronger-multi-scale-deep | 83.11 ± 3.2 |
| graph-attention-networks | 78.87 ± 0.86 |
| simplifying-graph-convolutional-networks | 83.28 ± 5.43 |
| revisiting-heterophily-for-graph-neural | 94.75 ± 2.91 |
| generalizing-graph-neural-networks-beyond | 85.90 ± 3.53 |
| break-the-ceiling-stronger-multi-scale-deep | 83.11 ± 3.2 |
| beyond-low-frequency-information-in-graph | 88.85 ± 4.39 |
| mixhop-higher-order-graph-convolution | 76.39 ± 7.66 |
| revisiting-heterophily-for-graph-neural | 95.41 ± 2.82 |
| revisiting-heterophily-for-graph-neural | 94.75 ± 2.41 |
| revisiting-heterophily-for-graph-neural | 95.74 ± 2.22 |
| revisiting-heterophily-for-graph-neural | 93.28 ± 2.79 |
| half-hop-a-graph-upsampling-approach-for | 85.95 ± 6.42 |
| semi-supervised-classification-with-graph | 83.11 ± 3.2 |