Node Classification On Non Homophilic 1

المقاييس

1:1 Accuracy

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

جدول المقارنة

اسم النموذج	1:1 Accuracy
graph-attention-networks	71.01 ± 4.66
mixhop-higher-order-graph-convolution	77.25 ± 7.80
revisiting-heterophily-for-graph-neural	94.63 ± 2.96
break-the-ceiling-stronger-multi-scale-deep	74.88 ± 3.42
inductive-representation-learning-on-large	64.85 ± 5.14
generalizing-graph-neural-networks-beyond	87.5 ± 1.77
revisiting-heterophily-for-graph-neural	96.63 ± 2.24
revisiting-heterophily-for-graph-neural	97.00 ± 2.63
revisiting-heterophily-for-graph-neural	62.50 ± 15.75
joint-adaptive-feature-smoothing-and-topology	93.75 ± 2.37
revisiting-heterophily-for-graph-neural	96.38 ± 2.59
revisiting-heterophily-for-graph-neural	93.25 ± 2.92
revisiting-heterophily-for-graph-neural	96.75 ± 1.79
geom-gcn-geometric-graph-convolutional-1	64.12
revisiting-heterophily-for-graph-neural	94.00 ± 2.61
new-benchmarks-for-learning-on-non	93.87 ± 3.33
break-the-ceiling-stronger-multi-scale-deep	69.5 ± 5.01
predict-then-propagate-graph-neural-networks	92.00 ± 3.59
revisiting-heterophily-for-graph-neural	94.37 ± 2.81
revisiting-heterophily-for-graph-neural	97.13 ± 1.68
revisiting-heterophily-for-graph-neural	95.75 ± 2.03
revisiting-heterophily-for-graph-neural	97.5 ± 1.25
simplifying-graph-convolutional-networks	70.38 ± 2.85
revisiting-heterophily-for-graph-neural	96.62 ± 1.86
semi-supervised-classification-with-graph	75.5 ± 2.92
revisiting-heterophily-for-graph-neural	96.62 ± 2.44
beyond-low-frequency-information-in-graph	89.75 ± 6.37
simple-and-deep-graph-convolutional-networks-1	83.25 ± 2.69
simple-and-deep-graph-convolutional-networks-1	89.12 ± 3.06
revisiting-heterophily-for-graph-neural	96.5 ± 2.08
simplifying-graph-convolutional-networks	74.75 ± 2.89
revisiting-heterophily-for-graph-neural	69.50 ± 3.12