Node Classification On Citeseer 60 20 20

评估指标

1:1 Accuracy

评测结果

各个模型在此基准测试上的表现结果

		Paper Title	Repository
GNNDLD	86.3±1.24	GNNDLD: Graph Neural Network with Directional Label Distribution	-
FAGCN	82.37 ± 1.46	Beyond Low-frequency Information in Graph Convolutional Networks
ACM-GCNII	82.28 ± 1.12	Revisiting Heterophily For Graph Neural Networks
ACMII-Snowball-2	82.07 ± 1.04	Revisiting Heterophily For Graph Neural Networks
ACMII-GCN+	81.87 ± 1.38	Revisiting Heterophily For Graph Neural Networks
ACM-GCN++	81.83 ± 1.65	Revisiting Heterophily For Graph Neural Networks
GCNII*	81.83 ± 1.78	Simple and Deep Graph Convolutional Networks
ACMII-GCN	81.79 ± 0.95	Revisiting Heterophily For Graph Neural Networks
ACMII-GCN++	81.76 ± 1.25	Revisiting Heterophily For Graph Neural Networks
ACM-GCNII*	81.69 ± 1.25	Revisiting Heterophily For Graph Neural Networks
ACM-GCN+	81.65 ± 1.48	Revisiting Heterophily For Graph Neural Networks
GCNII	81.58 ± 1.3	Simple and Deep Graph Convolutional Networks
ACM-Snowball-2	81.58 ± 1.23	Revisiting Heterophily For Graph Neural Networks
ACMII-Snowball-3	81.56 ± 1.15	Revisiting Heterophily For Graph Neural Networks
Snowball-2	81.53 ± 1.71	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
GCN	81.39 ± 1.23	Semi-Supervised Classification with Graph Convolutional Networks
ACM-Snowball-3	81.32 ± 0.97	Revisiting Heterophily For Graph Neural Networks
ACM-SGC-1	80.96 ± 0.93	Revisiting Heterophily For Graph Neural Networks
ACM-SGC-2	80.93 ± 1.16	Revisiting Heterophily For Graph Neural Networks
Snowball-3	80.93 ± 1.32	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks

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