Node Classification On Citeseer 60 20 20

المقاييس

1:1 Accuracy

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	1:1 Accuracy	Paper Title	Repository
Snowball-2	81.53 ± 1.71	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
GraphSAGE	78.24 ± 0.30	Inductive Representation Learning on Large Graphs
FAGCN	82.37 ± 1.46	Beyond Low-frequency Information in Graph Convolutional Networks
APPNP	68.59 ± 0.30	Predict then Propagate: Graph Neural Networks meet Personalized PageRank
GCNII	81.58 ± 1.3	Simple and Deep Graph Convolutional Networks
GNNDLD	86.3±1.24	GNNDLD: Graph Neural Network with Directional Label Distribution	-
ACM-Snowball-3	81.32 ± 0.97	Revisiting Heterophily For Graph Neural Networks
BernNet	80.09 ± 0.79	BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation
GPRGNN	67.63 ± 0.38	Adaptive Universal Generalized PageRank Graph Neural Network
ACM-SGC-1	80.96 ± 0.93	Revisiting Heterophily For Graph Neural Networks
ACMII-GCN++	81.76 ± 1.25	Revisiting Heterophily For Graph Neural Networks
MLP-2	76.25 ± 0.28	Revisiting Heterophily For Graph Neural Networks
ACM-GCNII*	81.69 ± 1.25	Revisiting Heterophily For Graph Neural Networks
SGC-2	80.75 ± 1.15	Simplifying Graph Convolutional Networks
ACM-GCNII	82.28 ± 1.12	Revisiting Heterophily For Graph Neural Networks
ACM-GCN++	81.83 ± 1.65	Revisiting Heterophily For Graph Neural Networks
H2GCN	79.97 ± 0.69	Beyond Low-frequency Information in Graph Convolutional Networks
Geom-GCN*	77.99	Geom-GCN: Geometric Graph Convolutional Networks
ACM-SGC-2	80.93 ± 1.16	Revisiting Heterophily For Graph Neural Networks
ACMII-GCN+	81.87 ± 1.38	Revisiting Heterophily For Graph Neural Networks

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