Node Classification on Facebook

Metric: Accuracy (higher is better)

LeaderboardDataset

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#	Model↕	Accuracy▼	Extra Data	Paper	Date↕	Code
1	DEMO-Net(weight)	91.9	No	DEMO-Net: Degree-specific Graph Neural Networks ...	2019-06-05	Code
2	GCN_cheby (Kipf and Welling, 2017)	64.6	No	Semi-Supervised Classification with Graph Convol...	2016-09-09	Code
3	Intersection (Li et al., 2018)	59.8	No	Deeper Insights into Graph Convolutional Network...	2018-01-22	Code
4	GCN (Kipf and Welling, 2017)	57.5	No	Semi-Supervised Classification with Graph Convol...	2016-09-09	Code
5	GraphSAGE (Hamilton et al., [2017a])	38.9	No	Inductive Representation Learning on Large Graphs	2017-06-07	Code

#1DEMO-Net(weight)SOTA
91.9
Accuracy· 2019-06-05
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification Code
#2GCN_cheby (Kipf and Welling, 2017)SOTA
64.6
Accuracy· 2016-09-09
Semi-Supervised Classification with Graph Convolutional Networks Code
#3Intersection (Li et al., 2018)
59.8
Accuracy· 2018-01-22
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning Code
#4GCN (Kipf and Welling, 2017)
57.5
Accuracy· 2016-09-09
Semi-Supervised Classification with Graph Convolutional Networks Code
#5GraphSAGE (Hamilton et al., [2017a])
38.9
Accuracy· 2017-06-07
Inductive Representation Learning on Large Graphs Code