Node Classification on BGS

Metric: Accuracy (higher is better)

LeaderboardDataset

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#	Model↕	Accuracy▼	Extra Data	Paper	Date↕	Code
1	SCENE	92.41	No	SCENE: Reasoning about Traffic Scenes using Hete...	2023-01-09	Code
2	BoP	90.34	No	From Primes to Paths: Enabling Fast Multi-Relati...	2024-11-17	Code
3	RDF2Vec+SVM	87.24	No	-	-	Code
4	Path Tree	86.9	No	-	-	Code
5	RR-GCN-PPV-CUT	84.14	No	R-GCN: The R Could Stand for Random	2022-03-04	Code
6	R-GCN	83.1	No	Modeling Relational Data with Graph Convolutiona...	2017-03-17	Code
7	RR-GCN-PPV	78.97	No	R-GCN: The R Could Stand for Random	2022-03-04	Code

#1SCENESOTA
92.41
Accuracy· 2023-01-09
SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks Code
#2BoP
90.34
Accuracy· 2024-11-17
From Primes to Paths: Enabling Fast Multi-Relational Graph Analysis Code
#3RDF2Vec+SVM
87.24
Accuracy
No paperCode
#4Path Tree
86.9
Accuracy
No paperCode
#5RR-GCN-PPV-CUTSOTA
84.14
Accuracy· 2022-03-04
R-GCN: The R Could Stand for Random Code
#6R-GCNSOTA
83.1
Accuracy· 2017-03-17
Modeling Relational Data with Graph Convolutional Networks Code
#7RR-GCN-PPV
78.97
Accuracy· 2022-03-04
R-GCN: The R Could Stand for Random Code