Node Classification On Aifb

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

		Paper Title
R-GCN	95.83	Modeling Relational Data with Graph Convolutional Networks
RR-GCN-PPV-CUT	95.83	R-GCN: The R Could Stand for Random
SCENE	95.83	SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks
BoP	92.22	From Primes to Paths: Enabling Fast Multi-Relational Graph Analysis
Path Tree	89.44	Inducing a Decision Tree with Discriminative Paths to Classify Entities in a Knowledge Graph
RDF2Vec+SVM	88.88	RDF2Vec: RDF Graph Embeddings and Their Applications
RR-GCN-PPV	86.11	R-GCN: The R Could Stand for Random

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