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SOTA
Node Classification
Node Classification On Aifb
Node Classification On Aifb
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
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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Node Classification On Aifb | SOTA | HyperAI